Solving spatial problems with representation and process models
The ArcGIS Spatial Analyst extension can help you perform useful analysis, but it cannot solve problems by itself. To get the results you are hoping for, you have to ask the right questions and provide the right information.
Modeling spatial problems
In general terms, a model is a representation of reality. Due to the inherent complexity of the world and the interactions in it, models are created as a simplified, manageable view of reality. Models help you understand, describe, and predict how things work in the real world.
There are two main types of models:
- Representation models—Represent the objects in the landscape
- Process models—Simulate processes in the landscape
Representation models
Representation models try to describe the objects in a landscape. Examples of these objects include buildings, streams, or forests. The way representation models are created in a GIS is through a set of data layers. For Spatial Analyst, these data layers will be either raster or feature data. Raster layers are represented by a rectangular mesh or grid, and each location in each layer is represented by a grid cell, which has a value. Cells from various layers stack on top of each other, describing many attributes of each location.
The representation model attempts to capture the spatial relationships within an object (for example, the shape of a building) and between the other objects in the landscape (for example, the distribution of buildings). Along with establishing the spatial relationships, the GIS representation model is also able to model the attributes of the objects (for example, who owns each building). Representation models are sometimes referred to as data models and are considered descriptive models.
Process models
Process models attempt to describe the interaction of the objects that are depicted in the representation model. The relationships are modeled using spatial analysis. There are many different types of interactions, Spatial Analayst provides a large suite of tools to describe them. Process modeling is sometimes referred to as cartographic modeling. Process models can be used to describe processes, but they are often used to predict what will happen if some action occurs.
Each Spatial Analyst tool can be considered a process model. Some process models are simple, while others are more complex. Even more complexity can be incorporated by adding logic and combining multiple process models with Map Algebra or ModelBuilder.
One of the most basic Spatial Analyst operations is adding two rasters together:
Complexity can be added through logic. For instance, if a location has sandy soil that is also dry, the location meets the criteria (true [T]) and is a suitable location for some purpose:
Additional complexity is added through specialized tools whose algorithms are designed to generate analytical results that would be very difficult to create yourself. Examples of these types of tools are ones that calculate non-Euclidean distance or hydrological dispersion of contaminants in groundwater.
And even more complexity can be achieved by combining multiple tools and logic:
A process model should be as simple as possible to capture the necessary reality to solve your problem. You may only need a single operation or tool, but with complicated models, sometimes hundreds may be necessary.
Types of process models
There are many types of process models to solve a wide variety of problems, including these:
- Suitability modeling—What is the optimum location for something, such as a new school, landfill, or public park?
- Distance modeling—What are the nearest protected habitats for an endangered species?
- Hydrologic modeling—What direction will the water flow off a surface?
- Surface modeling—What are the pollution levels for various locations in a county?