Analytical capabilities of a
Analysis of spatial data can be defined as computing new information to provide new insights from existing spatial data. Consider an example from the domain of road construction. In mountainous areas, this is a complex engineering task with many cost factors, including the number of tunnels and bridges to be constructed, the total length of the tarmac, and the volume of rock and soil to be moved. GISs can help to compute such costs on the basis of an up-to-date digital elevation model and a soil map.The exact nature of the analysis will depend on the application requirements, but computations and analytical functions can operate on both spatial and non-spatial data.
There are many ways to classify the analytical functions of a
Classification functions allow the assignment of features to a class on the basis of attribute values or attribute ranges (definition of data patterns). On the basis of reflectance characteristics found in a raster, pixels may be classified as representing different crops, e.g. potato or maize.
Retrieval functions allow selective searching of data. We might, for example, retrieve all agricultural fields on which potato is grown.
Measurement functions allow the calculation of distances, lengths or areas. All functions in this category are performed on a single (vector or raster) data layer, often using the associated attribute data.
Overlay functions are one of the most frequently used functions in a
Neighbourhood functions evaluate the characteristics of an area surrounding a feature’s location. A neighbourhood function “scans” the neighbourhood of the given feature(s), and performs a computation on it(them).
Network analytic functions for computing related to connected line features that make up a network. The network may consist of roads, public transport routes, high-voltage power lines, or other forms of transportation infrastructure. Analysis of such networks may entail shortest path computations (in terms of distance or travel time) between two points in a network for routing purposes. Other forms are to find all points reachable within a given distance or duration from a start point for allocation purposes, or determination of the capacity of the network for transportation between an indicated source location and sink location.
Surface analyses (raster based) are analyses on continuous fields that require more advanced computations, such as:
Here are the examples of the described functions which are applicable to Raster and Vector data.
RASTER | VECTOR |
---|---|
CLASSIFICATION | CLASSIFICATION |
Automatic Classification | Automatic Classification |
User Controlled Classification | User Controlled Classification |
RETRIEVAL | RETRIEVAL |
Selecting features based on their distance | Selecting features based on their distance |
Spatial Selection by Attribute Conditions | |
Selecting features that intersect | |
Spatial Selection using topological relationships | |
Selecting features that are inside a selection object | |
Selecting features that are adjacent to selection objects | |
Interactive Spatial Selection | |
MEASUREMENT | MEASUREMENT |
Standard Distance Function | Location Measurement Function |
Location Measurement Function | |
Distance Measurement Function | |
Area Measurement Function | |
Minimal Bounding Box Function | |
OVERLAY | OVERLAY |
Map Algebra | Polygon Intersection Operator |
Polygon Overwrite | |
Polygon Clipping Operator | |
NEIGHBOURHOOD | NEIGHBOURHOOD |
Proximity Calculations | Proximity Calculations |
Raster Based Surface Analysis | |
Flow Computation | |
Diffuse Calculations | |
CONNECTIVITY | CONNECTIVITY |
Optimal Path Finding | Optimal Path Finding |
Network Partitioning | |
Network Allocation | |
Trace Analysis | |
Classify and explain spatial analysis functions (measurements, classification, overlay, neighbourhood and connectivity) in a raster and vector environment (level 1 and 2).