With GIS, two- and three-dimensional characteristics of the Earth's surface, subsurface, and atmosphere can be modeled to relate climate events. For example, a GIS can quickly generate a map with isopleth or contour lines that indicate differing amounts of rainfall. A two-dimensional contour map created from the surface modeling of rainfall point measurements may be overlaid and analyzed with any other map in a GIS covering the same area. This GIS derived map can then provide additional information - such as the viability of water power potential as a renewable energy source.

By analyzing topological relationships, spatial modelling can be performed between geometric entities to determine such things as adjacency, containment, and proximity.

Geometric networks are linear networks of objects that can be used to represent interconnected features, and to perform special spatial analysis on them. A geometric network is connected at junction points, similar to graphs in mathematics. Just like graphs, networks can have weight and flow, which can be used to represent road networks, public utility networks.

GIS hydrological models can provide a spatial element data that other hydrological models lack, adding variables such as slope, aspect and watershed. Terrain analysis is fundamental to hydrology, since water always flows downward. Slope and aspect can determine direction of surface runoff and flow accumulation.

Cartographic modeling is a process where several thematic layers are produced, processed, and analyzed for simulation or optimization models.

By overlaying vectors data can be extracted and used in either vector or raster data analysis. Rather than combining the properties and features of both datasets, data extraction involves using a "clip" or "mask" to extract the features of one data set that fall within the spatial extent of another dataset.

Interpolation is the process by which a surface is created, usually a raster dataset, through the input of data collected at a number of sample points. Digital elevation models, triangulated irregular networks, edge-finding algorithms, Thiessen polygons, Fourier analysis, (weighted) moving averages, inverse distance weighting, kriging, spline, and trend surface analysis are all mathematical methods to produce interpolative data.

Geocoding is interpolating spatial locations from street addresses, ZIP Codes, parcel lots and other address locations.

Reverse geocoding is used in returning an estimated street address number as it relates to a given coordinate.

multi-criteria decision analysis supports analysis of alternative spatial solutions, such as the most likely ecological habitat for restoration.

Cartography is the design and production of maps, or visual representations of spatial data.