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INTEGRATION AND MODELLING OF SPATIAL DATA

The integration of data provides the ability to ask complex spatial questions that could not be answered otherwise. Often, these are inventory or locational questions such as how much ? or where ?. Answers to locational and quantitative questions require the combination of several different data layers to be able to provide a more complete and realistic answer. The ability to combine and integrate data is the backbone of GIS.

Often, applications do require a more sophisticated approach to answer complex spatial queries and what if ? scenarios. The technique used to solve these questions is called spatial modelling. Spatial modelling infers the use of spatial characteristics and methods in manipulating data. Methods exist to create an almost unlimited range of capabilities for data analysis by stringing together sets of primitive analysis functions. While some explicit analytical models do exist, especially in natural resource applications, most modelling formulae (models) are determined based on the needs of a particular project. The capability to undertake complex modelling of spatial data, on an ad hoc basis, has helped to further the resource specialists understanding of the natural environment, and the relationship between selected characteristics of that environment.

The use of GIS spatial modelling tools in several traditional resource activities has helped to quantify processes and define models for deriving analysis products. This is particularly true in the area of resource planning and inventory compilation. Most GIS users are able to better organize their applications because of their interaction with, and use of, GIS technology. The utilization of spatial modelling techniques requires a comprehensive understanding of the data sets involved, and the analysis requirements.

The critical function for any GIS is the integration of data.

The raster data model has become the primary spatial data source for analytical modeling with GIS. The raster data model is well suited to the quantitative analysis of numerous data layers. To facilitate these raster modeling techniques most GIS software employs a separate module specifically for cell processing.

The following diagram represents a logic flowchart of a typical natural resource model using GIS raster modeling techniques. The boxes represent raster maps in the GIS, while the connection lines imply an analytical function or technique (from Berry).