Analysis

Analytical capabilities of a GIS make use of spatial and non-spatial (attribute) data to answer questions and solve problems that are of spatial relevance. We now make a distinction between analysis (or analytical operations) and analytical models (often referred to as “modelling”). And by analysis we actually mean only a subset of what is usually implied by the term: we do not specifically deal with advanced statistical analysis (such as cluster detection or geostatistics).

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 GIS. The classification presented here is essentially the one put forward by Aronoff (1989), which makes the following distinctions:

Classification, measurement and retrieval functions

• 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

Overlay functions are one of the most frequently used functions in a GIS application. They combine two (or more) spatial data layers, comparing them position by position and treating areas of overlap - and of non-overlap - in distinct ways. Many GISs support overlays through an algebraic language, expressing an overlay function as a formula in which the data layers are the arguments.

Neighbourhood functions

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 Analysis

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 Analysis

Surface analyses (raster based) are analyses on continuous fields that require more advanced computations, such as:

• Slope angle and slope aspect
• Visibility functions

Raster vs. Vector

Here are the examples of the described functions which are applicable to Raster and Vector data.