Parameterization Essay

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3.2.6.3 Parameterization This refers to analysis parameters and input layer preparation to run FRAGSTATS in order to calculate spatial metric indices. This includes categorical map formatting and setting analysis parameters (sampling strategies and specifying neighbor rule to delineate patches). FRAGSTATS accepts several types of input image data formats, ESRI grid, ArcGIS raster grid, GeoTIFF grid (.tif), ERDAS Imagine grid (.img), SAGA GIS binary format grid (.sdat) and several others. For this study, classified maps with ERDAS Imagine grid (.img) formats used as an input. All input maps were integer grids i.e., each cell assigned an integer value corresponding to its class membership or patch type with the measurement units in meters.…show more content…
3.2.7 Statistical Layer Generation and Zonal Metrics Analysis This is conducted mainly to address and measure the direction and location of urban sprawl in the study area using ZonalMetrics Toolbox. ZonalMetrics toolbox is a new open source tool developed by Adamczyk and Tiede (2017) and written in python script to be added as toolbox in ArcGIS 10.2 or latest versions. It is such an important python tool with a specialized functionality for calculating spatial metrics at zonal level. The tool computes selected spatial metrics such Class Area (CA), Number of patches per class (NPC), Zone Area (ZA), Percentage of zone (PZ), Total Class Edge (TE), Edge Density (ED) and Diversity (SHDI) indices in the same way they are calculated in FRAGSTATS but here indices are calculated per class and per specified zones. The toolbox has the following 3 available utilities (Adamczyk, and Tiede, 2017): it accepts user-defined vector based categorical (polygon) layers for direct analysis; it provides landscape metrics designed to calculations within any user-defined zones for example regular gridded zones, administration zones, environmental zones, and last it provides functionalities to generate specific zone (pies, hexagons) to serve as statistical

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