Weighted Overlay with Model Builder



The objective of this assignment was to perform a Weighted Overlay analysis using ArcGIS Model Builder for the following scenario: "Biologists at the Great Smokey Mountain National Park are having problems with certain black bears. The problems occur when park visitors and bears interact. The problems seem to be concentrated around roads and trails throughout the park. Even though biologists capture these bears and relocate them to other areas of the park, they seem to return. Biologists want to know if there are areas in the park that would provide the basic needs for bears that would not lead to any human interactions."


This project was part of the requirements for GIS 520, Advanced Spatial Analytics. The data was provided with the assignment and consisted of separate layers for the following parke features: Roads, Streams, Trails, Vegetation, and Slope.


Several tools were used within Model BUilder to derive the solution of this project. The first step was to convert each of the given layers into Raster format. The Euclidean Distance tool was used for the line input shapefiles: Roads, Streams, and Trails. The Slope tool was used for the Elevation input file, and the Feature To Raster tool was used for the Vegetation input file. The output of each tool was then Reclassified (with the Reclassify tool) to align the scale of each layer to a know value that match the given suitability factors for the bear habitats. The final step in the analysis was to feed each of the Reclassified layers into the Weighted Overlay tool, each with an equal 20% weigthing, to provide a single Raster output of the solution.


Weighted Overlay is a powerful Spatial Analysis tool that helps to answer the question 'Where?' by allowing individual factors such as topography, distance to roads, streams, or trails to be individually ranked and then combined into a single scale. The most important item to consider when performing an analysis of this type, is to understand how the classifications are ranked or grouped together. By using Model Builder, it allows the inputs to be quickly adjusted for various weightings of input criteria.