ABSTRACT
The model management component (MMC) of SDSS specifically helps to manage, execute, and integrate different models (Chakhar and Martel
2004). Spatial models provide analytical capabilities to the SDSS and help in examining the locations, attributes, and relationships of features in spatial data through various overlay and analytical methods. As mentioned in Chapters 2 and 3, most existing GIS provide overlay functions but lack advanced analytical modeling capability. In recent years, a few GIS software programs have incorporated analytical spatial models. Examples of analytical modeling capabilities within GIS programs include a locationallocation model in ArcInfo, ideal point analysis in CommonGIS, and the analytic hierarchy process (AHP) and ordered weighted averaging (OWA) capabilities in IDRISI. In other cases, basic modeling frameworks, with specific user interfaces for developing spatial modeling processes, have been introduced in GIS and spatial analysis software. Modeling management frameworks built into GIS and other spatial analysis software include Spatial Modeler and Knowledge Engineer from ERDAS Imagine, Macro Modeler from IDIRISI, and ModelBuilder from Environmental Systems Research Institute (ESRI) (Figure 4.1). However, as these modeling frameworks rely on existing functions within the GIS, most do not provide users with the range of spatially explicit modeling capabilities necessary for complex spatial decision making. These modeling frameworks are growing in sophistication. However, SDSS have traditionally and often still do require the development of a specific model management component that manages a set of models that interact with the spatial database and GIS functionality to produce new information relevant for the decision-making process. The following sections provide a summary of different spatially explicit models often used in spatial decisionmaking processes.
