Skill list

Number	Name	Actions
1	Describe emerging geographical analysis techniques in geocomputation derived from artificial intelligence e.g., expert systems, artificial neural networks, genetic algorithms, and software agents	View
2	Describe difficulties in dealing with large spatial databases, especially those arising from spatial heterogeneity	View
3	Explain what is meant by the term contaminated data, suggesting how it can arise	View
4	Explain how to recognize contaminated data in large datasets	View
5	Outline the implications of complexity for the application of statistical ideas in geography	View
6	Describe how data mining can be used for geospatial intelligence	View
7	Differentiate between data mining approaches used for spatial and non-spatial applications	View
8	Compare and contrast the primary types of data mining: summarization/characterization, clustering/categorization, feature extraction, and rule/relationships extraction	View
9	Explain how spatial statistics techniques are used in spatial data mining	View
10	Explain how the analytical reasoning techniques, visual representations, and interaction techniques that make up the domain of visual analytics have a strong spatial component	View
11	Demonstrate how cluster analysis can be used as a data mining tool	View
12	Interpret patterns in space and time using Dorling and Openshaws Geographical Analysis Machine GAM demonstration of disease incidence diffusion	View
13	Explain how spatial data mining techniques can be used for knowledge discovery	View
14	Explain how visual data exploration can be combined with data mining techniques as a means of discovering research hypotheses in large spatial datasets	View
15	Explain how a Bayesian framework can incorporate expert knowledge in order to retrieve all relevant datasets given an initial user query	View
22	Define the following terms pertaining to a network: Loops, multiple edges, the degree of a vertex, walk, trail, path, cycle, fundamental cycle	View
23	Define different interpretations of cost in various routing applications	View
24	Describe networks that apply to specific applications or industries	View
25	Create a data set with network attributes and topology	View
26	Demonstrate how networks can be measured using the number of elements in a network, the distances along network edges, and the level of connectivity of the network	View
27	Explain the concept of the diameter of a network	View
28	Compute the estimated number of fundamental cycles in a graph	View
29	Compute the alpha, beta, and gamma indices of network connectivity	View
30	Compute the Detour Index and the measure of network density for a given network	View
31	Describe some variants of Dijkstras algorithm that are even more efficient	View
32	Explain how a leading World Wide Web-based routing system works e.g., MapQuest, Yahoo Maps, Google	View
33	Discuss the difference of implementing Dijkstras algorithm in raster and vector modes	View
34	Demonstrate how K-shortest path algorithms can be implemented to find many efficient alternate paths across the network	View
35	Compute the optimum path between two points through a network with Dijkstras algorithm	View
36	Describe practical situations in which flow is conserved while splitting or joining at nodes of the network	View
37	xplain how the concept of capacity represents an upper limit on the amount of flow through the network	View
38	Demonstrate how capacity is assigned to edges in a network using the appropriate data structure	View
39	Apply a maximum flow algorithm to calculate the largest flow from a source to a sink, using the edges of the network, subject to capacity constraints on the arcs and the conservation of flow	View
40	Explain why, if supply equals demand, there will always be a feasible solution to the Classic Transportation Problem	View
41	Exemplify the Classic Transportation Problem	View
42	Demonstrate how the Classic Transportation Problem can be structured as a linear program	View
43	Implement the Transportation Simplex method to determine the optimal solution	View
44	List several classic problems to which network analysis is applied e.g., The Traveling Salesman Problem, The Chinese Postman Problem	View
45	Explain why heuristic solutions are generally used to address the combinatorially complex nature of these problems and the difficulty of solving them optimally	View
46	List ways we can define accessibility on a network	View
47	Describe methods for measuring different kinds of accessibility on a network	View
48	Contrast accessibility modeling at the individual level versus at an aggregated level	View
49	Compare current accessibility models with early models of market potential	View
50	Explain how optimization models can be used to generate models of alternate options for presentation to decision makers	View
51	Explain the concept of solution space	View
52	Explain the principles of operations research modeling and location modeling	View
53	Explain, using the concept of combinatorial complexity, why some location problems are very hard to solve	View
54	Compare and contrast the concepts of discrete location problems and continuous location problems	View
55	Describe the structure of linear programs	View
56	Explain the role of objective functions in linear programming	View
57	Explain the role of constraint functions using the graphical method	View
58	Explain the role of constraint functions using the simplex method	View
59	Implement linear programs for spatial allocation problems	View
60	Differentiate between a linear program and an integer program	View
61	Explain why integer programs are harder to solve than linear programs	View
62	Describe the structure of origin-destination matrices	View
63	Explain the concepts of demand and service	View
64	Explain Webers locational triangle	View
65	Assess the outcome of location-allocation models using other spatial analysis techniques	View
66	Compare and contrast covering, dispersion, and p-median models	View
67	Locate, using location-allocation software, service facilities that meet given sets of constraints	View
68	Compare and contrast the impacts of different conversion approaches, including the effect on spatial components	View
69	Prioritize a set of algorithms designed to perform transformations based on the need to maintain data integrity [e.g., converting a digital elevation model (DEM) into a TIN]	View
70	Create a flowchart showing the sequence of transformations on a data set (e.g., geometric and radiometric correction and mosaicking of remotely sensed data)	View
71	Identify the conceptual and practical difficulties associated with data model and format conversion	View
72	Describe a workflow for converting a implementing a data model in a GIS involving an Entity-Relationship (E-R) diagram and the Universal Modeling Language (UML)	View
73	Discuss the role of metadata in facilitating conversation of data models and data structures between systems	View
75	Differentiate among common interpolation techniques (e.g., nearest neighbor, bilinear, bicubic)	View
76	Explain how the elevation values in a digital elevation model (DEM) are derived by interpolation from irregular arrays of spot elevations	View
77	Discuss the pitfalls of using secondary data that has been generated using interpolations (e.g., Level 1 USGS DEMs)	View
78	Estimate a value between two known values using linear interpolation (e.g., spot elevations, population between census years)	View
79	Explain how the vector/raster/vector conversion process of graphic images and algorithms takes place and how the results are achieved	View
80	Convert vector data to raster format and back using GIS software	View
81	Illustrate the impact of vector/raster/vector conversions on the quality of a dataset	View
82	Create estimated tessellated data sets from point samples or isolines using interpolation operations that are appropriate to the specific situation	View
83	Discuss the consequences of increasing and decreasing resolution	View
84	Evaluate methods used by contemporary GIS software to resample raster data on-the-fly during display	View
85	Select appropriate interpolation techniques to resample particular types of values in raster data (e.g., nominal using nearest neighbor)	View
86	Resample multiple raster data sets to a single resolution to enable overlay	View
87	Resample raster data sets (e.g., terrain, satellite imagery) to a resolution appropriate for a map of a particular scale	View
88	Cite appropriate applications of several coordinate transformation techniques (e.g., affine, similarity, Molodenski, Helmert)	View
89	Differentiate between polynomial coordinate transformations (including linear) and rubbersheeting	View
90	Describe the impact of map projection transformation on raster and vector data	View
91	Compare and contrast spatial statistical analysis, spatial data analysis, and spatial modeling	View
92	Compare and contrast spatial statistics and map algebra as two very different kinds of data analysis	View
93	Compare and contrast the methods of analyzing aggregate data as opposed to methods of analyzing a set of individual observations	View
94	Define the terms spatial analysis, spatial modeling, geostatistics, spatial econometrics, spatial statistics, qualitative analysis, map algebra, and network analysis	View
95	Differentiate between geostatistics, and spatial statistics	View
96	Discuss situations when it is desirable to adopt a spatial approach to the analysis of data	View
97	Explain what is added to spatial analysis to make it spatio-temporal analysis	View
98	Explain what is special i.e., difficult about geospatial data analysis and why some traditional statistical analysis techniques are not suited to geographic problems	View
99	Outline the sequence of tasks required to complete the analytical process for a given spatial problem	View
100	Describe set theory	View
101	Explain how set theory relates to spatial queries	View
102	Explain how logic theory relates to set theory	View
103	Perform a logic set theoretic query using GIS software	View
104	Define basic terms of query processing e.g., SQL, primary and foreign keys, table join	View
105	Explain the basic logic of SQL syntax	View
106	Demonstrate the basic syntactic structure of SQL	View
107	Create an SQL query to retrieve elements from a GIS	View
108	Demonstrate the syntactic structure of spatial and temporal operators in SQL	View
109	Compare and contrast attribute query and spatial query	View
110	State questions that can be solved by selecting features based on location or spatial relationships	View
111	Construct a query statement to search for a specific spatial or temporal relationship	View
112	Construct a spatial query to extract all point objects that fall within a polygon	View
113	Describe several different measures of distance between two points e.g., Euclidean, Manhattan, network distance, spherical	View
114	Explain how different measures of distance can be used to calculate the spatial weights matrix	View
115	Explain why estimating the fractal dimension of a sinuous line has important implications for the measurement of its length	View
116	Explain how fractal dimension can be used in practical applications of GIS	View
117	Explain the differences in the calculated distance between the same two places when data used are in different projections	View
118	Outline the implications of differences in distance calculations on real world applications of GIS, such as routing and determining boundary lengths and service areas	View
119	Estimate the fractal dimension of a sinuous line	View
120	Define direction and its measurement in different angular measures	View
121	Compare and contrast how direction is determined and stated in raster and vector data	View
122	Describe operations that can be performed on qualitative representations of direction	View
123	Explain any differences in the measured direction between two places when the data are presented in a GIS in different projections	View
124	Compute the mean of directional data	View
125	Identify situations in which shape affects geometric operations	View
126	Explain what is meant by the convex hull and minimum enclosing rectangle of a set of point data	View
127	Explain why the shape of an object might be important in analysis	View
128	Exemplify situations in which the centroid of a polygon falls outside its boundary	View
129	Compare and contrast different shape indices, include examples of applications to which each could be applied	View
130	Develop a method for describing the shape of a cluster of similarly valued points by using the concept of the convex hull	View
131	Develop an algorithm to determine the skeleton of polygons	View
132	Find centroids of polygons under different definitions of a centroid and different polygon shapes	View
133	Calculate several different shape indices for a polygon dataset	View
134	List reasons why the area of a polygon calculated in a GIS might not be the same as the real world object it describes	View
135	Explain how variations in the calculation of area may have real world implications, such as calculating density	View
136	Demonstrate how the area of a region calculated from a raster data set will vary by resolution and orientation	View
137	Outline an algorithm to find the area of a polygon using the coordinates of its vertices	View
138	Describe real world applications where distance decay is an appropriate representation of the strength of spatial relationships (e.g., shopping behavior, property values)	View
139	Describe real world applications where distance decay would not be an appropriate representation of the strength of spatial relationships (e.g., distance education, commuting, telecommunications)	View
140	Explain the rationale for using different forms of distance decay functions	View
141	Explain how a semi-variogram describes the distance decay in dependence between data values	View
142	Outline the geometry implicit in classical gravity models of distance decay	View
143	Plot typical forms for distance decay functions	View
144	Write typical forms for distance decay functions	View
145	Write a program to create a matrix of pair-wise distances among a set of points	View
146	List different ways connectivity can be determined in a raster and in a polygon dataset	View
147	Describe real world applications where adjacency and connectivity are a critical component of analysis	View
148	Explain the nine-intersection model for spatial relationships	View
149	Demonstrate how adjacency and connectivity can be recorded in matrices	View
150	Calculate various measures of adjacency in a polygon dataset	View
151	Create a matrix describing the pattern of adjacency in a set of planar enforced polygons	View
152	Describe how map algebra performs mathematical functions on raster grids	View
153	Describe a real modeling situation in which map algebra would be used e.g., site selection, climate classification, least-cost path	View
154	Explain the categories of map algebra operations i.e., local, focal, zonal, and global functions	View
155	Explain why georegistration is a precondition to map algebra	View
156	Differentiate between map algebra and matrix algebra using real examples	View
157	Perform a map algebra calculation using command line, form-based, and flow charting user interfaces	View
158	Compute measures of overall dispersion and clustering of point datasets using nearest neighbor distance statistics	View
159	List the conditions that make point pattern analysis a suitable process	View
160	Identify the various ways point patterns may be described	View
161	Identify various types of K-function analysis	View
162	Describe how Independent Random Process/Chi-Squared Result IRP/CSR may be used to make statistical statements about point patterns	View
163	Outline measures of pattern based on first and second order properties such as the mean centre and standard distance, quadrat counts, nearest neighbor distance and the more modern G, F and K functions	View
164	Outline the basis of classic critiques of spatial statistical analysis in the context of point pattern analysis	View
165	Explain how distance-based methods of point pattern measurement can be derived from a distance matrix	View
166	Explain how proximity polygons e.g., Thiessen polygons may be used to describe point patterns	View
167	Explain how the K function provides a scale-dependent measure of dispersion	View
168	Describe the relationships between kernels and classical spatial interaction approaches, such as surfaces of potential	View
169	Differentiate between kernel density estimation and spatial interpolation	View
170	Outline the likely effects on analysis results of variations in the kernel function used and the bandwidth adopted	View
171	Explain why and how density estimation transforms point data into a field representation	View
172	Explain why, in some cases, an adaptive bandwidth might be employed	View
173	Create density maps from point datasets using kernels and density estimation techniques using standard software	View
174	Identify several cluster detection techniques and discuss their limitations	View
175	Discuss the characteristics of the various cluster detection techniques	View
176	Demonstrate the extension of spatial clustering to deal with clustering in space-time using the Know and Mantel tests	View
177	Perform a cluster detection analysis to detect hot spots in a point pattern	View
178	State the classic formalization of the interaction model	View
179	Differentiate between the gravity model and spatial interaction models	View
180	Describe the formulation of the classic gravity model, the unconstrained spatial interaction model, the production constrained spatial interaction model, the attraction constrained spatial interaction model, and the doubly constrained spatial...	View
181	Explain how dynamic, chaotic, complex or unpredictable aspects in some phenomena make spatial interaction models more appropriate than gravity models	View
182	Explain the concept of competing destinations, describing how traditional spatial interaction model forms are modified to account for it	View
183	Create a matrix that shows spatial interaction	View
184	Relate plots of multidimensional attribute data to geography by equating similarity in data space with proximity in geographical space	View
185	Assemble a data matrix of attributes	View
186	Produce plots in several data dimensions using a data matrix of attributes	View
187	Conduct a simple hierarchical cluster analysis to classify area objects into statistically similar regions	View
188	Perform multidimensional scaling (MDS) and principal components analysis (PCA) to reduce the number of coordinates, or dimensionality, of a problem	View
192	Describe the implementation of an ordered weighting scheme in a multiple-criteria aggregation	View
193	Compare and contrast the terms multi-criteria evaluation, weighted linear combination, and site suitability analysis	View
194	Differentiate between contributing factors and constraints in a multi-criteria application	View
195	Explain the legacy of multi-criteria evaluation in relation to cartographic modeling	View
196	Determine which method to use to combine criteria e.g., linear, multiplication	View
197	Create initial weights using the analytical hierarchy process (AHP)	View
198	Calibrate a linear combination model by adjusting weights using a test data set	View
199	Discuss the relationship between spatial processes and spatial patterns	View
200	Differentiate between deterministic and stochastic spatial process models	View
201	Describe a simple process model that would generate a given set of spatial patterns	View
202	List the likely sources of error in slope and aspect maps derived from DEMs and state the circumstances under which these can be very severe	View
203	Outline a number of different methods for calculating slope from a Digital Elevation Model (DEM)	View
204	Outline how higher order derivatives of height can be interpreted	View
205	Explain how slope and aspect can be represented as the vector field given by the first derivative of height	View
206	Explain why the properties of spatial continuity are characteristic of spatial surfaces	View
207	Explain why zero slopes are indicative of surface specific points such as peaks, pits and passes and list the conditions necessary for each	View
208	Design an algorithm that calculates slope and aspect from a Triangulated Irregular Network (TIN) model	View
209	Identify the spatial concepts that are assumed in different interpolation algorithms	View
210	Describe how surfaces can be interpolated using splines	View
211	Compare and contrast interpolation by inverse distance weighting, bi-cubic spline fitting and kriging	View
212	Differentiate between trend surface analysis and deterministic spatial interpolation	View
213	Explain why different interpolation algorithms produce different results and suggest ways by which these can be evaluated in the context of a specific problem	View
214	Design an algorithm which interpolates irregular point elevation data onto a regular grid	View
215	Outline algorithms to produce repeatable contour-type lines from point datasets using proximity polygons, spatial averages, or inverse distance weighting	View
216	Implement a trend surface analysis using either the supplied function in a GIS or a regression function from any standard statistical package	View
217	Describe how a network of stream channels and ridges can be estimated from a Digital Elevation Model (DEM)	View
218	Explain how ridgelines and streamlines can be used to improve the result of an interpolation process	View
219	Define intervisibility	View
220	Explain the sources and impact of errors that affect intervisibility analyses	View
221	Outline an algorithm to determine the viewshed area visible from specific locations on surfaces specified by digital elevation models (DEM)	View
222	Perform siting analyses using specified visibility, slope, and other surface related constraints	View
223	Define friction surface	View
224	Explain how friction surfaces are enhanced by the use of impedance and barriers	View
225	Apply the principles of friction surfaces in the calculation of least-cost paths	View
226	Describe the statistical characteristics of a set of spatial data using a variety of graphs and plots including scatterplots, histograms, boxplots, qq plots	View
227	Select the appropriate statistical methods for the analysis of given spatial datasets by first exploring them using graphic methods	View
228	List the two basic assumptions of the purely random process	View
229	Justify the stochastic process approach to spatial statistical analysis	View
230	Exemplify deterministic and spatial stochastic processes	View
231	Exemplify non-stationarity involving first and second order effects	View
232	Differentiate between isotropic and anisotropic processes	View
233	Discuss the theory leading to the assumption of intrinsic stationarity	View
234	Outline the logic behind the derivation of long run expected outcomes of the independent random process using quadrat counts	View
235	Explain how different types of spatial weights matrices are defined and calculated	View
236	Explain the rationale used for each type of spatial weights matrix	View
237	Discuss the appropriateness of different types of spatial weights matrices for various problems	View
238	Construct a spatial weights matrix for lattice, point, and area patterns	View
239	Describe the effect of the assumption of stationarity on global measures of spatial association	View
240	Explain how a statistic that is based on combining all the spatial data and returning a single summary value or two can be useful in understanding broad spatial trends	View
241	Explain how the K function provides a scale-dependent measure of dispersion	View
242	Compute Morans I and Gearys c for patterns of attribute data measured on interval ratio scales	View
243	Compute measures of overall dispersion and clustering of point datasets using nearest neighbor distance statistics	View
244	Compute the K function	View
245	Justify, compute, and test the significance of the join count statistic for a pattern of objects	View
246	Describe the effect of non-stationarity on local indices of spatial association	View
247	Compare and contrast global and local statistics and their uses	View
248	Explain how a weights matrix can be used to convert any classical statistic into a local measure of spatial association	View
249	Explain how geographically weighted regression provides a local measure of spatial association	View
250	Decompose Morans I and Gearys c into local measures of spatial association	View
251	Compute the Gi and Gi* statistics	View
252	Explain how outliers affect the results of analyses	View
253	Explain how the following techniques can be used to examine outliers: tabulation, histograms, box plots, correlation analysis, scatter plots, local statistics	View
254	Define prior and posterior distributions and Markov-Chain Monte Carlo	View
255	Explain how the Bayesian perspective is a unified framework from which to view uncertainty	View
256	Compare and contrast Bayesian methods and classical frequentist statistical methods	View
257	List and describe several spatial sampling schemes and evaluate each one for specific applications	View
258	Describe sampling schemes for accurately estimating the mean of a spatial data set	View
259	Differentiate between model-based and design-based sampling schemes	View
260	Design a sampling scheme that will help detect when space-time clusters of events occur	View
261	Create spatial samples under a variety of requirements, such as coverage, randomness, transects	View
262	Identify and define the parameters of a semi-variogram range, sill, nugget	View
263	Describe the relationships between semi-variograms and correlograms, and Morans indices of spatial association	View
264	Demonstrate how semi-variograms react to spatial nonstationarity	View
265	Construct a semi-variogram and illustrate with a semi-variogram cloud	View
266	List the possible sources of error in a selected and fitted model of an experimental semi-variogram	View
267	Describe some commonly used semi-variogram models	View
268	Describe the conditions under which each of the commonly used semi-variograms models would be most appropriate	View
269	Explain the necessity of defining a semi-variogram model for geographic data	View
270	Apply the method of weighted least squares and maximum likelihood to fit semi-variogram models to datasets	View
271	Describe the relationship between the semi-variogram and kriging	View
272	Explain why kriging is more suitable as an interpolation method in some applications than others	View
273	Explain why it is important to have a good model of the semi-variogram in kriging	View
274	Explain the concept of the kriging variance, and describe some of its shortcomings	View
275	Explain how block-kriging and its variants can be used to combine data sets with different spatial resolution support	View
276	Compare block-kriging with areal interpolation using proportional area weighting and dasymetric mapping	View
277	Outline the basic kriging equations in their matrix formulation	View
278	Conduct a spatial interpolation process using kriging from data description to final error map	View
279	Compare and contrast co-kriging log-normal kriging, disjunctive kriging, indicator kriging, factorial kriging and universal kriging	View
280	Apply universal kriging to appropriate data sets	View
281	Interpret the results of universal kriging	View
282	Describe the general types of spatial econometric model	View
283	Explain how spatial dependence and spatial heterogeneity violate the Gauss-Markov assumptions of regression used in traditional econometrics	View
284	Demonstrate how spatially lagged, trend surface, or dummy spatial variables can be used to create the spatial component variables missing in a standard regression analysis	View
285	Demonstrate how the spatial weights matrix is fundamental in spatial econometrics models	View
286	Demonstrate why spatial autocorrelation among regression residuals can be an indication that spatial variables have been omitted from the models	View
287	Explain Anselins typology of spatial autoregressive models	View
288	Conduct a spatial econometric analysis to test for spatial dependence in the residuals from least-squares models and spatial autoregressive models	View
289	Demonstrate how the parameters of spatial auto-regressive models can be estimated using univariate and bivariate optimization algorithms for maximizing the likelihood function	View
290	Find a best model	View
291	Implement a maximum likelihood estimation procedure for determining key spatial econometric parameters	View
292	Apply spatial statistic software e.g., GEODA to create and estimate an autoregressive model	View
293	Identify modeling situations where spatial filtering might not be appropriate	View
294	Describe the relationship between factorial kriging and spatial filtering	View
295	Explain how spatial correlation can result as a side effect of the spatial aggregation in a given dataset	View
296	Explain how dissolving clusters of blocks with similar values may resolve the spatial correlation problem	View
297	Explain how the Getis and Tiefelsdorf Griffith spatial filtering techniques incorporate spatial component variables into OLS regression analysis in order to remedy misspecification and the problem of spatially auto-correlated residuals	View
298	Demonstrate how spatial autocorrelation can be removed by resampling	View
299	Describe the characteristics of the spatial expansion method	View
300	Discuss the appropriateness of GWR under various conditions	View
301	Explain how allowing the parameters of the model to vary with the spatial location of the sample data can be used to accommodate spatial heterogeneity	View
302	Explain the principles of geographically weighted regression	View
303	Compare and contrast GWR with universal kriging using moving neighborhoods	View
304	Perform an analysis using the geographically weighted regression technique	View
305	Analyze the number of degrees of freedom in GWR analyses and discuss any possible difficulties with the method based on your results	View
306	Define common theories on what is real, such as realism, idealism, relativism, and experiential realism	View
307	Evaluate the influences of particular worldviews (including ones own) on GIS practices	View
308	Identify the ontological assumptions underlying the work of colleagues	View
309	Justify the metaphysical theories with which you agree	View
310	Compare and contrast the ability of different theories to explain various situations	View
311	Recognize the commonalities of philosophical viewpoints and appreciate differences to enable work with diverse colleagues	View
312	Define common theories on what constitutes knowledge, including positivism, reflectance-correspondence, pragmatism, social constructivism, and memetics	View
313	Explain the notions of model and representation in science	View
314	Recognize the influences of epistemology on GIS practices	View
315	Justify the epistemological frameworks with which you agree	View
316	Compare and contrast the ability of various theories to explain different situations	View
317	Identify the epistemological assumptions underlying the work of colleagues	View
318	Bridge the differences in epistemological viewpoints to enable work with diverse colleagues	View
319	Define common philosophical theories that have influenced geography and science, such as logical positivism, Marxism, phenomenology, feminism, and critical theory	View
320	Defend or refute the statement, All data are theory-laden	View
321	Describe a brief history of major philosophical movements relating to the nature of space, time, geographic phenomena and human interaction with it	View
322	Compare and contrast the kinds of questions various philosophies ask, the methodologies they use, the answers they offer, and their applicability to different phenomena	View
323	Evaluate the influences of ones own philosophical views and assumptions on GIS AND T practices	View
324	Identify the philosophical views and assumptions underlying the work of colleagues	View
325	Describe the differences between real phenomena, conceptual models, and GIS data representations thereof	View
326	Compare and contrast the symbolic and connectionist theories of human cognition and memory and their ability to model various cases	View
327	Compare and contrast theories of spatial knowledge acquisition (e.g., Marr on vision, Piaget on childhood, Golledge on wayfinding)	View
328	Explain the role of metaphors and image schema in our understanding of geographic phenomena and geographic tasks	View
329	Explore the contribution of linguistics to the study of spatial cognition and the role of natural language in the conceptualization of geographic phenomena	View
330	Define the following terms: data, information, knowledge, and wisdom	View
331	Transform a conceptual model of information for a particular task into a data model	View
332	Describe the limitations of various information stores for representing geographic information, including the mind, computers, graphics, text, etc.	View
333	Define the properties that make a phenomenon geographic	View
334	Describe some insights that a spatial perspective can contribute to a given topic	View
335	Justify or refute whether geography (as a discipline) should have a central role in GIS AND T	View
336	Explore the history of geography including (but not limited to) Greek and Roman contributions to geography (Eratosthenes, Strabo, Ptolemy), geography and cartography in the age of discovery, military geography, and geography...	View
337	Justify a chosen position on which disciplines should have as important a role in GIS AND T as geography	View
338	Discuss the differing denotations and connotations of the terms spatial, geographic, and geospatial	View
339	Explain how the concept of place is more than just location	View
340	Define the notions of cultural landscape and physical landscape	View
341	Select a place or landscape with personal meaning and discuss its importance	View
342	Evaluate the differences in how various parties think or feel differently about a place being modeled	View
343	Describe the elements of a sense of place or landscape that are difficult or impossible to adequately represent in GIS	View
344	Differentiate between space and place	View
345	Differentiate among elements of the meaning of a place that can or cannot be easily represented using geospatial technologies	View
346	Describe the ways in which the elements of culture (e.g., language, religion, education, traditions) may influence the understanding and use of geographic information	View
347	Recognize the impact of ones social background on ones own geographic worldview and perceptions and how it influences ones use of GIS	View
348	Collaborate effectively with colleagues of differing social backgrounds in developing balanced GIS applications	View
349	Evaluate the influences of political ideologies (e.g., Marxism, Capitalism, conservative liberal) on the understanding of geographic information	View
350	Evaluate the influences of political actions, especially the allocation of territory, on human perceptions of space and place	View
351	Recognize the constraints that political forces place on geospatial applications in public and private sectors	View
352	Identify common-sense views of geographic phenomena that sharply contrast with established theories and technologies of geographic information	View
353	Evaluate the impact of geospatial technologies (e.g., Google Earth) that allow non-geospatial professionals to create, distribute, and map geographic information	View
354	Effectively communicate the design, procedures, and results of GIS projects to non-GIS audiences (clients, managers, general public)	View
355	Collaborate with non-GIS experts who use GIS to design applications that match common-sense understanding to an appropriate degree	View
356	Differentiate applications that can make use of common-sense principles of geography from those that should not	View
357	Define the four basic dimensions or shapes used to describe spatial objects (i.e., points, lines, regions, volumes)	View
358	Differentiate between absolute and relative descriptions of location	View
359	Differentiate between common-sense, Cartesian metric, relational, relativistic, phenomenological, social constructivist, and other theories of the nature of space	View
360	Discuss the contributions that different perspectives on the nature of space bring to an understanding of geographic phenomenon	View
361	Justify the discrepancies between the nature of locations in the real world and representations thereof (e.g., towns as points)	View
362	Select appropriate spatial metaphors and models of phenomena to be represented in GIS	View
363	Develop methods for representing non-cartesian models of space in GIS	View
364	Discuss the advantages and disadvantages of the use of cartesian metric space as a basis for GIS and related technologies	View
365	Differentiate between mathematical and phenomenological theories of the nature of time	View
366	Exemplify different temporal frames of reference: linear and cyclical, absolute and relative	View
367	Recognize the role that time plays in static GISystems	View
368	Compare and contrast models of a given spatial process using continuous and discrete perspectives of time	View
369	Select the temporal elements of geographic phenomena that need to be represented in particular GIS applications	View
370	Discuss common prepositions and adjectives (in any particular language) that signify either spatial or temporal relations but are used for both kinds, such as after or longer	View
371	Compare and contrast the characteristics of spatial and temporal dimensions	View
372	Identify various types of geographic interactions in space and time	View
373	Describe different types of movement and change	View
374	Understand the physical notions of velocity and acceleration which are fundamentally about movement across space through time	View
375	Define Stevens four levels of measurement (nominal, ordinal, interval, ratio)	View
376	Recognize attribute domains that do not fit well into Stevens four levels of measurement (nominal, ordinal, interval, ratio), such as cycles, indexes, and hierarchies	View
377	Describe particular geographic phenomena in terms of attributes	View
378	Characterize the domains of attributes in a GIS, including continuous and discrete, qualitative and quantitative, absolute and relative	View
379	Determine the proper uses of attributes based on their domains	View
380	Recognize situations and phenomena in the landscape which cannot be adequately represented by formal attributes, such as aesthetics	View
381	Formalize attribute values and domains in terms of set theory	View
382	Compare and contrast the theory that properties are fundamental (and objects are human simplifications of patterns thereof) with the theory that objects are fundamental (and properties are attributes thereof)	View
383	Develop alternative forms of representations for situations in which attributes do not adequately capture meaning	View
384	Justify or refute the conception of fields (e.g., temperature, density) as spatially-intensive attributes of (sometimes amorphous and anonymous) entities	View
385	Model gray area phenomena, such as categorical coverages (a.k.a. discrete fields), in terms of objects	View
386	Evaluate the influence of scale on the conceptualization of entities	View
387	Discuss the human predilection to conceptualize geographic phenomena in terms of discrete entities	View
388	Describe particular entities in terms of space, time, and properties	View
389	Describe the perceptual processes (e.g., edge detection) that aid cognitive objectification	View
390	Compare and contrast differing epistemological and metaphysical viewpoints on the reality of geographic entities	View
391	Identify the types of features that need to be modeled in a particular GIS application or procedure	View
392	Identify phenomena that are difficult or impossible to conceptualize in terms of entities	View
393	Describe the difficulties in modeling entities with ill-defined edges	View
394	Describe the difficulties inherent in extending the tabletop metaphor of objects to the geographic environment	View
395	Evaluate the effectiveness of GIS data models for representing the identity, existence, and lifespan of entities	View
396	Define a field in terms of properties, space, and time	View
397	Identify applications and phenomena that are not adequately modeled by the field view	View
398	Identify examples of discrete and continuous change found in spatial, temporal, and spatio-temporal fields	View
399	Differentiate various sources of fields, such as substance properties (e.g., temperature), artificial constructs (e.g., population density), and fields of potential or influence (e.g., gravity)	View
400	Formalize the notion of field using mathematical functions and Calculus	View
401	Relate the notion of field in GIS to the mathematical notions of scalar and vector fields	View
402	Recognize the influences of scale on the perception and meaning of fields	View
403	Evaluate the representation of movement as a field of location over time (e.g. :x,y,z: = f(t) )	View
404	Evaluate the field views description of objects as conceptual discretizations of continuous patterns	View
405	Compare and contrast the concepts of continuants (entities) and occurrents (events)	View
406	Compare and contrast the concepts of event and process	View
407	Describe particular events or processes in terms of identity, categories, attributes, locations, etc.	View
408	Evaluate the assertion that events and processes are the same thing, but viewed at different temporal scales	View
409	Apply or develop formal systems for describing continuous spatio-temporal processes	View
410	Describe the actor role that entities and fields play in events and processes	View
411	Discuss the difficulty of integrating process models into GIS software based on the entity and field views, and methods used to do so	View
412	Discuss the contributions of early attempts to integrate the concepts of space, time, and attribute in geographic information, such as Berry (1964) and Sinton (1978)	View
413	Illustrate major integrated models of geographic information, such as Peuquets Triad, Mennis Pyramid, and Yuans Three-Domain	View
414	Determine whether phenomena or applications exist that are not adequately represented in an existing comprehensive model	View
415	Discuss the degree to which these models can be implemented using current technologies	View
416	Design data models for specific applications based on these comprehensive general models	View
417	Reconcile differing common-sense and official definitions of common geospatial categories of entities, attributes, space, and time	View
418	Explain the human tendency to simplify the world using categories	View
419	Identify specific examples of categories of entities (i.e., common nouns), properties (i.e., adjectives), space (i.e., regions), and time (i.e., eras)	View
420	Explain the role of categories in common-sense conceptual models, everyday language, and analytical procedures	View
421	Recognize and manage the potential problems associated with the use of categories (e.g., the ecological fallacy)	View
422	Construct taxonomies and dictionaries (also known as formal ontologies) to communicate systems of categories	View
423	Describe the contributions of category theory to understanding the internal structure of categories	View
424	Document the personal, social, and or institutional meaning of categories used in GIS applications	View
425	Create or use GIS data structures to represent categories, including attribute columns, layers themes, shapes, legends, etc.	View
426	Use categorical information in analysis, cartography, and other GIS processes, avoiding common interpretation mistakes	View
427	Describe ways in which a geographic entity can be created from one or more others	View
428	Describe the genealogy (as identity-based change or temporal relationships) of particular geographic phenomena	View
429	Determine whether it is important to represent the genealogy of entities for a particular application	View
430	Discuss the effects of temporal scale on the modeling of genealogical structures	View
431	Find spatial patterns in the distribution of geographic phenomena using geographic visualization and other techniques	View
432	Discuss the causal relationship between spatial processes and spatial patterns, including the possible problems in determining causality	View
433	Hypothesize the causes of a pattern in the spatial distribution of a phenomenon	View
434	Differentiate among distributions in space, time, and attribute	View
435	Identify influences of scale on the appearance of distributions	View
436	Employ techniques for visualizing, describing, and analyzing distributions in space, time, and attribute	View
437	Delineate regions using properties, spatial relationships, and geospatial technologies	View
438	Exemplify regions found at different scales	View
439	Explain the relationship between regions and categories	View
440	Differentiate among different types of regions, including functional, cultural, physical, administrative, and others	View
441	Identify the kinds of phenomena that are commonly found at the boundaries of regions	View
442	Explain why general-purpose regions rarely exist	View
443	Compare and contrast the opportunities and pitfalls of using regions to aggregate geographic information (e.g., census data)	View
444	Use established analysis methods that are based on the concept of region (e.g., landscape ecology)	View
445	Explain the nature of the Modifiable Areal Unit Problem (MAUP)	View
446	Describe the ways in which a spatial perspective enables the synthesis of different subjects (e.g., climate and economy)	View
447	Describe the common constraints on spatial integration	View
448	Use established analysis methods that are based on the concept of spatial integration (e.g., overlay)	View
449	Describe particular geographic phenomena in terms of their place in mereonomic hierarchies (parts and composites)	View
450	Identify phenomena that are best understood as networks	View
451	Explain the modeling of structural relationships in standard GIS data models, such as stored topology	View
452	Represent structural relationships in GIS data	View
453	Explain the effects of spatial or temporal scale on the perception of structure	View
454	Explain the contributions of formal mathematical methods such as Graph Theory to the study and application of geographic structures	View
455	Define various terms used to describe topological relationships, such as disjoint, overlap, within, and intersect	View
456	Describe geographic phenomena in terms of their topological relationships (in space and time to other phenomena	View
457	List the possible topological relationships between entities in space (e.g., 9-intersection) and time	View
458	Use methods that analyze topological relationships	View
459	Recognize the contributions of Topology (the branch of mathematics) to the study of geographic relationships	View
460	Describe geographic phenomena in terms of their distances and directions (in space and time) Define spatial autocorrelation in the context of geographic proximity	View
461	Define spatial autocorrelation in the context of geographic proximity	View
462	Use methods that analyze metrical relationships	View
463	Identify situations in which Toblers First Law of Geography is valuable	View
464	Identify situations in which Toblers First Law of Geography does not apply	View
465	Explain why Toblers First Law of Geography is fundamental to many operations in GIS and whether it should be	View
466	Define the principle of friction of distance and geographic models that are based on it (e.g., gravity models, spatial interaction models)	View
467	Compare and contrast the meanings of related terms such as vague, fuzzy, imprecise, indefinite, indiscrete, unclear, and ambiguous	View
468	Evaluate the role that system complexity, dynamic processes, and subjectivity play in the creation of vague phenomena and concepts	View
469	Identify the hedges used in language to convey vagueness	View
470	Describe the cognitive processes that tend to create vagueness	View
471	Differentiate applications in which vagueness is an acceptable trait from those in which it is unacceptable	View
472	Recognize the degree to which vagueness depends on scale	View
473	Evaluate vagueness in the locations, time, attributes, and other aspects of geographic phenomena	View
474	Differentiate between the following concepts: vagueness and ambiguity, well defined and poorly defined objects and fields or discord and non-specificity	View
475	Define uncertainty-related terms, such as error, accuracy, uncertainty, precision, stochastic, probabilistic, deterministic, and random	View
476	Differentiate uncertainty in geospatial situations from vagueness	View
477	Recognize the degree to which the importance of uncertainty depends on scale and application	View
478	Recognize expressions of uncertainty in language	View
479	Evaluate the causes of uncertainty in geospatial data	View
480	Describe a stochastic error model for a natural phenomenon	View
481	Explain how the familiar concepts of geographic objects and fields affect the conceptualization of uncertainty	View
482	Describe the basic principles of randomness and probability	View
483	Devise simple ways to represent probability information in GIS	View
484	Recognize the assumptions underlying probability and geostatistics and the situations in which they are useful analytical tools	View
485	Compute descriptive statistics and geostatistics of geographic data	View
486	Interpret descriptive statistics and geostatistics of geographic data	View
500	Create different map layouts using the same map components (main map area, inset maps, titles, legends, scale bars, north arrows, grids and graticule) to produce maps with very distinctive purposes	View
501	Create different maps using the same data for different purposes and intended audiences (e.g., expert and novice hikers)	View
502	List the major factors that should be considered in preparing a map	View
503	Describe the design needs of special purpose maps such as subdivision plans, cadastral mapping, drainage plans, nautical charts, aeronautical charts, geological maps, military maps, wire-mesh volume maps, and 3D plans of urban change	View
504	Describe differences in design needed for a map that is to be viewed on the Internet versus as a 5x7 foot poster, including a discussion of the effect of viewing distance, lighting, and media type	View
505	Discuss how to create an intellectual and visual hierarchy on maps	View
506	Discuss the differences between maps that use the same data but are for different purposes and intended audiences	View
507	Discuss the differences between maps that use the same data but are for different purposes and intended audiences	View
508	Critique the graphic design of several maps in terms of balance, legibility, clarity, visual contrast, figure-ground organization, and hierarchal organization	View
510	Design maps that are appropriate for users with vision limitations	View
515	List the range of factors that should be considered in selecting colors	View
517	Discuss how cultural differences with respect to color associations impact map design	View
518	Explain the common color models used in mapping	View
520	Discuss the role of gamut in choosing colors that can be reproduced on various devices and media	View
521	Explain how real-world connotations (e.g., blue=water, white=snow) can be used to determine color selections on maps	View
524	Build a set of mapping problems that can be used to illustrate point, line, and area label conventions for placing text on maps	View
525	Solve a labeling problem for a dense collection of features on a map using minimal leader lines	View
528	Contrast the strengths and limitations of methods for automatic label placement	View
529	Compare the relative merits of having map labels placed dynamically versus having them saved as annotation data	View
530	Explain how text properties can be used as visual variables to graphically represent the type and attributes of geographic features	View
531	Explain how to label features with indeterminate boundaries (canyons, oceans, etc.)	View
533	Apply the appropriate technology to place name labels on a map using a geographic names database	View
534	Select type font, size, style and color for labels on a map by applying basic typography design principles	View
535	Select a technique that can be used to represent the value of each of the components of data quality (positional and attribute accuracy, logical consistency, and completeness)	View
536	Apply multivariate and dynamic visualization methods to display uncertainty in data	View
537	Outline a map with a reliability overlay using symbols suited to reliability representations	View
538	Develop graphic techniques that clearly show different forms of inexactness (e.g., existence uncertainty, boundary location uncertainty, attribute ambiguity, transitional boundary) of a given feature (e.g., a culture region)	View
539	Explain the design considerations for different thematic maps	View
540	Evaluate the strengths and limitations of different thematic mapping methods	View
541	Propose thematic mapping methods for mapping numerical data	View
542	Choose suitable mapping methods for each attribute of a given type of feature in a GIS (e.g., roads with various attributes such as surface type, traffic flow, number of lanes, direction such as one-way, etc.)	View
543	Select base information suited to providing a frame of reference for thematic map symbols (e.g., network of major roads and state boundaries underlying national population map)	View
544	Create maps using each of the following methods: choropleth, dasymetric, proportioned symbol, graduated symbol, isoline, dot, cartogram, and flow map	View
545	Create well-designed legends using the appropriate conventions for the following methods: choropleth, dasymetric, proportioned symbol, graduated symbol, isoline, dot, cartogram, and flow map	View
546	Describe situations in which methods of terrain representation (e.g., shaded relief, contours, hypsometric tints, block diagrams, profiles) are well or poorly suited	View
548	Differentiate 3D representations from 2.5 D representations	View
549	Explain how maps that show the landscape in profile can be used to represent terrain	View
550	Create a map that represents both slope and aspect on the same map using the Moellering-Kimerling coloring method	View
553	Find a multivariate outlier using a combination of maps and graphs	View
554	Design a map series to show the change in a geographic pattern over time	View
555	Design a single map symbol that can be used to symbolize a set of related variables	View
556	Create a map that displays related variables using different mapping methods (e.g., choropleth and proportional symbol, choropleth and cartogram)	View
557	Create a map that displays related variables using the same mapping method (e.g., bivariate choropleth map, bivariate dot map)	View
558	Demonstrate how the adding time-series data reveals (or not) patterns not evident in a cross-sectional data	View
559	Illustrate how an animated map reveals patterns not evident without animation	View
561	Create a temporal sequence representing a dynamic geospatial process	View
562	Explain how interactivity influences map use	View
563	Describe a mapping goal in which the use of each of the following would be appropriate: brushing, linking, multiple displays	View
564	Discuss the uses of the map as a user interface element in interactive presentations of geographic information	View
565	Critique the interactive elements of an online map	View
566	Develop a useful interactive interface and legend	View
567	Build an animated map for a specified purpose	View
568	Build an interactive map suitable for a given audience	View
569	Describe considerations for using maps on the Web as a method for downloading data	View
570	Discuss the influence of the user interface on maps and visualizations on the Web	View
571	Critique the user interface for existing Internet mapping services	View
572	Construct a Web page that includes an interactive map	View
573	Edit the symbology, labeling, and page layout for a map originally designed for hard copy printing so that it can be seen and used on the Web	View
574	Illustrate the use of virtual environments	View
575	Explain how the virtual and immersive environments become increasingly more complex as we move from the relatively non-immersive VRML desktop environment to a stereoscopic display (e.g., a GeoWall) to a more fully immersive CAVE	View
576	List software and hardware environments supporting immersive visualization	View
577	Discuss about the advantages of different immersive display systems	View
579	Explain how spatial metaphors can be used to illustrate the relationship among ideas	View
580	Explain how spatialization is a core component of visual analytics	View
581	Evaluate graphic techniques used to portray spatializations	View
582	Create a pseudo-topographic surface to portray the relationships in a collection of documents	View
583	Create a concept map that represents the contents and topology of a physical or social process	View
584	Describe print quality characteristics and price differences for limited-run color map distribution	View
585	Describe production concerns that might be discussed with a publisher who will print a map product	View
586	Compare and contrast the quality of product evaluation that can be made from process proofs and color laser prints	View
587	Outline the stages in lithographic offset printing	View
588	Prepare a color map for black-and-white photocopy distribution	View
589	Specify a print job for publication, including paper, ink, lpi, proof needs, press check and other contract decisions	View
590	Explain how maps such as topographic maps are produced within certain relations of power and knowledge	View
593	Select maps that illustrate the provocative, propaganda, political, and persuasive nature of maps and geospatial data	View
617	Perform a pilot study to evaluate the feasibility of an application	View
618	Justify feasibility recommendations to decision-makers	View
619	Identify potential sources of data (free or commercial) needed for a particular application or enterprise	View
620	Estimate the cost to collect needed data from primary sources (e.g., remote sensing, GPS)	View
625	Create a budget of expected labor costs, including salaries, benefits, training, and other expenses	View
642	Differentiate between conceptual and logical models, in terms of the level of detail, constraints, and range of information included	View
643	Define the cardinality of relationships	View
644	Explain the various types of cardinality	View
645	Distinguish between the temporary and structural relationships in a conceptual model	View
647	Evaluate the various general data models common in GIS project	View
648	Create logical models based on conceptual models using UML or other tools	View
649	Differentiate between logical and physical models, in terms of the level of detail, constraints, and range of information included	View
650	Recognize the constraints and opportunities of a particular choice of software for implementing a physical model	View
651	Create UML diagrams of physical models based on logical model diagrams and software requirements	View
652	Create a complete design document ready for implementation	View
653	Define basic terms used in the raster data model (e.g., cell, row, column, value)	View
654	Explain how the raster data model instantiates a grid representation	View
655	Interpret the header of a standard raster data file	View
656	Compare and contrast the raster with other types of regular tessellations for geographic data storage	View
657	Compare and contrast the raster with other types of regular tessellations for geographic data analysis	View
658	Write a program to read and write a raster data file	View
659	Explain how grid representations embody the field-based view	View
660	Differentiate among a lattice, a tessellation, and a grid	View
661	Explain how terrain elevation can be represented by a regular tessellation and by an irregular tessellation	View
662	Identify the national framework datasets based on a grid model	View
663	Illustrate the existing methods for compressing gridded data (e.g., run length encoding, Lempel-Ziv, wavelets)	View
664	Differentiate between lossy and lossless compression methods	View
665	Evaluate the relative merits of grid compression methods for storage	View
666	Explain the advantage of wavelet compression	View
667	Illustrate the hexagonal model	View
668	Exemplify the uses (past and potential) of the hexagonal model	View
669	Explain the limitations of the grid model compared to the hexagonal model	View
670	Describe the architecture of the TIN model	View
671	Demonstrate the use of the TIN model for different statistical surfaces (e.g., terrain elevation, population density, disease incidence) in a GIS software application	View
672	Describe how to generate a unique TIN solution using Delaunay triangulation	View
673	Construct a TIN manually from a set of spot elevations	View
674	Delineate a set of break lines that improve the accuracy of a TIN	View
675	Describe the conditions under which a TIN might be more practical than GRID	View
676	Relate the concept of grid cell resolution to the more general concept of support and granularity	View
677	Illustrate the impact of grid cell resolution on the information that can be portrayed	View
678	Evaluate the implications of changing grid cell resolution on the results of analytical applications by using GIS software	View
679	Evaluate the ease of measuring resolution in different types of tessellations	View
680	Illustrate the quadtree model	View
681	Describe the advantages and disadvantages of the quadtree model for geographic database representation and modeling	View
682	Describe alternatives to quadtrees for representing hierarchical tessellations (e.g., hextrees, r-trees, pyramids)	View
683	Explain how quadtrees and other hierarchical tessellations can be used to index large volumes of raster or vector data	View
684	Implement a format for encoding quadtrees in a data file	View
685	Evaluate the positive and negative impacts of this shift from integrated topological models	View
686	Define terms related to topology (e.g., adjacency, connectivity, overlap, intersect, logical consistency)	View
687	Illustrate a topological relation	View
688	Explain the advantages and disadvantages of topological data models	View
689	Demonstrate how a topological structure can be represented in a relational database structure	View
690	Exemplify the concept of planar enforcement (e.g., TIN triangles)	View
691	Discuss the role of graph theory in topological structures	View
692	Describe the integrity constraints of integrated topological models (e.g., POLYVRT)	View
693	Discuss the historical roots of the Census Bureaus creation of GBF/DIME as the foundation for the development of topological data structures	View
694	Explain why integrated topological models have lost favor in commercial GIS software	View
695	Discuss some of the difficulties of applying the standard process-pattern concept to lines and networks	View
696	Define the following terms pertaining to a network: Loops, multiple edges, the degree of a vertex, walk, trail, path, cycle, fundamental cycle	View
697	Demonstrate how a network is a connected set of edges and vertices	View
698	List definitions of networks that apply to specific applications or industries	View
699	Create an adjacency table from a sample network	View
700	Explain how a graph can be written as an adjacency matrix and how this can be used to calculate topological shortest paths in the graph	View
701	Create an incidence matrix from a sample network	View
702	Explain how a graph (network) may be directed or undirected	View
703	Demonstrate how attributes of networks can be used to represent cost, time, distance, or many other measures	View
704	Demonstrate how the star (or forward star) data structure, which is often employed when digitally storing network information, violates relational normal form, but allows for much faster search and retrieval in network databases	View
720	Explain the mathematical basis by which latitude and longitude locations are projected into x and y coordinate space	View
727	Differentiate rectification and orthorectification	View
728	Explain the role and selection criteria for ground control points (GCPs) in the georegistration of aerial imagery	View
729	Identify and explain an equation used to perform image-to-map registration	View
730	Identify and explain an equation used to perform image-to-image registration	View
731	Use GIS software to transform a given dataset to a specified coordinate system, projection, and datum	View
736	Describe the location and geometric characteristics of the principal point of an aerial image	View
739	Describe the elements of image interpretation	View
740	Use photo interpretation keys to interpret features on aerial photographs	View
741	Using a vertical aerial image, produce a map of land use/land cover classes	View
742	Calculate the nominal scale of a vertical aerial image	View
743	Calculate heights and areas of objects and distances between objects shown in a vertical aerial image	View
744	Explain the relevance of the concept parallax in stereoscopic aerial imagery	View
745	Outline the sequence of tasks involved in generating an orthoimage from a vertical aerial photograph	View
746	Evaluate the advantages and disadvantages of photogrammetric methods and LiDAR for production of terrain elevation data	View
747	Specify the technical components of an aerotriangulation system	View
748	Describe the source data, instrumentation, and workflow involved in extracting vector data (features and elevations) from analog and digital stereoimagery	View
749	Discuss the extent to which vector data extraction from aerial stereoimagery has been automated	View
750	Discuss future prospects for automated feature extraction from aerial imagery	View
751	Plan an aerial imagery mission in response to a given RFP and map of a study area, taking into consideration vertical and horizontal control, atmospheric conditions, time of year, and time of day	View
755	Illustrate the spectral response curves for basic environmental features (e.g., vegetation, concrete, bare soil)	View
756	Describe an application that requires integration of remotely sensed data with GIS and/or GPS data	View
757	Explain the concept of data fusion in relation to remote sensing applications in GIS and T	View
758	Compare common sensors by spatial resolution, spectral sensitivity, ground coverage, and temporal resolution [e.g., AVHRR, MODIS (intermediate resolution ~500 m, high temporal) Landsat, commercial high resolution (Ikonos and Quickbird); ...	View
759	Differentiate between active and passive sensors, citing examples of each	View
760	Differentiate push-broom and cross-track scanning technologies	View
761	Explain the principle of multibeam bathymetric mapping	View
762	Evaluate the advantages and disadvantages of airborne remote sensing versus satellite remote sensing	View
763	Evaluate the advantages and disadvantages of acoustic remote sensing versus airborne or satellite remote sensing for seafloor mapping	View
764	Select the most appropriate remotely sensed data source for a given analytical task, study area, budget, and availability	View
765	Differentiate supervised classification from unsupervised classification	View
766	Produce pseudocode for common unsupervised classification algorithms including chain method, ISODATA method, and clustering	View
767	Perform a manual unsupervised classification given a two-dimensional array of reflectance values and ranges of reflectance values associated with a given number of land cover categories	View
768	Calculate a set of filtered reflectance values for a given array of reflectance values and a digital image filtering algorithm	View
769	Describe a situation in which filtered data are more useful than the original unfiltered data	View
770	Describe the sequence of tasks involved in the geometric correction of the Advanced Very High Resolution Radiometer (AVHRR) Global Land Dataset	View
771	Compare pixel-based image classification methods with object-based techniques	View
772	Explain how to enhance contrast of reflectance values clustered within a narrow band of wavelengths	View
773	Describe an application of hyperspectral image data	View
774	Explain how U.S. Geological Survey scientists and contractors assess the accuracy of the National Land Cover Dataset	View
775	Evaluate the thematic accuracy of a given soils map	View
776	Outline a plausible workflow used by MDA Federal (formerly EarthSat) to create the high-resolution GEOCOVER global imagery and GEOCOVER-LC global land cover datasets	View
777	Outline a plausible workflow for habitat mapping, such as the benthic habitat mapping in the main Hawaiian Islands as part of the NOAA Biogeography program	View
778	Describe how sea surface temperatures are mapped	View
779	Explain how sea surface temperature maps are used to predict El Nino events	View
780	Digitize and georegister a specified vector feature set to a given geometric accuracy and topological fidelity thresholds using a given map sheet, digitizing tablet, and data entry software	View
781	Outline a workflow that can be used to train a new employee to update a county road centerlines database using digital aerial imagery and standard GIS editing tools	View
782	Outline the process of scanning and vectorizing features depicted on a printed map sheet using a given GIS software product, emphasizing issues that require manual intervention	View
783	Demonstrate the importance of a clean, relatively error-free database (together with an appropriate geodetic framework) with the use of GIS software	View
784	Modify spatial and attribute data while ensuring consistency within the database	View
785	Discuss the implication of long transactions on database integrity	View
786	Exemplify scenarios in which one would need to perform a number of periodic changes in a real GIS database	View
787	Explain how one would establish the criteria for monitoring the periodic changes in a real GIS database	View
788	Define a set of rules for modeling changes in spatial databases	View
789	Describe techniques for handling version control in spatial databases	View
790	Describe techniques for managing long transactions in a multi-user environment	View
791	Explain why logging and rollback techniques are adequate for managing short transactions	View
792	Design a test of reliability of change information (e.g., the logical consistency of updates to the TIGER database)	View
793	Implement a test of reliability of change information	View
794	Describe an application in which it is crucial to maintain previous versions of the database	View
795	Produce viable queries for change scenarios using GIS or database management tools	View
796	Describe existing algorithms designed for performing dynamic queries	View
797	Demonstrate how both the time criticality and the data security might determine whether one performs change detection on-line or off-line in a given scenario	View
798	Exemplify how the lack of a data librarian to manage data can have disastrous consequences on the resulting dataset	View
799	In contrast to the National Map Accuracy Standard, explain how the spatial accuracy of a digital road centerlines data set may be evaluated and documented	View
800	Explain the formula for calculating root mean square error	View
801	Compare the concepts of geometric accuracy and topological fidelity	View
802	Describe how geometric accuracy should be documented in terms of the FGDC metadata standard	View
803	State the geometric accuracies associated with the various orders of the U.S. horizontal geodetic control network	View
804	Explain how geometric accuracies associated with the various orders of the U.S. horizontal geodetic control network are assured	View
805	State the approximate number and spacing of control points in each order of the horizontal geodetic control network	View
806	Explain the factors that influence the geometric accuracy of data produced with Global Positioning System (GPS) receivers	View
807	Explain the concept of dilution of precision	View
808	Describe the impact of the concept of dilution of precision on the uncertainty of GPS positioning	View
809	Explain the principle of differential correction in relation to the global positioning system	View
810	Apply the National Map Accuracy Standard to calculate the accuracy associated with the various USGS topographic map scales	View
811	Compare the National Map Accuracy Standard with the ASPRS Coordinate Standard	View
812	Explain the distinction between thematic accuracy, geometric accuracy, and topological fidelity	View
813	Describe the different measurement levels on which thematic accuracy is based	View
814	Describe the component measures and the utility of a misclassification matrix	View
815	Discuss how measures of spatial autocorrelation may be used to evaluate thematic accuracy	View
816	Outline the SDTS and ISO TC211 standards for thematic accuracy	View
817	Illustrate and explain the distinction between resolution, precision, and accuracy	View
818	Illustrate and explain the distinctions between spatial resolution, thematic resolution, and temporal resolution	View
819	Discuss the implications of the sampling theorem (Lambda = 0.5 delta) to the concept of resolution	View
820	Differentiate among the spatial, spectral, radiometric, and temporal resolution of a remote sensing instrument	View
821	Explain how resampling affects the resolution of image data	View
822	Discuss the advantages and potential problems associated with the use of Minimum Mapping Unit (MMU) as a measure of the level of detail in land use, land cover, and soils maps	View
823	Calculate, in terms of ground area, the uncertainty associated with decimal coordinates specified to three, four, and five decimal places	View
824	Explain the concept of error propagation	View
825	Explain, in general terms, the difference between single and double precision and impacts on error propagation	View
826	Explain the distinction between primary and secondary data sources in terms of census data, cartographic data, and remotely sensed data	View
827	Describe a scenario in which data from a secondary source may pose obstacles to effective and efficient use	View
828	Discuss ways in which the geospatial profession is regulated under the U.S. legal regime	View
829	Compare and contrast and contrast the relationship of the geospatial profession and the U.S. legal regime with similar relationships in other countries	View
830	Discuss the status of the concept of privacy in the U.S. legal regime	View
831	Explain how data aggregation is used to protect personal privacy in data produced by the U.S. Census Bureau	View
832	Explain how conversion of land records data from analog to digital form increases risk to personal privacy	View
833	Compare and contrast geographic information technologies that are privacy-invasive, privacy-enhancing, and privacy-sympathetic	View
834	Explain the argument that human tracking systems enable geoslavery	View
837	List and describe the types of data maintained by local, state, and federal governments	View
838	Describe how geospatial data are used and maintained for land use planning, property value assessment, maintenance of public works, and other applications	View
839	Explain the concept of a spatial decision support system	View
840	Explain how geospatial information might be used in a taking of private property through a governments claim of its right of eminent domain	View
841	Describe a variety of philosophical frameworks upon which codes of professional ethics may be based	View
842	Discuss the ethical implications of a local government's decision to charge fees for its data	View
843	Describe a scenario in which you would find it necessary to report misconduct by a colleague or friend	View
844	Describe the individuals or groups to which GIS and T professionals have ethical obligations	View
845	Compare and contrast the ethical guidelines promoted by the GIS Certification Institute (GISCI) and the American Society for Photogrammetry and Remote Sensing (ASPRS)	View
846	Describe the sanctions imposed by ASPRS and GISCI on individuals whose professional actions violate the codes of ethics	View
847	Explain how one or more obligations in the GIS Code of Ethics may conflict with organizations proprietary interests	View
848	Propose a resolution to a conflict between an obligation in the GIS Code of Ethics and organizations proprietary interests	View
849	Explain the argument that GIS privileges certain views of the world over others	View
850	Identify alternatives to the algorithmic way of thinking that characterizes GIS	View
851	Discuss critiques of GIS as deterministic technology in relation to debates about the Quantitative Revolution in the discipline of geography	View
852	Describe the extent to which contemporary GIS and T supports diverse ways of understanding the world	View
853	Discuss the implications of interoperability on ontology	View
857	Defend or refute the contention that the masculinist culture of computer work in general, and GIS work in particular, perpetuates gender inequality in GIS and T education and training and occupational segregation in the GIS and T workforce	View
858	Explain the argument that GIS and remote sensing foster a disembodied way of knowing the world	View
859	Discuss the potential role of agency (individual action) in resisting dominant practices and in using GIS and T in ways that are consistent with feminist epistemologies and politics	View
860	Explain the argument that, throughout history, maps have been used to depict social relations	View
861	Explain how a tax assessors office adoption of GIS and T may affect power relations within a community	View
862	Discuss the production, maintenance, and use of geospatial data by a government agency or private firm from the perspectives of a taxpayer, a community organization, and a member of a minority group	View
863	Explain the argument that GIS is socially constructed	View
864	Describe the use of GIS from a political ecology point of view (e.g., consider the use of GIS for resource identification, conservation, and allocation by an NGO in Sub-Saharan Africa)	View
865	Defend or refute the contention that critical studies have an identifiable influence on the development of the information society in general and GIScience in particular	View
866	Analyze how using GIS and T as an integrating technology affects different models of management	View
867	Describe how GI S and T can be used in the decision-making process in organizations dealing with natural resource management, business management, public management or operations management	View
868	Differentiate an enterprise system from a department-centered GI system	View
869	Explain how GIS and T can be an integrating technology	View
870	Illustrate what functions a support or service center can provide to an organization using GIS and T	View
871	Calculate the estimated schedule required to carry out all of the implementation steps for an enterprise GIS of a given size	View
872	Describe the components of a needs assessment for an enterprise GIS	View
873	Exemplify each component of a needs assessment for an enterprise GIS	View
874	Indicate the possible justifications that can be used to implement an enterprise GIS	View
875	List some of the topics that should be addressed in a justification for implementing an enterprise GIS (e.g., return on investment, workflow, knowledge sharing)	View
881	Describe the differences between licensing, certification and accreditation in relation to GIS and T positions and qualifications	View
882	Discuss the status of professional and academic certification in GIS and T	View
883	Discuss how a code of ethics might be applied within an organization	View
884	Explain why it has been difficult for many agencies and organizations to define positions and roles for GIS and T professionals	View
885	Identify the qualifications needed for a particular GIS and T position	View
886	Identify the standard occupational codes that are relevant to GIS and T	View
887	Describe issues that may hinder implementation and continued successful operation of a GI system if effective methods of staff development are not included in the process	View
888	Outline methods (programs or processes) that provide effective staff development opportunities for GIS and T	View
889	Compare and contrast training methods utilized in a non-profit to those employed in a local government agency	View
890	Discuss different formats (tutorials, in house, online, instructor lead) for training and how they can be used by organizations	View
891	Discuss the National Research Council report on Learning to Think Spatially (2005) as it relates to spatial thinking skills needed by the GIS and T workforce	View
892	Find or create training resources appropriate for GIS and T workforce in a local government organization	View
893	Identify the particular skills necessary for users to perform tasks in three different workforce domains (e.g., small city, medium county agency, a business, or others)	View
894	Illustrate methods that are effective in providing opportunities for education and training when implementing a GIS in a small city	View
895	Teach necessary skills for users to successfully perform tasks in an enterprise GIS	View
896	Describe political, economic, administrative, and other social forces in agencies, organizations, and citizens that inhibit or promote sharing of geospatial and other data	View
899	Compare and contrast the impact effect of time for developing consensus-based standards with immediate operational needs	View
900	Explain how resistance to change affects the adoption of standards in an organization coordinating a GIS	View
901	Explain how a business case analysis can be used to justify the expense of implementing consensus-based standards	View
902	Identify organizations that focus on developing standards related to GIS and T	View
903	Identify standards that are used in GIS and T	View
904	Compare and contrast the missions, histories, constituencies, and activities of professional organizations including Association of American Geographers (AAG), America Society for Photogrammetry and Remote Sensing (ASPRS) ...	View
905	Discuss the mission, history, constituencies, and activities of the GIS Certification Institute (GISCI)	View
906	Identify conferences that are related to GIS and T hosted by professional organizations	View
907	Assess the involvement of non-GIS companies (e.g., Microsoft, Google) in the geospatial industry	View
908	Describe the U.S. geospatial industry including vendors, software, hardware and data	View
909	Describe three applications of geospatial technology for different workforce domains (e.g., first responders, forestry, water resource management, facilities management)	View
910	Explain why software products sold by U.S. companies may predominate in foreign markets, including Europe and Australia	View
937	Explain the principle of along track scanning (pushbroom technology)	View
938	Explain the advantages and disadvantages of the pushbroom system	View
939	Design workflows, procedures, and customized software tools for using geospatial technologies and methods	View
940	Develop effective mathematical and other models of spatial situations and processes	View
941	Understand spatial data models and structures	View
942	Design databases for spatial data management	View
944	Demonstrate why the system design is important in any GIS implementation	View
945	Interpret business needs and translate them to IT needs	View
946	Interpret user needs as an input for the design process	View
947	Model project workflows	View
948	Identify user locations, network connectivity, and data center server locations	View
949	Analyse suitability of a network	View
950	Identify data center platform tier configuration and identify platform selection for each tier	View
951	Identify platform assignment for each workflow software component peak transaction processing load	View
952	Define a methodology for gathering of requirements	View
953	Build a mechanism for converting the requirements into a product	View
954	Select from conflicting requirements	View
955	Develop use cases for potential applications using established techniques with potential users, such as questionnaires, interviews, focus groups, the Delphi method, and/or joint application development	View
956	Determine how to integrate or combine the proposed workflow with current applications running	View
957	Report existing and potential tasks in terms of workflow and information flow	View
958	Assess the relative importance and immediacy of the requirements	View
959	Compile the needs of individual users and tasks into enterprise-wide needs	View
960	Illustrate how a business process analysis can be used to identify requirements during a GIS implementation	View
962	Manage requirements using a management tool (such as Trello, JIRA, etc.)	View
963	Document existing and potential tasks in terms of workflow and information flow	View
965	Describe how spatial data and GIS&T can be integrated into a workflow process	View
966	Select among the most appropriate method for documenting a certain process	View
967	Create a user manual to help users understand a process or task	View
968	Choose the best symbols for representing different attributes	View
969	Design icons suitable for mapping different elements	View
970	Interpret different symbols and icons in a map	View
971	Relate the spatial dimension and the weight of mapped features with the attributes they represent	View
972	Create an aesthetic map icon library	View
973	Select a color palette appropriate for a representation	View
974	Identify the most appropriate color palette for an online map for visually-impaired people	View
975	Identify the most appropriate color palette for a printed map for visually-impaired people	View
976	Evaluate the colors used in a web map to be used indoors and outdoors	View
977	Select the most appropriate place in a map to place a label and a legend	View
978	Solve ambiguities in map label by selecting the most appropriate typography	View
979	Transform imagery into radiometrically/atmospherically corrected state	View
980	Apply EO metadata to satellite image to convert digital numbers (DN) of pixels into top-of-atmosphere (TOA) reflectance values	View
981	Understand sun, sun angle, and sensor parameters that influence top of atmosphere (TOA) reflectance	View
982	Atmospherically correct remotely sensed data to derive bottom of atmosphere (BOA) reflectance values from TOA data with the use of an appropriate radiative transfer modelling technique	View
983	Understand atmospheric parameters that influence bottom of atmosphere (BOA) reflectance	View
984	Choose and apply a method for atmospheric radiative transfer modelling like ATCOR	View
985	Produce a surface corrected version of image values from BOA reflectance that removes topographic effects based on an input DSM and equations representing the relationship between sun incidence angle relative to terrain surface orientation	View
986	Create a set of ground control points tying image coordinates to map coordinates of a reference dataset using a digital reference dataset or in-situ GPS measurements	View
987	Apply rational polynomial coefficients (RPCs) to refine georeference of satellite images	View
988	Understand how root mean squared error (RMSE) at tie points represents local spatial accuracy and enables calculation of total RMSE that informs about the average spatial accuracy of the entire image	View
990	Understand spatial reference systems and apply them to an EO dataset	View
991	Transform an EO dataset to map coordinates using a registered image of like geometry as a reference	View
992	Apply pan-sharpening to an image according to metadata settings	View
993	Measure reflectance of surfaces of vegetation types and other thematic classes in the field	View
994	Compare reflectance measurements from the field to reflectance values in radiometrically pre-processed EO data	View
995	Having in-depth knowledge of two of the three Copernicus-relevant topics: Land monitoring, Emergency response including Humanitarian action, and Climate change	View
996	designing the description of a service for the need of a particular user of EO information	View
997	Explain a use case of EO for smart cities, e.g. how EO derived information about urban green instrastructure supports designing nature based solutions for preserving ecosystem services	View
998	Determine requirements and quality criteria for an EO information product that serves spatial planners in monitoring soil sealing	View
1000	Describe the importance of geometric correction when using Earth Observation data	View
1001	Explain the main causes of geometric distortions	View
1003	Explain the results of an SDI assessment	View
1004	Compare different frameworks for assessing Spatial Data Infrastructures	View
1005	Design an SDI assessment framework and methodology for assessing and evaluating an SDI	View
1006	Describe the main advantages of object-based image analysis methods	View
1007	List the main segmentation methods used to group similar pixels into homogeneous objects	View
1008	Identify physical, semantic and spatial properties used to assigned objects to the target classes	View
1009	Explain the advantages and limitations of rule-based classification method	View
1010	Apply object-based image analysis methods for extracting information from optical imagery	View
1011	Develop and implement an object-based image analysis workflow for a specific application context	View
1012	Explain the importance of visualisation of cartographic materials over time	View
1013	Relate the science and technology of graphical representation of geographic data	View
1014	Choose from different options to create a map	View
1015	Propose a holistic historical perspective of maps creation and use	View
1016	Correlate map making methods with technological or societal factors across History	View
1017	Discuss about the History of Cartography in different cultures	View
1018	Illustrate the evolution of Cartography in different periods of time	View
1019	Interpret the impact of paper-based and web maps in their context	View
1020	Discuss the relationship between the history of exploration and the development of a more accurate map of the world	View
1021	List the costs and benefits (tangible or intangible) of implementing a GI project	View
1022	Identify major obstacles to the success of a GIS proposal	View
1023	Cite software licenses	View
1024	Identify the positions necessary to design and implement a GIS project / GI unit	View
1025	Apply methods for organising and budgeting resources	View
1026	Discuss the advantages and disadvantages of outsourcing elements of a GIS project / GI system	View
1027	Create proposals and presentations to secure funding	View
1028	Compare different design choices in developing spatial simulation models	View
1029	Discuss different ways of simulating space and visualizing model behaviour	View
1030	Explain how spatial simulation models can be used to advance scientific knowledge in different geographic scenarios (e.g. transportation, health geography, urban and regional analysis)	View
1031	Perform a simulation experiment using available simulation software	View
1032	Explain geocomputation, related concepts and how the two relate	View
1033	Identify and compare the scenarios on which geocomputation methods are relevant	View
1034	Understand how the theoretical roots and experimental emphasis on geocomputation are integrated	View
1035	Understand complexity in the broadest sense	View
1036	Outline the role of computational science in geocomputation	View
1037	Illustrate the relationships between geocomputation with other terms, disciplines and areas of knowledge	View
1038	Understand how geocomputation relates to other similar terms	View
1039	Identify the types of geography problems geocomputation solves	View
1040	Identify commonalities and patterns of geocomputation	View
1041	Compare commonalities and patterns of geocomputation to other related terms	View
1042	Define and discuss opportunities and limitations of computational science	View
1043	Examine how computational technology relates to geocomputation	View
1044	Understand the all-encompassing concepts of complexity	View
1045	Understand how complex systems operate	View
1046	Interpret how individual parts contained in a complex system relate to each other	View
1047	Outline the complex problems where geocomputation is relevant	View
1048	Understand the defining characteristics of simulation models, and their applicability	View
1049	Explain the role and purpose of computer simulation methods in geocomputation	View
1050	Explain the process simulation model development	View
1051	Evaluate the tradeoffs between abstraction and representativeness in simulation model development	View
1052	Differentiate between individual and aggregate models	View
1053	Understand how models are translated into differential equations for execution	View
1054	Explain what a cellular automata is and what its key components are	View
1055	Identify cellular automata principles and pattern	View
1056	Assess cellular automata for modeling geographical systems	View
1058	Explain what an agent-based model is and what its key components are	View
1059	Identify agent-based modelling principles and methodologies	View
1060	Assess agent-based models for simulating spatio-temporal systems	View
1061	Discuss concepts of space-time dynamics for spatial modeling	View
1062	Interpret when space-time dynamics can be used to study geographical phenomen	View
1063	Compare different options of combining space-time dynamics approaches in spatial modelling	View
1064	Understand how models can be specified into logical rules	View
1065	Evaluate when rule-based models can be applied to spatiotemporal problems	View
1066	Discuss options of combining rule-based models with other individual modelling approaches	View
1067	Describe properties of a particular DEM product	View
1068	Select an appropriate DEM product for usage in a specific application	View
1069	Explain how the Urban Atlas product quality depends on its source EO data and how this affects its usage for urban planning.	View
1070	Generate high quality time series by removing clouds and cloud shadows from the available images	View
1071	Apply various phenology metrics to map target land cover classes	View
1072	Identify anomalies by means of surface properties such as evapotranspiration (ET) or land surface temperature (LST) derived from satellite image time series	View
1073	Estimate the potential value of a historical map	View
1074	Convert historical maps in digital format	View
1075	Demonstrate how to georeference an historical map	View
1076	Discuss about the relationship between art and cartography	View
1077	Illustrate with examples the relationship between art and cartography at different historical moments	View
1078	Discuss how maps express relations of power	View
1079	Discuss about the degree of subjectivity and/or objectivity of a map	View
1080	Create two versions of the same map addressed to different targets	View
1081	Construct a new map from an existing one with a biased view	View
1082	Knowledge of the basic (selective) mechanism of the absorption/emission of electromagnetic radiation by atoms.	View
1083	Choose or define a new image extent to extract an image subset for further analysis	View
1084	Generate a layer stack from bands of various EO data sources	View
1085	Apply an interpretation key to visually digitize land cover in an optical EO image	View
1086	Explain how the NDVI relates to vegetation activity/health	View
1087	Explain the main two phases of the LCCS approach to land cover classification	View
1088	Explain the benefits of a flexible hierarchical classification system like LCCS	View
1089	Explain an application example where SVM is used for EO image classification	View
1090	Develop strategies and policies	View
1091	Plan and design project implementations	View
1092	Categorize different types of changes that can be identified from multitemporal images	View
1093	Analyse and understand impact / consequences.	View
1094	Analyse atmospheric EO measurements	View
1095	Compare human-induced emissions to natural sources	View
1096	Use EO products to forecast sunlight exposure	View
1097	Assess climate forecasts and projections	View
1098	Use EO products to conduct forecasts and projections	View
1099	Use EO products to conduct numerical simulations	View
1100	Understand how numerical prediction models work	View
1101	Interpret the output of numerical prediction models	View
1102	Use EO products to assess the risk of a disaster	View
1103	Use EO products to monitor disaster prone areas	View
1104	Use EO products to measure impact and/or recovery	View
1105	Assess EO measurements of affected area	View
1106	Plan emergency response actions	View
1107	Use EO products to assess land areas, its ecosystems, and its evolution	View
1108	Use EO products to plan land areas, its ecosystems, and its evolution	View
1109	Evaluate the impact of changes in land areas	View
1110	Analyse the suitability of the land area	View
1111	Explain how a specific EO technology supports the assessments of disasters and geohazards	View
1112	Explain the advantages of object-based classification approaches over pixel-based approaches	View
1113	Relate the spatial and spectral characteristics of EO data to the types and proportions of materials found within the scene and within pixel IFOVs to relabel spectral classes as information classes of a classification scheme	View
1114	Explain how stereoscopic imagery allows to derive an orthorectified image for the overlapping image areas	View
1115	Explain how a set of overlapping images/satellite scenes can provide digital elevation models used for orthorectification and 3D modelling	View
1116	Explain how band maths can be applied to derive an index that indicates a specific land cover type like vegetation	View
1117	Explain why radiometric correction is a key requirement for deriving indices with band maths	View
1118	Explain which principles a segmentation should follow to arrive at meaningful objects that are appropriate for a specific application	View
1120	Explain to customers the information derived from EO	View
1121	Understand the strategic meaning of DIAS in the user segment of Copernicus	View
1122	Explain the advantages of cloud-based processing over downloading and processing data locally	View
1123	List specifics competitive DIAS solutions over other	View
1124	Understand how positional/geometric accuracy of a dataset affects subsequent analysis	View
1126	Explain how the SAVI relates to soil and vegetation properties	View
1127	Explain how the NDSI relates to snow properties	View
1128	Explain an application example where the spectral indices are used for vegetation, water or snow monitoring	View
1129	Examine how the vegetation indices relates to the vegetation dynamics and health	View
1130	Examine how the water-related spectral indices relates to changes in the vegetation and soil water content	View
1131	Explain how fourier transformation is used to reduce noise in optical imagery	View
1132	Explain how a histogram is derived from an EO image	View
1133	Select a contrast stretch for an image	View
1134	Identify and explain methods of image enhancement	View
1135	Apply preparatory data manipulation	View
1136	Convert multispectral image into its principal components	View
1138	Explain the purpose of image pre-processing	View
1140	Apply Minimum Noise Fraction (MNF) to reduce the number of bands in a hyperspectral image	View
1141	Identify different types of noise and associated methods for their reduction	View
1142	Explain the role of Gram-Schmidt vector orthogonalization in pan-sharpening	View
1143	Outline the workflow for pan-sharpening an image with the PCA method	View
1144	Explain how image processing and analysis methods are used to derive geospatial information from Earth observation imagery	View
1145	Explain how minimum noise fraction makes use of principal components analysis for dimensionality reduction	View
1146	Compare different strategies of data assimilation	View
1147	Identify image fusion techniques to fill gaps in image time series caused by clouds and cloud shadow	View
1148	Understand how data augmentation can improve deep learning methods for image classification	View
1149	Discuss imputation methods for filling in missing data	View
1150	Generate fine-scale images at a high temporal resolution with a spatio-temporal image fusion method	View
1151	Explain how EO applications targeting several countries at once can profit from data harmonisation	View
1152	Create an integrated population distribution map from census data and EO-based land use classification	View
1153	Discuss the different types of resolution of Earth observation data	View
1154	Discuss the minimum spatial resolution required for detecting single houses in a satellite image	View
1155	Discuss how radiometric resolution influences the granularity of a land cover classification	View
1156	Discuss how different spectral resolution of EO sensors influences their potential for vegetation mapping	View
1157	Discuss the needs for high temporal resolution for analysing crop cycles in agriculture	View
1158	Understand the difficulties in searching and selecting satellite images with sufficient spatial coverage for time series analysis	View
1159	Discuss valid time ranges for images used for landslide mapping with pre- and post-event image comparison	View
1160	Compare different error metrics that are based on the error matrix	View
1161	Explain how the F-score is calculated	View
1162	Explain the procedure how to collect ground reference data for an image classification	View
1163	Explain how the Kappa statistics is different from the overall accuracy metric	View
1164	Explain the difference between the evaluation measures of precision and recall	View
1165	Explain why rapid mapping applications have high requirements in timely availability of Earth observation products	View
1166	Explain how user validation ensures a high enough product quality	View
1167	Understand how limited temporal completness affects the usefulness of a time series analysis	View
1168	Understand the relevance of topological consistency for linear network features derived from Earth observation data	View
1169	Identify critical design decisions that make an EO-derived map readable	View
1170	Explain why image understanding goes beyond feature extraction	View
1171	Produce a map of vegetation fraction from optical EO data	View
1172	Explain the value of the leaf area index for vegetation mapping	View
1173	Explain how the net primary production (NPP) can be derived from EO data	View
1174	Explain how stereo-imaging enables the derivation of information about elevation	View
1175	Produce a digital surface model from stereographic optical EO data	View
1176	Explain why multimodal distributions in training samples should be avoided when using the maximum likelihood classifier	View
1177	Produce zero-crossing maps for a DoG-filtered optical EO image	View
1178	Explain sensitivity of NDVI to the chlorophyll content of vegetation	View
1179	Understand the role of pruning for reducing overfitting when applying decision trees for various classification purposes	View
1180	Describe the role of machine learning classifiers to find patterns in the available data	View
1181	Explain the sensitivity of the Random Forests classifier to the number of trees and the number of variables used to split the tree nodes	View
1182	Explain the sensitivity of SVM to hyper-parameters	View
1183	Explain how the scale parameter influences the size of image segments	View
1184	Apply object-based classification methods for classifying very high resolution satellite images	View
1185	Explain how topological features can be used to differentiate between classes with a low inter-class variance	View
1186	Understand how satellite image time series can be used for mapping, trend analysis and change detection	View
1187	Understand the role of multi-temporal satellite images for identifying not only when a change occurred but also the changing drivers	View
1188	Understand the way in which Dynamic Time Warping can align shifted temporal sequences	View
1189	Understand the subjectivity of the visual interpretation	View
1190	Explain how the interpretation keys can be used for guiding the process of visual interpretation	View
1191	Explain how OGC standards can be used for sharing spatial data (including Earth Observation data) across different communities and computing infrastructures	View
1192	Understand the importance of using spatially independent validation samples to assess the quality of the classification results	View
1194	Discuss limitations of the different region-based segementation methods	View
1195	Discuss how low-pass filtering of an image impacts the resulting regions derived with watershed segmentation	View
1196	Transform HTML documents thorugh the Document Object Model (DOM)	View
1197	Develop a Javascript function that handles a GeoJSON file	View
1198	Create a sample HTML5 Web page	View
1199	Identify the extensions HTML5 brings over older HTML versions	View
1201	Explain the advantages of satellite image time series for change detection	View
1202	Recognize the importance of reproducible research as a fundamental pillar of modern science	View
1203	Understand the problems associated with the lack of reproducibility	View
1204	Apply a series of practices (steps and tasks) for reproducible research in different phases of a project	View
1205	Use software tools to automate the practice of reproducible research in daily work	View
1206	Plan a reproducibility project independently	View
1207	Outline the types of geospatial software architectures	View
1208	Explain the requirements that best match each geospatial software architecture	View
1209	Compare geospatial software architecture through cost-analysis framework	View
1210	Select the most appropriate technology to help decision-making	View
1211	Deliver a resources plan consistent with organisation’s concrete actions	View
1212	Explain the phases involved in a geodesign-based project	View
1213	Explain what a project is, and the difference between a project, programme, and product	View
1214	List the key elements of a project management	View
1215	Illustrate each of the project management areas with an example of a technique or tool used	View
1216	Select the most appropriate techniques for a EO*GI project	View
1217	List the phases of a project management life cycle	View
1218	Differentiate between copyleft and permissive licenses for a software product	View
1219	Outline key tasks involved in the application, development and marketing of proprietary GIS software	View
1220	Identify the viability of a proprietary GIS application	View
1221	Test all functionalities and data standards for interoperability	View
1222	Design a test project to demonstrate interoperability	View
1223	Build functionalities and services to ensure interoperability	View
1224	Define entities and relationships in conceptual data model	View
1225	Understand the degree to which attributes need to be conceptually modeled	View
1226	Explain the objectives of the design phase of a conceptual model	View
1227	Deconstruct an application use case into its conceptual elements	View
1228	Create a diagram of a conceptual data model for a geospatial application or enterprise database	View
1229	Design application-specific conceptual models	View
1231	Explain the main features and elements of Open Science	View
1232	Compare the different cultures of Open Science	View
1233	Identify the defining characteristics of an open geocomputation project	View
1234	Understand the main software engineering methodologies	View
1235	Decide which graphical representation better reflects the messages embedded in your story	View
1236	Illustrate the elements of the story by proper geovisualizations	View
1237	Illustrate the ways in which maps could be integrated in an infography	View
1238	Discuss the strengths and weaknesses of infographics as a method of displaying geographic information	View
1239	Describe an example where the use of an augmented environment could be of help	View
1240	Outline a process for acquiring feedback from target users throughout design and development	View
1241	Explain how it is possible to retrieve atmospheric temperature and trace gases profiles form multi/iper spectral radiances	View
1242	Evaluate the usability of a web map	View
1243	Evaluate the usability of a hard-copy map	View
1244	Assess the effective use of a web map by a set of users	View
1245	Design an iterative process for evaluating the usability of (geospatial) products	View
1246	Distinguish between usability, utility, and user needs in the context of geovisualizations	View
1247	Compare different evaluation methods for cartography and visualization products (e.g., qualitative versus quantitative, formative versus summative studies).	View
1248	Recognize spatial schemes like patterns and shapes	View
1249	Arrange previously observed objects in a place	View
1250	Represent an object or a scene from different viewpoints	View
1251	Contrast cloud and grid computing technologies	View
1252	Create conceptual, logical, and physical data models using automated software tools	View
1253	Identify gaming elements which may be part of geo-games	View
1254	Contrast gaming elements which are both part of traditional games and geo-games	View
1255	Design a game mechanics of a geo-game	View
1256	Illustrate with examples of maps or geovisualizations that could be improved by the addition of an audio layer	View
1257	Outline a multivariate visual display that incorporates sounds	View
1258	Explain why a layer with audio could be of interest in certain situations	View
1259	Illustrate the landscape of GIS and related libraries	View
1260	Assess which GIS APIs are more suitable for developing GIS applications	View
1261	List which data considerations should be taken into account when starting a GIS project	View
1262	Outline the importance of photographs or imagery either from satellites or at street level	View
1263	Differentiate uses for different types of imagery related to earth	View
1264	Differentiate between and application built with a Service Oriented Architecture (SOA) or a Resource Oriented Architecture (ROA)	View
1265	Outline the Reference Model of Open Distributed Processing framework	View
1266	Outline a database with its main functionalities	View
1267	Understand how map scale is used to provide the relationship of size of object on a map and its real-world size	View
1268	Understand that features have been omitted or generalized for clarity	View
1269	Apply spatial thinking to transform a graphical world into a real-world space	View
1300	Discuss various legal aspects of public and private sectors concerning owning, controlling, sharing/ disseminating open data.	View
1301	Differentiate "contracts for service" from "contracts of service"	View
1302	Identify the liability implications associated with contracts	View
1303	Discuss the potential legal problems associated with licensing geospatial information	View
1304	Understand the nature of tort law generally and nuisance law specifically	View
1305	Differentiate among contract liability, tort liability, and statutory liability	View
1306	Explain cases of liability claims associated with misuse of geospatial information, erroneous information, and loss of proprietary interests	View
1307	Propose strategies for managing liability risk, including disclaimers and data quality standards	View
1308	Explain the legal definition of the concepts "ownership" and "property rights"	View
1309	Explain organizations’ and governments’ incentives to treat geospatial information as property and arguments for and against the treatment of geospatial information as a commodity	View
1310	Outline the arguments for and against the notion of information as a public good	View
1311	Compare and contrast National, European policy regarding rights to geospatial data with similar policies in other countries	View
1312	Explain how geospatial information might be used in a taking of private property through a government's claim of its right of eminent domain	View
1313	Compare and contrast the consequences of different national policies about rights to geospatial data in terms of the real costs of spatial data, their coverage, accuracy, uncertainty, reliability, validity, and maintenance	View
1314	Discuss and define open data and impact on GIS&T	View
1315	Discuss various sources of open data (science, public and private sectors)	View
1316	Discuss of arguments for and against open data	View
1317	Discuss about open data impact on society and citizenship	View
1319	Discuss the role of the public and private sectors in producing and dissemination of geospatial information	View
1320	Discuss the legal framework related to competition and public-private sector relationships in the geospatial domain	View
1321	Discuss of opportunities for exchange of geospatial data between public and private sector to enable more efficient analysis	View
1338	Discuss and define the process of the Information value chain	View
1345	Discuss over the argument that the use of Geospatial geospatial Information privileges certain views of the world over others.	View
1346	Identify alternatives to the "algorithmic way of thinking" that characterizes use of geospatial Information.	View
1347	Discuss critiques of GIS as "deterministic" technology in relation to debates about the Quantitative quantitative revolution in the discipline of geography.	View
1348	Indicate the extent to which contemporary use of geospatial information supports diverse ways of understanding the world.	View
1349	Discuss the implications of interoperability on ontology	View
1350	Discuss over the various implications of surveillance technology	View
1352	Discuss about "mapping whose reality?" Pros and cons of geoinformation sharing in social media, i.e. big data, "digital shadow" etc.	View
1353	Discuss about open data and data sharing and public/private sector	View
1354	Discuss over the changing role of the private sector in the use of geospatial information	View
1356	Develop GI infrastructure with a the role in the private sector	View
1357	Research and develop geospatial information for the private sector	View
1359	Discuss over the paradigm shifts and current trends in GIS&T education and pedagogical approaches for GIS teaching and learning in detail	View
1363	Discuss how to approach the widening audience/participants for geospatial products and service, increasing geo-awareness and geo-enablement	View
1364	Discuss ways of working with crowdsourcing in education and research	View
1365	Discuss the role of public, private sector and citizens in facilitating geospatial information in environmental/sustainable issues.	View
1366	Discuss legal aspects of access to environmental data, global change/warming or sustainable development (regional, national, global) in conjunction to society.	View
1367	Define and understand citizenship, democracy, maturity, and negotiation related to geo information use and participation in society /community development (at local, regional, national level)	View
1368	Differentiate among universal/deliberative, pluralist/representative, and participatory models of citizen participation	View
1369	Compare the advantages and disadvantages of group participation and individual participation	View
1372	Illustrate an example of "local knowledge" that is unlikely to be represented in the geospatial data maintained routinely by government agencies	View
1373	Explain how community organizations represent the interests of citizens, politicians, and specialists	View
1376	Discuss the impact of geospatial information for the development of social media (Facebook, Twitter, Wikimapia, Flickr etc.) becoming increasingly location-based	View
1377	Discuss the role and value of "place" and "space" for geo media based social networking	View
1378	Differentiate between consumption, analysis, presumption and production of geoinformation within digital geo media	View
1379	Define and discuss volunteered geographic information	View
1380	Define and discuss enabling technologies: geotag, georeferencing, GPS and more	View
1381	Discuss positive and negative aspects of the term "humans as sensors"	View
1382	Apply domains and roles regarding geoinformation use in society: "spatial information systems manager", "spatial analyst", "spatial citizen"	View
1383	Define and discussing impact of Crowdsourcing on Geospatial Society	View
1384	Define Service Oriented Architecture (SOA) and identify main elements of it	View
1385	Discuss consensus based interoperability and its relation to geospatial data interchange. Define what a Web Service (WS) is and present characteristic scenarios. Data serving and Data Processing WSs	View
1386	Define the characteristics of web services and present some examples	View
1387	Define Web services transport over the Web	View
1388	Describe generally the hypertext transfer protocol and its main operations like POST and GET	View
1389	Identify design issues of SOAP web services; fine grained and coarse grained services, design patterns	View
1390	Define characteristics of REST Web services and Resource oriented Architecture (ROA)	View
1391	Differentiate between SOAP and REST Web services. - Identify design issues of REST Web services	View
1392	Discuss the issue whether a service is really "RESTful" or not	View
1393	Define Web Map Service (WMS). Describe GetCapabilities, GetMap, and GetFeatureInfo operations in detail. Practice its usage in a given use case	View
1394	Define Web Feature Service (WFS). Describe GetCapabilities, DescribeFeaturetype, and GetFeature, and GetFeatureInfo operations in detail. Practice its usage in a given use case	View
1395	Define Web Coverage Service (WCS). Describe GetCapabilities, GetCoverageInfo, and GetCoverage operations in detail. Practice its usage in a given use case	View
1396	Define Web Processing Service (WPS). Describe GetCapabilities, DescribeProcess, and Execute operations in detail. Practice its usage in a given use case	View
1397	Define Web Map Tile Service (WMTS). Describe GetCapabilities, GetTile, and GetFeatureInfo operations in detail. Practice its usage in a given use case	View
1398	Define and practice the usage, in a given use case, of StyledLayerDescriptor (SLD) and Symbology Encoding (SE). Practice their usage in a given use case	View
1399	Interpret generally the main components and functionality of "Web Application Frameworks" such as AngularJS, Ext.js, Django, Java Server Faces (JSF), and the like	View
1401	Illustrate basic radiation-matter interactions and related concepts of spectral reflectance, absorbance and transmittance as specific properties of the matter	View
1402	Illustrate basic features of spectral signatures of vegetation, water and bare soil	View
1403	Illustrate the importance of the choice of the satellite orbit for the design of a satellite mission devoted to specific applications	View
1404	Demonstrate the relationships among measured multi-spectral radiation and specific chemical (e.g. composition) and physical (e.g. temperature, pressure, etc.) properties of the observed matter.	View
1405	Illustrate the concept of spectral signatures of the matter	View
1406	Illustrate basic modern physics theory understanding their implications on the development of advanced sensors for EO	View
1407	Illustrate the interaction of e.m. radiation in the thermal infrared with the atmosphere understanding specifc characteristics of radiative transfer in this specific spectral region.	View
1408	Explain the concept of composition of spectral signatures and apply the "linear mixing" models in some simple case	View
1409	Illustrate and apply basic concepts of Atmospheric Physics to EO science and its applications	View
1410	Illustrate the concept of spectral emissivity and brigthness temperature and compute them in some simple real case	View
1411	Discuss the structure and chemical composition of the atmosphere	View
1412	Demonstrate basic knowledge of the interaction between the solar radiation and atmospheric constituents	View
1413	Discuss the basic principles of solar radiation.	View
1414	Demonstrate basic knowledge of the atmospheric absorption and scattering mechanisms.	View
1415	Relate to the aspects of radiation transfer through the atmosphere.	View
1416	Produce the processes of spectral calculations of radiometric quantities by the line by line radiative transfer models	View
1417	Estimate the meteorological and the cloud optical properties by LBRTM and validate against high accuracy spectral measurements	View
1418	Discuss the processes that describe the hydrologic cycle	View
1419	Illustrate the transferring of Energy within the Earth-Atmosphere System	View
1420	Illustrate e.m. radiation intercations with/within clouds.	View
1421	Illustrate main spectral signatures of clouds and apply them in paractical cloud-detection exercise	View
1422	Describe Electromagnetic Waves in terms of Photons	View
1423	Describe how Maxwell's equation explain EM waves' propagation	View
1424	Explain how Planck function and Wien law can help to characterize blackbodies' emission	View
1425	Explain in wich spectral regions the Rayleigh-Jeans and Wien's approximations of the Planck function better work	View
1426	Derive the Stefan-Boltzman Law from the Planck's one	View
1427	Explain the impact of Kirchoff's Law on the measurements of spectral emissivity of opaque bodies	View
1429	Describe the main spectral components of solar radiation at the top of atmosphere	View
1430	Describe the main branch of physycs relevant to the study of e.m. radiation and its interaction with the matter in the optical range	View
1431	Illustrate the nature of electromagnetic radiation	View
1432	Illustrate the importance of Earth's emitted radiation for EO from space	View
1433	Illustrate the main forms of radiation-matter interaction	View
1434	Illustrate the main energetic transictions that can be associated to molecular absorption of e.m. radiation	View
1435	Describe the main sources of spectral line broadening	View
1436	Illustrate how the Voigt's line profile is related to the Doppler and pressure line broadening contributes	View
1437	Illustrate the concept of grey body	View
1438	Describe how the complex part of the refractive index affects the propagation of e.m. radiation through the matter	View
1439	Describe the concept of attenuation length	View
1439	Describe the concept of attenuation length	View
1440	Discuss the change of attenuation length moving from visible to the microwave range and from sea water to solid land surfaces	View
1441	Describe the scattering properties of a lambertian surface	View
1442	Illustrate how the Rayleigh criterion can help to characterize surfaces' scattering properties in relation with their roughness and wavelength of the incident radiation	View
1443	Describe under which conditions the Beer-Bouguert-Lambert Law well approximates the general radiative transfer equation-	View
1444	Illustrate why we refer to the BRDF as an absolute definition of spectral reflectance	View
1445	Illustrate how it is possible to estimate the BRDF of a sample through measurements of BRF	View
1446	Describe what EM sensing means	View
1447	Define the radiometric spectral quantities radiance, irradiance, flux	View
1448	Define the radiometric spectral quantities brightness, emittance, luminosity	View
1449	Illustrate the decay of the emittance with the distance from the source	View
1450	Describe the spectral regions where Mineral and Rocks exhibit their main signatures	View
1451	Illustrate the main differences among passive and active remote sensing techniques	View
1452	Illustrate the scope Radiative Transfer theory	View
1453	Illustrate the general equation of radiative transfer.	View
1455	Illustrate the concept of Absorption Coefficient	View
1456	Illustrate the concept of Source Function	View
1457	Illustrate the concept of Cross Section of Extinction per Mass Unit	View
1458	Illustrate scope and conditions of validity of Schwarzshild equation.	View
1459	Illustrate of the concept of optical path	View
1460	Illustrate of the concept of optical thickness	View
1461	Describe under which conditions Mie scattering occurs in the Earth's Atmosphere	View
1462	Describe under which conditions Rayleigh Scattering in the Earth's Atmosphere occurs	View
1463	Illustrate how cloud presence complicate radiative transfer description in Earth's atmosphere	View
1464	Illustrate the concepts of Reflection, Refraction and Dispersion of the light	View
1465	Illustrate the concepts of Interference and Diffraction	View
1466	Describe how a Michelson interferometer make it possible to measure the emitted Earth radiation with hyperspectral resolution.	View
1467	Illustrate the role of the principle of constant speed of light within the special relativity theory	View
1468	Describe atmospheric transmittance in the optical spectral range	View
1469	Illustrate the main atmospherical spectral windows	View
1470	Illustrate the Greenhouse effect associate to CO2 emission	View
1471	Describe the concept of thermodynamic temperature	View
1472	Describe the main state functions of ideal gases	View
1473	Illustrate the First Law of Thermodynamic	View
1474	Illustrate the Second Law of Thermodynamic	View
1475	Describe the different payload capabilities of polar and geostationary platforms	View
1476	Illustrate the Helmotz’s equation	View
1477	Describe the impact of geometrical optics on optical sensors design	View
1478	Describe the impact of the theory of interference on the development of modern satellite hyperspectral sounders	View
1479	Describe the impact of theory of diffraction and grating spectrometers on the development of modern satellite hyperspectral sounders	View
1480	Describe the impact of Einstein’s theory of radiation on the design of modern devices for the measurements and/or production of coherent light	View
1481	Illustrate the importance of electric conduction in solids for the design and development of advanced EO sensors	View
1482	Illustrate possible noise sources related to photovoltaic and photoconductive detectors	View
1483	Describe the process of light scattering by atmospheric particulates	View
1484	Describe the process of water vapour cloud formation	View
1485	Describe the adiabatic decrease of tropospheric temperature with the heigth	View
1486	Describe the scope of thermodynamics	View
1487	Illustrate the concept of "kinetic temperature" in absence of thermodynamic equilibrium	View
1488	Illustrate the ideal gas law	View
1489	Ilustrate the state function of the condensed gas phase	View
1490	Describe the fundamental thermodynamic processes (isothermal, adiabatic, isochoric, isobaric)	View
1491	Illustrate the role of Eulerian and Lagrangian models in budget equations definition	View
1492	Describe the scope of irreversible thermodynamics	View
1493	Describe under what conditions adiabatic processes of homogeneous system occur	View
1494	Illustrate the utility of thermodynamic diagrams for the study of local atmospheric properties	View
1495	Describe the relevance of mechanics laws in the framework of EO satellite mission design and planning	View
1496	Illustrate the factors limiting lifetime of satellites on their originally planned orbits	View
1497	Describe the concept of spectral emissivity	View
1499	Explain why passive EO sensors with the highest spectral or spatial resolution operate in the VIS/NIR spectral region	View
1500	Explain and outline the advantages of radar sensors	View
1501	Explain how radar images are used for specific applications	View
1502	Explain differences between optical and radar remote sensing	View
1503	Explain what microwave remote sensing is	View
1504	Explain what soil permittivity is	View
1505	Explain how the soil permittivity influences radar signal	View
1506	Explain what properties of microwave electromagnetic spectrum are recorded	View
1507	Explain how the microwave signal is detected	View
1508	Explain what active-passive microwave imaging is	View
1509	Explain the principles of synthetic aperture radar (SAR) interferometry	View
1510	Explain principles of permanent/persistent scatterer interferometry	View
1511	State application examples of PSI methods	View
1512	Apply PSI method	View
1513	Explain differences between DInSAR and PSI	View
1514	Explain what the ground range and azimuth resolution are	View
1515	Calculate ground rage resolution	View
1516	Explain and discuss elements of Synthetic Aperture Radar (SAR) geometric configuration	View
1517	Explain principles of passive microwave imaging	View
1518	Explain why spatial resolution of passive radar system is much lower than that of active systems	View
1519	State and explain Synthetic Aperture Radar (SAR) geometric distortions	View
1520	Explain and discuss what terrain reflectivity is and how it influences radar signal	View
1521	Explain the fundamentals of Differential SAR Interferometry	View
1522	Discuss advantages of SAR techniques over traditional measuring techniques	View
1523	Discuss limitations of interferometric measurement	View
1524	State the microwave portion of the electromagnetic spectrum	View
1525	State the typical used radar bands and their application	View
1526	Discuss types and classes of remote sensing sensors	View
1527	Select the type of remote sensing sensor appropriate for your application	View
1528	Explain and discuss types of sensing mechanisms	View
1529	Discuss advantages and disadvantages of passive and active sensors	View
1530	State types of polarisations used in remote sensing	View
1531	Discuss the use of polarization for different application domains	View
1532	Explain principles of imaging radar	View
1533	Discuss the application possibilities of imaging radar	View
1534	Discuss orientational polarisation of media	View
1535	Discuss the polarimetry technique	View
1536	Explain and discuss the LiDAR technology	View
1537	State and explain different SAR acquisition modes	View
1538	Discuss main characteristics of digital imagery	View
1539	Explain what the picture element is	View
1540	Explain what the digital number is	View
1541	Distinguish and explain the different types of properties of digital imagery	View
1542	Explain and discuss what the spectral resolution is	View
1543	Explain and discuss what the spatial resolution is	View
1544	Explain and discuss what the radiometric resolution is	View
1545	Explain and discuss what the temporal resolution is	View
1546	Explain and discuss what the main processing levels of remote sensing data are	View
1547	Discuss the development of remote sensing sensors	View
1548	Discuss different types of satellite orbits	View
1549	Discuss the main types of remote sensing sensors	View
1550	Discuss the main types of remote sensing platforms	View
1551	Discuss the main types of remote sensing data	View
1552	Create a project plan for a map, from planning to finalisation	View
1553	List the main variables to take into account during the planning phase of a map	View
1554	Plan the creation of a map according to a given audience	View
1555	Understand how the representation of geographic data facilitates visual communication	View
1556	Select the most suitable graphic representation for a targeted audience	View
1557	Select the most suitable graphic representation for a given set of data	View
1558	Distinguish between different graphic representation techniques	View
1559	Design an interactive web map	View
1560	Outline a map layout taking into account design principles	View
1561	Understand how graphic representations can be interpreted distinctively by culturally different audiences	View
1562	Assess the effective understanding of a map by a set of users	View
1563	Create different visual hierarchies to produce maps with different purposes	View
1564	Identify examples of static, animated, and interactive web maps	View
1565	Distinguish between animated and interactive maps	View
1566	Apply appropriate terrain representation based on their relative pros and cons	View
1567	Design a stylized terrain map from a digital elevation model (DEM)	View
1568	Use appropriate interpolation techniques to derive DEMs from point data	View
1569	Discuss and compare different types of processing levels of SAR data	View
1570	Select the appropriate SAR data type for the application	View
1571	State different types of processing levels of SAR data	View
1572	Discuss and compare different types of processing levels of optical data	View
1573	Select the appropriate optical data type for the application	View
1574	Explain the laser scanner technology	View
1575	Discuss different types of laser scanners	View
1576	Explain what the phase in remote sensing means and in what units is expressed	View
1577	Discuss how to use phase information in remote sensing	View
1578	Explain what the mathematical description of the phase is	View
1579	Explain and apply phase unwrapping	View
1580	Explain what the attenuation length and penetration depth are	View
1581	Compare and discuss attenuation length and penetration depth of the optical and radar signal	View
1582	Explain and discuss surface roughness in microwave remote sensing	View
1583	Recognize different types of surface roughness on a radar image	View
1584	Discuss what surface height variation (or RMS height) is	View
1585	Discuss what horizontal roughness component (correlation legth) is	View
1586	Explain surface correlation function	View
1587	Model surface roughness slope	View
1588	Discuss scale of roughness of microwaves	View
1589	Explain scattering matrix	View
1590	Construct scattering matrix	View
1591	Explain covariance and coherence matrix	View
1592	Explain Stokes vector	View
1593	Apply covariance and coherence matrix	View
1594	Discuss polarimetric decomporition techniques	View
1595	Apply polarimetric decomporition techniques	View
1596	Explain polarimetric coherences	View
1597	Explain polarisation ellipse	View
1598	Apply Jones vector formalism	View
1599	Explain the concept of polarisation synthesis	View
1600	Explain one biophysical parameter and the EO technologies to estimate it for a specific region of interest	View
1601	Explain how a DSM differs from a DTM	View
1602	Explain one of the EO methods that allow DEM generation	View
1603	Explain how the DEM generation with SfM works and discuss its differences to the traditional method of DEM extraction with stereographic photogrammetry	View
1604	Apply k-Means clustering to an image to extract spectrally homogeneous clusters	View
1605	Compare results of the Laplacian of Gaussian filter to the original input image	View
1699	Describe the concept of Kinetic Temperature	View
1700	Understand the diverse set of EO technologies that are capable of mapping different landslide aspects	View
1701	Explain the capabilities and limitations of a particular EO technology for mapping landslides	View
1702	Compare one optical EO method with a SAR method for landslide mapping and explain their differences	View
1703	Explain why the use of multiple EO sensors for mapping landslides associated with one triggering event increases the completeness of a landslide inventory	View
1704	Explain the quality criteria where EO technologies differ from each other in their capabilities to detect, monitor and forecast landslides	View
1705	Design and test an EO-based workflow for landslide mapping	View
1706	Explain the application of EO information for monitoring urban sprawl	View
1707	Explain how the CORINE Land Cover product quality depends on its source EO data and how this affects its usage for regional planning.	View
1708	Choose a viable strategy for operations in the field of managed living ressources	View
1709	Apply the output of EO/GI tools to decisions in everyday operations	View
1710	Choose a viable strategy for farming operations	View
1711	Understand the health of the crop, extent of infestation or stress damage, or potential yield and soil conditions	View
1712	Choose a viable strategy for fishing operations	View
1713	Understand the health of the fishing grounds	View
1714	Choose a viable strategy for forest operations	View
1715	Understand the health of the forests	View
1716	Develop strategies and policies for energy and mineral resources	View
1717	Plan and design project implementations in the field of energy and mineral resources	View
1718	Analyse and understand environmental impact / consequences	View
1719	Plan and design alternative energy project implementations	View
1720	Plan and design oil & gas project implementations	View
1721	Plan and design mineral & mining project implementations	View
1722	Use EO/GI information to plan and design projects, monitor and assess the environment, support decision-making processes, and to tackle environmental challenges	View
1723	Monitor changes in infrastructure	View
1724	Assess environmental impact of human activities	View
1725	Monitor building development	View
1726	Detect land movement, subsidence, heave	View
1727	Monitor pollution in rivers and lakes	View
1728	Assess changes in the carbon balance	View
1729	Monitor land pollution	View
1730	Assess changes to urban and rural areas	View
1731	Assess and monitor water quality	View
1732	Assess ground water and run-off	View
1733	Map line of sight visibility (terrain height, land cover)	View
1734	Monitor transportation routes	View
1735	Monitor shipping routes	View
1736	Interpret land cover change detection	View
1737	Monitor and assess natural hazards	View
1738	Assess crop damage due to storms	View
1739	Assess damage from earthquakes, detect and monitor wildfires	View
1740	Map and assess flooding	View
1741	Assess and forecast landslides	View
1742	Interpret location based services (LBS)	View
1743	Manage the use of land	View
1744	Demonstrate impacts of land use change	View
1745	Identify high risk areas produced naturally or by humans	View
1746	Identify border incursions or maritime movements	View
1747	Develop monitoring to evaluate and deliver policy goals	View
1748	Assess ecosystems	View
1749	Identify rapid response to major environmental risk events	View
1750	Identify rapid response to events associated with health security & care	View
1751	Evaluate citizen-driven observations	View
1752	Forecast and monitor ocean winds and waves	View
1755	Evaluate the impact of the climate change	View
1756	Identify impact of a flood	View
1757	Assess areas threatened by wildfires	View
1758	Identify geotectonic shifts	View
1759	Identify geological features	View
1760	Compare glacier extents using EO data	View
1761	Calculate the water depth in coastal areas	View
1762	Analyse the strength of a hurricane	View
1763	Identify wake trailing to detect ships using EO data	View
1764	Identify sea-ice or icebergs using EO data	View
1765	Analyse and classify different land covers	View
1766	Use NDVI to estimate the vegetation cover	View
1767	Combine different bands to calculate NDVI	View
1768	Detect and monitor oil slicks	View
1769	Create new EO products out of raw data or other products	View
1770	Apply methods that assign labels to objects or locations in a field	View
1771	Apply a cloud mask to optical EO data	View
1772	Apply a semi-automated search to detect man-made objects like buildings or ships	View
1773	Develop an event map based on a time-series analysis	View
1774	Interpret information from EO products or EO time series	View
1775	Understand how the tracking of moving objects is implemented	View
1776	Interpret the output of an point cloud measurement	View
1777	Analyse the ice shield loss due to melting	View
1778	Analyse vector fields to determine wind directions	View
1779	Determine object movement by comparing subsequent images	View
1780	Relate EO measurements with detected features	View
1781	Produce forecasts for flood risk areas	View
1782	Identify construction sites	View
1783	Use 3D textured models to present study area	View
1784	Decide on urban planning measures on the basis of a semantic 3D model	View
1785	Illustrate the information of EO data	View
1786	Interpret the content of EO data	View
1787	Understand the technology behind LiDAR as an active sensor and what makes it different from the other existing Remote Sensing approaches	View
1788	Develop thorough understanding of the complex process from collecting the LiDAR data to generation of the final modeled outputs	View
1789	Enable citizen skills spatially	View
1790	Demonstrate multidisciplinarity, combining GISciences, Social Sciences, Smart Cities, Computational Sciences and Social Media	View
1791	Develop sense of space	View
1800	Interpret generally the functionality offered by "portal frameworks" land Geoportals like Geonetwork, Opengeoportal, Esri geoportal server, Degree portal, Liferay, Jboss portal	View
1801	Identify differences, advantages and disadvantages of web application framework based and portal framework based web applications from the geospatial data perspective	View
1802	Indicate generally how "NSDI-requiring-scenarios"would be handled by web application framework based applications	View
1803	Explain how JSON (GeoJSON)`s "schema-less"structure may be transformed into an application schema	View
1804	Identify the need for and main issues in spatial data interchange	View
1805	Identify the main components of OGC Filter encoding and compare it to SQL	View
1806	Practically apply getting data from a WFS and integrate it into a client application	View
1807	Practically apply getting data from a WCS and integrate it into a client application	View
1808	Demonstrate the usage of popular ETL tools in an NSDI scenario	View
1809	Define web services composition (WSC) concept and identify main issues	View
1810	Define Web API composition (WAPIC) concept for RESTful WSs and identify main issues	View
1811	Apply a WSC for a certain use case in Taverna workbench using OGC WPS services	View
1812	Define OGC Simple Features Access Schema. Well-Known Text (WKT) and Well-Known Binary (WKB) representations of Geometry	View
1813	interpret GML data model and GML definition of geometry. GML application schemas and GML documents	View
1814	Define spatial extensions that GeoSPARQL brings over SPARQL. Identify the difference between qualitative spatial reasoning and quantitative spatial computations	View
1815	Define GeoJSON definition of Geospatial objects and describe the structure of a GeoJSON document and identify advantages and disadvantages of representing the same geospatial data in GML and in GeoJSON	View
1816	Compare different Geospatial object and geometry definitions included under this topic	View
1817	Define Resource Description Framework (RDF), its RDF graphs, RDF Schema (RDF-S)and a data set in RDF	View
1818	Explain Web Ontology Language (OWL) and how to define a data set in OWL DL	View
1819	Identify virtues of defining a given data set in both RDF and OWL, and compare semantic richness of both definitions	View
1820	Define Semantic Web and identify the role of the languages included under this topic for Semantic Web	View
1821	Identify the relation between OWL-S and WSDL and give an overview of Semantic Web service definition in OWL-S	View
1822	Define the components of a Web Services Description Language (WSDL) document	View
1823	Use Web services description for RESTful web services, Web Application Description Language (WADL) and its use	View
1824	Define what an ontology is. Identify differences among ontologies, Thesauri, and taxonomies	View
1825	Differentiate between upper, domain, and application level ontologies	View
1826	Identify issues in the development of geospatial ontologies. Criticise the role of ontology development methodologies and ontology evaluation in the development of ontologies	View
1827	Define and exemplify the reuse of ontologies - Define and identify the role of ontology patterns	View
1828	Explain how analytical methods are used to derive analytical results from geospatial data	View
1829	Differentiate among the concepts of scale (as in map scale), support, scope, and resolution	View
1830	Determine the mathematical relationships among scale, scope, and resolution	View
1831	Defend or refute the statement "GIS data are scaleless"	View
1832	Discuss the implications of tradeoff between data detail and data volume	View
1833	Select a level of data detail and accuracy appropriate for a particular application (e.g., viewshed analysis, continental land cover change)	View
1834	Understand the benefits of publishing and using open data	View
1835	Explain what open data and the main principles of open data are	View
1836	Publish a dataset as open data	View
1837	Determine if a dataset can be considered as open data	View
1838	Compare and explain different models for funding an SDI	View
1839	Describe and explain the funding model of an existing SDI	View
1840	Explain the impact of open data policies on SDI funding models	View
1841	Explain why the process "dissolve and merge" often follows vector overlay operations	View
1842	Explain what is meant by the term "planar enforcement"	View
1843	Outline the possible sources of error in overlay operations	View
1844	Exemplify applications in which overlay is useful, such as site suitability analysis	View
1845	Compare and contrast the concept of overlay as it is implemented in raster and vector domains	View
1846	Demonstrate how the geometric operations of intersection and overlay can be implemented in GIS	View
1847	Demonstrate why the georegistration of datasets is critical to the success of any map overlay operation	View
1848	Formalize the operation called map overlay using Boolean logic	View
1849	Explain in which cases digitizing is a relevant data production technique	View
1850	Develop a strategy to improve the performance of an SDI initiative	View
1851	Explain what SDI governance is and why it is important in the development and implementation of SDIs	View
1852	Discuss the governance structure in place of a particular country	View
1853	Design an effective governance structure for a national SDI	View
1854	Explain the main objectives of an SDI	View
1855	Identify and discuss the different components of an SDI	View
1856	Use the models of ‘SDI generations’ and ‘SDI components’ to describe the main elements of an existing SDI initiative	View
1857	Explain the relevant legal and organizational issues around development and implementation of Spatial Data Infrastructures (SDI)	View
1858	Explain the relevant technological issues around development and implementation of Spatial Data Infrastructures (SDI)	View
1859	Explain the different steps in the geo-information value chain	View
1860	Apply the geo-information value chain approach to an existing geo-information process	View
1861	Identify and explain the different actors and their roles in the geo-information value chain	View
1862	Explain what a business model is and how is used	View
1863	Apply a business model framework to identify the different components of a business model in the GI domain	View
1864	Compare and explain the main business models in the GI domain	View
1866	Explain semantic annotation of data and services	View
1867	Solve issues in determining what ontologies to use for semantic annotation	View
1868	Identify issues in developing new ontologies for geospatial data	View
1869	Define Mapping between legacy definition and the semantic definition of publish	View
1870	Indicate an architecture and tools for organizing semantically annotated data	View
1871	Illustrate stages of publishing a relational database as Linked Data	View
1872	Identify issues in finding proper ontologies to annotate the data	View
1873	Identify issues in determining the relationships to be represented when publishing Linked Data	View
1874	Relate with manual and automated methods linking data	View
1875	Apply publishing a relational database as Linked Data	View
1876	Identify main issues in "keyword-based" discovery of data and services	View
1877	Demonstrate how to discover over a catalogue service; and the discovery procedure in OGC CS-W	View
1878	Perform discovery over some popular SDI (NSDI) portals like INSPIRE and GOS geoportals	View
1879	Use "Full-text-based" discovery; open source and commercial search engines, its use in GI related applications	View
1880	Semantic Discovery and its main components. Identify the areas of its use for GI related applications	View
1881	Identify the main concepts of reasoning and architectural components of Reasoners	View
1882	Identify main issues in Semantic discovery	View
1883	Indicate some examples of semantic discovery; Semantic search engines, highlighting projects and practice concerning GI related applications in the area	View
1884	Describe Querying Linked Data; SPARQL and GeoSPARQL	View
1885	Describe Linked Data Browsers; Define Faceted browsers and identify what problems of linked data discovery they aim to solve	View
1886	Use Natural language based discovery over linked data	View
1887	Compare Linked geospatial data to SDI approaches	View
1888	Identify whether Full-automated WSC has still a value in it concerning both where we stand today on the road to 'Semantic Web' and unresolved problems in the area, which are the problems of Artificial Intelligence indeed	View
1889	Indicate main elements of HTML5	View
1890	Identify building blocks of Javascript programming language	View
1891	Understand the importance of Cascading Style Sheets (CSS) to separate content from style in HMTL documents	View
1892	Outline the use Scalable Vector Graphics (SVG) for client-side graphic processing	View
1893	Examine the Document Object Model (DOM) in HTML documents	View
1894	Identify main elements and functionality Google maps, describe some of its most popular API operations and how they are employed	View
1895	Identify main components and functionality of Openlayers library, describe its main functions and how they are employed	View
1896	Identify main components and functionality of Leaflet library, describe its main functions and how they are employed	View
1897	Identify main elements and functionality Mapbox, describe some of its most popular API operations and how they are employed	View
1898	Indicate an overview of OpenStreetMap and define its general functionality, comment its usage by Web APIs	View
1899	Provide examples of cases in which crouwdsourcing is the most effective data collection method	View
1900	Define metadata and identify metadata standards like ISO 19115 and 19119 describe their metadata schema generally	View
1901	Differentiate between a metadata standard and a metadata profile	View
1902	Identify the aspects of selecting keywords which would characterize the data properly	View
1903	Identify the issues in mapping between different metadata standards. Also identify the roles of thesauri and crosswalks	View
1905	Identify main components of manual metadata creation software tools	View
1906	Demonstrate harvesting and crawling mechanisms for automated metadata collection	View
1907	Apply harvesting using GeoNetwork Open Source tool	View
1908	Demonstrate publishing in some popular SDI (NSDI) portals like INSPIRE and GOS geoportals	View
1909	Examine Metadata schema and vocabularies used for open data publishing	View
1910	Use open data APIs that enable the usage of Open data; identify design aspects and usage scenarios	View
1911	Describe the basic forms of generalization used in applications in addition to cartography (e.g., selection, simplification)	View
1912	Discuss the possible effects on topological integrity of generalizing data sets	View
1913	Explain why areal generalization is more difficult than line simplification	View
1914	Explain the logic of the Douglas-Peucker line simplification algorithm	View
1915	Explain the pitfalls of using data generalized for small scale display in a large scale application	View
1916	Design an experiment that allows one to evaluate the effect of traditional approaches of cartographic generalization on the quality of digital data sets created from analog originals	View
1917	Evaluate various line simplification algorithms by their usefulness in different applications	View
1918	Apply open data publishing using CKAN Open source tool	View
1919	Explain what is meant by "Odata" (Open data Protocol), an OASIS standard	View
1920	Identify the technical aspects that open data paradigm would affect concerning Spatial Data Infrastructures including NSDIs	View
1921	Identify a variety of likely measurement level transformations (e.g., the classification of ratio data yields ordinal data)	View
1922	Discuss the relationship of attribute measurement levels to database query operations	View
1923	Describe the pitfalls, in terms of information loss and analytical options, of transforming attribute measurement levels	View
1924	Reclassify (group) a nominal attribute domain to fewer, broader classes	View
1925	Reclassify a raster before converting it into a vector file	View
1931	Explain the main differences between image orthorectification, geo-referencing, and co-registration	View
1932	Describe the advantages and disadvantages of analytical and physical-based models for orthorectification	View
1933	Understand the underlying assumptions for spatial stochastics process	View
1934	Explain the need for the stationarity assumption	View
1935	Explain the different forms of kriging	View
1936	Ability to define elements and requirements of the spatial weight matrix	View
1937	Identify the different methods for constructing spatial weigh matrix	View
1938	Compare the different types of spatial weight matrices	View
1939	Understand the assumption under which spatial autocorrelation may occur	View
1940	Identify different measures of spatial autocorrelation	View
1941	Understand the assumption under which spatial autocorrelation may occur	View
1942	Explain the difference between local and global measures of spatial autocorrelation	View
1943	Identify different measures of spatial autocorrelation	View
1944	Explain the advantage of Bayesian methods over frequentist methods	View
1945	Understand different estimation methods for Bayesian models	View
1946	Convert vector data to raster format and back using the GIS software	View
1947	Compare the result of conversion vector/raster or raster/vector and examine the impact of conversion on the quality of the dataset	View
1948	Understand and examine the common methods for raster resampling	View
1949	Explain the impact of the applied resampling method on the quality of the output dataset	View
1950	Convert a dataset from the native format of one GIS product to another	View
1951	Describe the workflow for converting data from one data model to another	View
1952	Identify the conceptual and practical difficulties associated with data model and format conversion	View
1953	Understand various formats of storing raster and vector data	View
1954	Illustrate the main use of spatial clustering in earth observation	View
1955	Identify a clustering method which does not require the number of clusters as input	View
1956	Explain the advantage of the cokriging method in earth observation studies	View
1957	Explain the advantage of the cokriging method in earth observation studies	View
1958	Explain how reclassification can be used for data simplification and measurement scale change	View
1959	Explain how buffers can be used in GI analysis	View
1960	Apply basic query operations on a dataset	View
1961	Compare models and software tools that allow for optimization	View
1962	Apply analytical methods to solve spatial problems	View
1963	Assess which geometric operations are suitable for raster and vector data sets.	View
1965	Compare the basic analytical operations of different GISs.	View
1966	Explain the difference between Generalized multidimensional scaling and Classical multidimensional scaling.	View
1967	Compare methods of spatial statistical analysis for the testing of hypotheses.	View
1968	Classify common models for spatial regression analysis.	View
1969	Explain in which cases representation transformation is needed.	View
1970	Discuss implications of data loss in the case of generalisation of spatial data.	View
1971	Explain how graph theory plays a role in network analysis.	View
1972	Describe how conceptual foundations of GI Science have become implemented in GISs.	View
1973	Compare relationships between entities, between attributes and between locations.	View
1974	Discuss the importance of space, time, properties, and categories as fundamentals in the conceptualization and representation of spatial entities.	View
1975	Explain Tobler's first law of geography.	View
1976	Explain how spatial analysis is dependent explicitly on the borders of study fields.	View
1977	Distinguish between metaphysics and epistemology.	View
1978	Distinguish between continuants and occurrents in relation with spatial phenomena.	View
1979	Relate epistemology to spatial knowledge.	View
1980	Recommend for what applications we should use a field or an object-base approach.	View
1981	Illustrate how fields, such as geography, cartography, computer and information science, engineering, mathematics, philosophy, cognitive science, and linguistics have their influence on GI science.	View
1982	Explain which technologies have an impact on GI science.	View
1983	Explain from which scientific fields GIS&T borrows ideas.	View
1984	Explain how linguistics play a role in GI science.	View
1985	Explain the role of metaphors and image schemata in our understanding of geographic phenomena and geographic tasks.	View
1986	Differentiate between formal and natural language in GI science applications.	View
1987	Discuss the difference between vagueness and uncertainty.	View
1988	Classify the main knowledge domains of GI Science and Earth observation.	View
1989	Discuss the synergy between processes in geo-information systems and earth observation systems.	View
1990	Decide which generalisation technique (aggregation, selection, etc.) is best for a specific situation of reducing map scale.	View
1991	Distinguish between transformation methods for raster and vector representations.	View
1992	Explain how Representation transformations are related to spatial data quality.	View
2002	Apply InSAR technique	View
2003	Apply DInSAR method	View
2004	Explain along-track interferometry technique	View
2005	Explain across-track interferometry technique	View
2007	Explain SBAS technique	View
2008	Apply SBAS technique	View
2009	Explain and discuss the complex elements of a radar signal	View
2010	Explain what the phasor represents	View
2011	Explain what the azimuth direction is	View
2012	Explain and discuss what the range direction is	View
2013	Explain what an incident angle is	View
2014	Discuss how the angle of SAR signal incidence affects SAR acquisition	View
2015	Explain and discuss what the foreshortening is	View
2016	Produce a geometrically corrected SAR image	View
2017	Explain and discuss what the layover is	View
2018	Explain and discuss what the shadow in SAR acquisition means	View
2019	Explain and discuss the SAR acquisition mode staring spotlight	View
2020	Explain and discuss the SAR acquisition mode spotlight	View
2021	Explain what a data cube is	View
2022	Explain and discuss the concept of Big Data in the field of Earth Observation	View
2023	State examples of image description files used in Earth Observation	View
2024	Explain and discuss the development of remote sensing data carriers	View
2025	Discuss and compare different types of interactions of microwaves with matter	View
2026	Explain the relationship between the material constant and the interaction of microwaves with the object	View
2027	Plan an Earth observation mission objectives and priorities in response to user expectations, taking into account type of application, type of sensor, expected accuracy	View
2028	Explain and discuss what antenna gain is and why it is described as the key performance of a radar antenna	View
2029	Explain what the main representations of radar antenna pattern are	View
2030	Calculate the size of the syntheric aperture of a radar system taking into account the platform and sensor specifications	View
2031	Check incidance angle of a SAR system in data metadata	View
2032	Calculate the radar antenna footprint taking into account the orbit of the radar system and bandwidth	View
2033	Check and discuss an local incidence angle of a SAR system in data metadata	View
2034	Explain the principle of the radargrammetric equation	View
2035	Select and apply the radargrammetric equation	View
2037	Explain the principles of the SAR tomography	View
2038	Apply SAR tomography	View
2039	Explain the geophysical method using ground penetrating radar	View
2040	Explain how the radar speckle is formed	View
2041	Explain principles of the real aperture radar	View
2042	Explain principles of the coherent and active systems	View
2043	Discuss radar antennas	View
2044	Plan the calibration of the radar antenna	View
2045	Explain plant permitivity and its effect on radar data acquisition	View
2046	Explain dielectric properties of objects and their effect on radar data acquisition	View
2047	Calculate radar beta nought	View
2048	Calculate radar gamma nought	View
2049	Calculate radar sigma nought	View
2050	Explain what the radar equation is	View
2051	Explain what the radar cross-section is	View
2052	Discuss the radiometric anomalies of radar data	View
2053	Discuss electromagnetic interactions and scattering mechanisms	View
2054	Explain what it is and causes diffraction	View
2055	Explain what the wave-particle dualism is	View
2056	Explain why the Doppler effect is important in radar remote sensing	View
2057	Explain what coherent means in radar remote sensing	View
2058	Explain how fourier transformation is used to generate radar image	View
2059	Explain why a radar signal needs a complex waveform description	View
2060	Explain what can be measured with a seismic sensor or seismic sensors	View
2061	Explain what can be measured with a sonic sensor	View
2062	Explain what can bea measeard with a sonar sensor	View
2063	Explain what the interferometric wide swath mode is	View
2064	Apply SAR data acquired in interferometric wide swath mode	View
2065	Discuss the main applications using the extra wide swath mode	View
2066	Select an optical spectrometer suitable for your application taking into account the acquired wavelength	View
2067	Discuss how line detectors array sensors work	View
2068	Explain the principle of across track scanning	View
2069	Discuss the use of area array sensors in remote sensing	View
2070	Discuss the use of digital frame cameras in remote sensing	View
2071	Discuss what the main characteristics of radiometers are	View
2072	Discuss the differences between imaging and non-imaging sensors	View
2073	Discuss the main properties of thermal radiometers	View
2074	Discuss the main properties of passive microwave radiometers	View
2075	Discuss the main properties of hyperspectral radiometers	View
2076	Discuss the use of data obtained by spectroradiometer	View
2077	Discuss what types of electromagnetic waves the laser profiler uses	View
2078	Discuss the applications for which Wind Doppler LiDAR is used	View
2079	Discuss the applications for which Differential Absorption LiDAR can be used	View
2080	Discuss what information is acquired by the laser altimeters	View
2081	Explain the principles of operation of a ranging camera	View
2082	Discuss an example of using a radar altimeter	View
2083	Explain what the radar scatterometer measures	View
2084	Explain the principles of operation of the structured-light-projection camera	View
2085	Explain the principles of operation of the speckle-pattern based sensor	View
2086	Explain the principles of operation of the multi-temporal pattern based sensor	View
2087	Explain the principles of operation of the multi-spectral pattern based sensor	View
2088	Select the type of remote sensing platform for your specific application	View
2089	Discuss the history of the development of remote sensing platforms	View
2090	Discuss the ways of using data acquired by UAS in remote sensing	View
2091	Apply data acquired by UAS	View
2092	Discuss examples of the objectives of Earth observation missions	View
2093	Compare and discuss different SAR acquisition modes	View
2094	Explain what swath represents	View
2095	Discuss examples of ground-based platforms and their use	View
2096	Explain the principles of terrestrial laser scanning operation and discuss its applications	View
2097	Plan in-situ measurements using a field spectroradiometer	View
2098	Discuss the purposes of obtaining remote sensing data	View
2099	Discuss how remote sensing data is organized and stored	View
2100	Identify the different barriers for the integration of datasets	View
2101	select the development elements best suited for your application	View
2102	compare different development components and their advantages and disadvantages	View
2103	identify the web services needed for a particular use case	View
2104	perform the connection to existing web services to use the resources exposed by the service	View
2105	select the web services best fit to expose your own resources	View
2106	understand how different web services complement each other	View
2120	Identify the main organizational challenges in implementing and use GIS&T	View
2121	Identify the key organizational components of a GIS&T implementation	View
2122	Prepare a strategy on setting up the organizational components of a GIS&T implementation	View
2123	Prepare a GIS Management Strategy	View
2124	Evaluate and revise an existing GIS management strategy	View
2125	Explain the different components of a GIS management strategy	View
2126	Understand and explain the main legal issues related to the production, use and sharing of geospatial data and information	View
2127	Recognize the relevant legal issues in a particular case of geospatial data collection, use and/of sharing	View
2128	Suggest and prepare solutions for addressing particular legal issues related to the production, use and sharing of geospatial data	View
2129	Explain the relevance and added value of geospatial information in particular use cases	View
2130	Explain how geographic information is valuable to different sectors	View
2131	Provide examples of the use of geospatial information in different sectors	View
2132	Explain the difference between data privacy and data security	View
2133	Explain the main challenges in dealing with data privacy and data security issues	View
2134	Propose and design solutions for dealing with particular data privacy and data security issues	View
2135	State the names of the most important regions of the electromagnetic spectrum	View
2136	State the names of the regions of the electromagnetic spectrum most important for Earth's remote sensing	View
2137	State the basic physical principles for EO systems design and data analysis	View
2138	Illustrate the concepts of solar constant and daily solar insolation	View
2139	Discuss in which way annual solar insolation and average cloud coverage parameters affect the choice of a solar power plant location	View
2140	Discuss in which way modeled daily solar insolation and cloud coverage forecast could affect solar power plant day-by-day management	View
2200	Explain why the legal framework on geospatial data sharing can be considered as diverse and complex	View
2201	Explain why the legal framework on geospatial data sharing consists of two main types of legislation from a data perspective	View
2202	Give examples of more general types of legislation that are also applicable and relevant to geospatial data sharing	View
2203	Provide examples of different types of legal instruments that can be used for supporting geospatial data sharing	View
2204	Explain what framework agreements are and how they can be used for sharing geospatial data	View
2205	Explain what licenses are and how they can be used for sharing geospatial data	View
2206	Explain the difference between standard licenses and open licenses	View
2207	Explain the concept of geospatial citizenship	View
2209	Explain why it is important to take into consideration the 'digital divide' when dealing with the use of and access to geographic data and information	View
2210	Provide examples of different types of critiques on GI and GIS	View
2211	Explain the implications of Critical GIS for GIS education	View
2212	Explain the implications of Critical GIS for GIS practice	View
2213	Explain the relevant economic aspects related to the access to and use of geographic information	View
2214	Explain the relevance and importance of privacy issues in dealing with geospatial data	View
2215	Explain what relevant ethical aspects are related to the access to and use of geospatial information	View
2216	List and explain the different societal aspects that are important in dealing with geospatial information	View
2217	Design solutions to different types of barriers to geospatial data sharing	View
2218	Explain the benefits of geospatial data sharing as a data acquisition approach	View
2219	Explain the institutional framework of an existing SDI initiative	View
2220	Evaluate the institutional framework of an existing SDI initiative	View
2221	Explain how next-generation SDIs are different from current SDIs	View
2222	Explain the key components of next-generation SDIs	View
2223	Explain the importance of SDI policies	View
2224	Explain the different types of policies that are relevant to the development and implementation of SDIs	View
2225	Design effective teaching and learning methods for GIS&T education	View
2226	Evaluate the relevance and applicability of different teaching and learning methods for GIS&T education	View
2227	Design GIS&T curricula and courses	View
2228	Explain relevant GIS&T workforce aspects and their interrelationships from different perspectives (employee, employer, tutor, ...)	View
2229	Explain the particular characteristics of sub-national and local governments as actors in the GIS&T domain	View
2230	List and explain relevant organizational and institutional aspects related to GIS&T.	View
2231	Design and implement approaches and methods for collecting users feedback on GIS	View
2232	Design and implement approaches and methods for assessing the performance of GIS	View
2233	Define user roles for an existing or planned GIS	View
2234	Explain why the definition of user roles is an important element in the implementation of a GIS	View
2235	Design and implement an effective GIS coordination strategy	View
2236	Use the most effective change model depending on the nature and needs of the client's organization.	View
2237	List and describe the main categories of organizations in the GIS&T domain	View
2238	List and describe the most important producers and users of geospatial data at the European Commission	View
2239	Explain the particular characteristics of national government organizations in the GIS&T ecosystem	View
2240	Explain what data mashups are	View
2241	Create a new application by combining existing data from different sources	View
2242	Explain the different stages in the development of applications through web services composition	View
2244	Explain the main steps in the process of aligning data structures and ontologies	View
2245	Apply different tools for aligning ontologies	View
2246	Explain the differences between syntatic and semantic discovery of resources	View
2247	Implement and configure a catalogue service	View
2248	Explain the main differences between different types of resource publishing	View
2249	Explain the differences between traditional GIS and Web-GIS	View
2250	Develop Web-GIS solutions to replace each of the functions of a traditional GIS	View
2251	Explain what the Resource Description Framework (RDF) is and what it can be used for	View
2252	Explain the principles of 3D modelling	View
2253	Apply different 3D model mapping and modelling approaches	View
2254	Explain what CityGML is	View
2255	Explain how CityGML is related to GML	View
2256	Explain and apply GML data models	View
2257	Explain the differences between geospatial data and other types of data	View
2258	Determine the most appropriate data collection method for collecting particular data	View
2259	Prepare and implement an effective geospatial data transaction management approach	View
2260	Explain why metadata are important for assessing and ensuring the quality of geospatial data	View
2261	List and explain the key requirements for geolocating data to earth	View
2262	Model geospatial data	View
2263	Model complex aspects of geographic information, such as temporal change, uncertainty and three-dimensional phenomena	View
2264	Explain basic aspects of data modelling, storage and exploitation, such as relation models & databases, data structures, SQL, UML and other basics	View
2265	Determine the standards that are essential for geospatial data modelling	View
2266	Explain what tessellation data models are	View
2267	Understand vector data models	View
2268	Deal with time aspects in modelling data	View
2269	Deal with uncertainty aspects in modelling data	View
2271	Explain the differences between OGC and ISO standards	View
2272	Use standards such as ISO 19141 Schema for moving features, ISO 19142 Web Feature Service and ISO 19109 - Rules for application schema	View
2273	Transfer a conceptual model to a logical (database) model	View
2274	Model temporal aspects	View
2275	Explain which standards are essential for conceptual data modelling	View
2276	Explain and apply standards relevant for geometric modelling	View
2277	Explain the concept of continuous fields and the commonly used ways of representing geo-fields	View
2278	Explain what linear referencing is and how it is used	View
2279	Develop solutions to different kind of challenges of model interoperability	View
2280	Give and explain an example of an application models	View
2281	Define and describe an application schema	View
2282	Apply techniques for the definition of features / feature classes	View
2283	Explain what databases are	View
2284	Explain the key elements of the relational - database - model	View
2285	Design relational databases	View
2286	Provide examples of typical non-spatial and spatial queries	View
2287	Work with different data compression techniques	View
2288	Access and interpret SQL databases	View
2289	Explain and use UML diagrams	View
2290	Understand and use XML	View
2291	Explain the relations between GIS and databases	View
2292	Explain which elements determine the quality of geospatial data	View
2293	Explain how metadata, standards and data infrastructures are linked to each other	View
2294	Explain what map projections are	View
2295	Explain why the shape of the Earth is complex and complicated to measure	View
2296	Explain what horizontal and vertical datums precisely determine	View
2297	Explain why aerial imaging and photogrammetry are important for the geospatial domain and the geospatial industry	View
2298	Explain which types of geospatial data are collected through satellite remote sensing	View
2299	Explain the differences between satelitte remote sensing and shipboard remote sensing	View
2300	Explain the approach how image analysis follows the physical model of solar radiation interacting with the Earths surface and the atmosphere	View
2301	Explain how computer vision imitates the human visual system when interpreting EO images	View
2302	Identify different options where Artificial Intelligence can be integrated in the image processing and analysis workflow	View
2303	Understand how the entropy represents the the average level of information contained in an image pixel	View
2304	Discuss algorithms that use the detection of keypoints to identify objects in images	View
2305	Apply CNN approaches in EO applications	View
2306	Describe how deep learning works	View
2306	Compare different deep learning approaches in EO image classification	View
2307	Discuss the main drawback of edge-based segmentation in partitioning an image	View
2308	Explain how the histogram-based segmentation works	View
2309	Explain how the consideration of local variance can enhance image segmentation results	View
2310	Explain how local density gradients are employed in mean-shift segmentation	View
2311	Discuss the principles of regionalisation and their use in segmentation methods	View
2312	Discuss spatial autocorrelation and homogeneity of image objects	View
2313	Discuss how the choice of sampling strategy impacts the classification result	View
2313	Discuss how the choice of sampling strategy impacts the classification result	View
2314	Discuss how the choice of sampling strategy impacts the accuracy assesment for a classification result	View
2314	Discuss how the choice of sampling strategy impacts the accuracy assesment for a classification result	View
2315	Interpret the effect of a convolution from a given mask and contained weights	View
2316	Identify and discuss an example of a combined filtering process	View
2317	Explain the shape and weights for a horizontal edge detector	View
2318	Discuss the frequencies that a high-pass filter preserves and subdues	View
2319	Create a convolution filter that integrates the standard deviation of the entire scene in its weights	View
2320	Discuss how the size of the neighborhood impacts the smoothing effect of a low-pass filter	View
2321	Discuss the benefits of using a gauss filter instead of a mean filter for smoothing an image	View
2322	Discuss how hierarchical representation is exploited for object-based image analysis	View
2323	Explain how class modelling can make use of per-parcel analysis	View
2324	Apply distance to objects of a specific class as a feature for enhancing class assignment	View
2325	Explain how the geometry of an object relates to its membership to a specific class	View
2326	Explain the advantage of polyhedralization when adding new classes to an existing image classification system	View
2327	Create a scale space for an image by applying multiple iterations of low-pass filtering	View
2328	Explain how SIFT algorithms can be used for enhancing orthorectification	View
2329	Discuss cloud masks as early steps towards semantic enrichment for EO images	View
2330	Discuss why a query through time is easier realized with a data cube than by comparison of a time series stored in image files	View
2331	Analyse the uncertainty that is present in an EO product	View
2332	Explain how error propagates in the production workflow of an example EO product	View
2333	Choose a set of quality indicators for an EO product that are relevant for a specific application	View
2334	Select images for time series analysis where the cumulated cloud cover percentage in the study area is low enough for the analysis	View
2335	Explain the different phases of the remote sensing life cycle	View
2336	Explain the different limitations of human vision and computer vision that make scene-from-image reconstruction and understanding an ill-posed process	View
2337	Explain how a lack of knowledge about data quality limits the data value	View
2338	Discuss the available data quality standards for EO	View
2339	Determine all necessary steps to make EO-derived products of a resarch project accessible	View
2340	Create a protocol for quality assessment of an EO information product that conforms to EO4GEO guidelines	View
2341	Evaluate the conformity of an EO imagery product to ISO 19129	View
2342	Evaluate an EO product and its metadata on its reusability for a new application context	View
2343	Discuss different methods for assessing the quality of a specific EO product	View
2344	Explain the benefits of structuring images in a data cube	View
2345	Identify steps of processing on large image collections that benefit from storing them in array databases	View
2346	Create a data cube using the data model of the Open data cube initiative	View
2347	Use an image archive to retrive Earth observation data for an application	View
2348	Build semantic queries to retrieve selections of images from an EO image database	View
2349	Use a web portal to retrieve EO data	View
2350	Explain how online processing can enhance the functionality of a web viewer for EO data	View
2351	Create a web interface and related system architecture that enables image processing by using OGC interfaces	View
2352	Explain how the acquisition, storing, and processing of EO images and derived products is distributed over a chain of stakeholders	View
2353	Understand the challenge in matching sensory image data to a mental model of the world-scene	View
2354	Explain the components of a production system for automatic image classification	View
2355	Identify different methods that employ conditional probability for image classification	View
2356	Apply spatial aggregation for generalizing an image classification	View
2357	Apply gridding to derive images with coarser resolution	View
2358	Use filtering techniques to spatially aggregate an image classification	View
2359	Explain the difference between precision and bias	View
2360	Interpret ocean colour for deriving chlorophyll concentration in water	View
2361	Identify spectral bands necessary for interpreting ocean colour	View
2362	Identify adequate preprocessing for deriving ocean colour from EO data	View
2363	Apply radiative transfer modelling to retrieve inherent optical properties (IOP) from Ocean Colour reflectance values	View
2364	Understand the difference between Inherent Optical Properties (IOP) and Apparent Optical Properties (AOP) of water	View
2365	Select imagery from a satellite sensor with spectral bands suitable for mapping Ocean Colour	View
2366	Apply atmospheric correction to extract Ocean Colour from EO imagery	View
2367	Design a map of chlorophyll-a concentration according to the requirements of HAB management for aquaculture	View
2368	Understand the types of decision trees and their output	View
2369	Understand the advantages and shortcomings of decision trees	View
2370	Identify the most popular decision tree algorithms	View
2371	Apply decision trees to classify land cover in an EO image	View
2372	Explain how CNNs are structured to derive information from image data	View
2373	Identify programming languages (like Python, R, and C++) and the main open-source libraries (like OpenCV, PyTorch, TensorFlow, Google Colab, Github, Scikit-learn) that are common for deep learning	View
2374	Apply deep learning methods on EO data within online processing platforms like Google Earth Engine Cloud Computing, Amazon Web Service, Microsoft Azure, or Sentinel Hub	View
2375	Analyse the EO Image processing tools required for preparing EO data for deep learning	View
2376	Apply different DL approaches in EO imagery for classification, detection, or regression	View
2377	List different types of features that can be used for multispectral image classification	View
2378	Create feature space visualisations for a multispectral image	View
2379	Analyse and select features derived from an image to classify land cover	View
2380	Analyse vegetation growth & development on a land parcel with an NDVI time series derived from EO	View
2400	Discuss advantages and disadvantages of different methods of storing remote sensing data	View
2401	Discuss and compare different temporal resolutions of remote sending data	View
2402	Discuss what the header file describes	View
2403	Discuss how the radiometrically corrected data are processed	View
2404	Explain how the geometrically corrected data are processed	View
2405	Discuss advantages and disadvantages of different SAR data formats	View
2406	Explain the purpose of the analysis ready data	View
2407	Discuss the use of atmospheric passive sounders	View
2408	Explain the principles of spaceborne laser scanning operation and discuss its applications	View
2409	Explain the principles of airborne laser scanning operation and discuss its applications	View
2410	Explain the principles of mobile laser scanning operation	View
2411	Explain the principles of underwater laser scanning operation and discuss its applications	View
2412	Explain the principles of bathymetric laser scanning operation and discuss its applications	View
2500	Explain in which cases land surveying and field data collection are effective data collection methods	View
2501	Describe the scattering and atmospheric absorption factors	View
2502	Understand the main factors generating geometric distortions of the remotely sensed images	View
2503	Describe the data quality dimensions of the main remote sensing lifecycle phases	View
2504	List the main international organization responsible for the standardization of the image data and gridded data quality	View
2505	Describe the role of infrastructures for sharing remote sensing data products	View
2506	Explain the importance of FAIR data principles for accessing remote sensing data and derived products	View
2507	Explain the different types of water quality variables that EO provides for ocean monitoring	View
2508	Understand how EO data can be used to monitor the marine ecosystem	View
2509	Explain the ocean physical and biological variables used for EO-based marine ecosystem monitoring	View
2510	Compare the main satellite sensors used in marine ecosystem monitoring	View
2511	Assess ocean physical and biophysical parameters to evaluate ocean productivity and identify upwelling areas	View
2512	Analyse the emergence of regions with algal blooms in an ocean colour time series data	View
2513	Analyse ocean currents	View
2514	Estimate evaporation rates	View
2515	Find oil spills in EO data for Ocean surveillance	View
2516	Analyse wave height variability	View
2517	Assess climate change effects in time series data	View
2518	Produce EO derived marine ecosystem information to support fisheries management	View
2519	Estimate near-surface chlorophyll-a concentration for monitoring harmful algal blooms (HABs)	View
2520	Choose the right software tool to apply image classification to a specific satellite image	View
2521	Understand what products can be extracted from point clouds	View
4001	Describe the scattering properties of a mirroring surface	View
4002	Describe under which conditions a mirroring surface can be defined a "perfect" mirror	View
4003	Describe under which conditions a Lambertian surface can be defined as a "perfect" Lambertian diffusor	View
4004	Compute the maximum average roughness of a mirror for incident radiation in the visible spectral range	View
4005	Compute the maximum average roughness of a mirror for incident radiation in the microwaves spectral range	View
4006	Compute the minimum average roughness of a surface operating as a diffuser of incident radiation in the visible spectral range	View