Suitability Analysis

Identifying a suitable site for bear relocation in Great Smoky Mountains Park.

Problem Statement

There has been increased interactions between black bears and visitors in the Great Smoky Mountains National Park hence problematic to biologists. The park has tried to capture the bears and relocate them to reduce the threat to humans, but bears keep on returning. There is need to relocate them to areas which will be more suitable to bears, and hence reduce the chance of returning to sites where there will be interactions with visitors. The objective of this assignment is therefore to find suitable sites which can be used to relocate the bears

Analysis procedure

To address the problem, I used ArcGIS Pro 3.0.2. I also used five main data sets which included the roads layer, streams layer, trails layer, vegetation clipped layer, and elevation raster layer, all which were provided by the course instructor. Projection for all these datasets was UTM, NAD27, zone 17, meters. I performed this assignment in model builder, and I used the following functions to prepare, transform, and conducted a suitability analysis: Slope, Feature to Raster, Distance Accumulation, Reclassify, and Weighted Overlays.

I started the assignment with transforming my vector datasets into raster layers. I had already set the environments in the analysis table to processing extent of the vegetation layer, and the cell size to “same as layer elev_all”, which was 30meters. The following layers were converted using distance accumulation tool; roads layer, streams layer and trails layer. I used feature to raster tool to convert the vegetation layer to a raster grid, with “CLASSES” set as a field for conversion. Then I used slope tool in spatial analyst tools to convert the Elevation Raster to a slope layer. This was followed by setting the symbiology of the output layer to stretch, so that I have one continuous stretch color code for easy reclassification. After all raster layers were produced, I added the reclassify tool to my model builder and connect all raster outputs to the reclassify tool. This was done to standardize the measurement values to be used in the weighted overlays. 3 main classes were utilized, with 1) least favorable, 2) favorable, 3) most favorable. The following parameters were set in the reclassification of various layers;

Finally, I added the Weighted Overlay tool to the model builder and connected all the reclassified layers. I adjusted the scales to “1-3” and did the same for all layers. I validated the model builder before running the process and I ended with displaying the map which showcased the suitable sites for bear relocation.

Process Diagram

Results

Application and Reflection

Problem statement: Fish provides a 70% of animal protein to Malawi households and its also a source of employment to many individuals living across the lakeshore. There has been a steady decline in large fish of high economic value like chambo, and the government wants to promote aquaculture to argument the capture fisheries supply. The plans are underway and the last aquaculture suitable site zoning exercise was conducted in 2005/6, with no updating to date. Government would like to conduct a suitability analysis to identify areas which are suitable for aquaculture, especially chambo growth, to guide investments in the sector.

Data needed: Roads layer, water availability data, soil layer, temperature raster, and elevation raster layer. The data will be obtained from Malawi Fisheries Department under the Ministry of Agriculture.

Analysis procedure: I will start with transforming my vector datasets into raster layers. I will covert roads layer, streams (water layer), soil type layer to raster using distance accumulation tool. Then I will use slope tool in spatial analyst tools to convert the Elevation Raster to a slope layer. For water, aquaculture requires that the areas has to have continuous supply of water for at least months (most favorable will be 9 months, favorable will be 6-9 months, least favorable will be 0 to less than 6 months). Roads: site has to be close to road network for easy transportation of inputs and produce (within 2km buffer). Soil: clay soil is most favorable for pond aquaculture. Slope: doesn't have to be too steep, nor too flat, to allow for drainage and water flow. I added the reclassify tool to my model builder and connect all raster outputs to the reclassify tool. Then I will reclassify these into 3 main classes with 1) least favorable, 2) favorable, 3) most favorable. I will finally use weighted overlays to find suitable sites for aquaculture, which will then be used to guide investments in aquaculture.