Geoprocessing—Computing with geographic data

Geoprocessing is the methodical execution of a sequence of operations on geographic data to create new information. The two fundamental purposes are to help you perform modeling and analysis and to automate GIS tasks.

Spatial analysis

Spatial analysis is the process of modeling, deriving results by computer processing, then examining and interpreting the model results. Spatial analysis is useful for evaluating suitability and capability, estimating and predicting, and interpreting and understanding.

For example, spatial analysis can be used to study the relationships between air quality in urban settings and childhood asthma.

Using spatial analysis in GIS
Home addresses of children with asthma can be geocoded against a streets layer. Major roads (such as multilane roads and highways) can be selected and buffered—say by a distance of 150 meters. These layers can be overlaid for studying this spatial relationship and its impact on the incidence of asthma. GIS includes many more sophisticated operators (such as spatial statistics tools) for studying these relationships.

Spatial analysis is one of the more interesting and remarkable aspects of GIS. Using spatial analysis, GIS users can combine information from many independent sources and derive an entirely new set of information (results)—by applying a large, rich, and sophisticated set of spatial operators. GIS professionals use Geoprocessing to "program their own ideas" in order to derive these analytical results. In turn, these results are applied to a wide variety of problems.

Automation using geoprocessing

Geoprocessing is certainly used for spatial analysis, but it is also used for much more. With geoprocessing, users automate many GIS tasks—data preparation and conversion, creation of a set of automated tests to perform integrity checks of your data against a set of business rules, coordinate management, automation of other data management workflows, map production, and much more.

Geoprocessing is repeatable. In fact, many users create a series of automated workflows that help perform tedious, repetitive work. These workflows are repeatable and self-documenting. They can be shared with many users. They can be placed into a server framework and used for all kinds of GIS tasks, not just for analysis.

The spatial analysis process

Spatial analysis is the process of applying analytic techniques to geographically referenced datasets to extract or generate new geographic information to address a particular question or objective.

Steps in the spatial analysis process


Establish an objective and frame the questions you want to answer.


Gather, organize, and prepare the data for analysis.


Build the analysis model (typically performed using geoprocessing but could be as simple as a few mouse clicks in ArcMap).


Execute the model and generate results.


Explore, evaluate, chart, summarize, interpret, visualize, understand, and analyze the results.


Make conclusions, arrive at decisions, and document your results.


Present your results and findings.

In practice, this analysis process is iterative. A review is conducted at each step, providing the opportunity to incorporate new knowledge and insight gained along the way. The analysis process is one part modeling and one part the generation of—and working with—a series of maps, summary reports, scientific and statistical charts, and summaries for analysis.

During analysis, a model is built based on the analysis objectives. A set of results (output data and map views) is generated. Then that information is analyzed—the results are mapped, compared, visualized, interpreted, modified, updated, calibrated, reexecuted, and so forth.

Users explore and interpret the results and use these to draw conclusions and make decisions.