Geoprocessing Solutions Developed While Calculating the Mean Human Footprint™ for Federal and State Protected Areas at the Continent Scale

Donald J Lipscomb, Robert F Baldwin

Abstract


We calculated the mean Human Footprint™ (HF) for 196,498 polygons representing state and federal administrated Protected Areas (e.g., National Forests, National Parks, State and/or Provincial Parks, etc.) of Canada, Mexico, and the Continental United States. Separate calculations were made for (1) the area in each protected area which ranged in size from less than one to over 11 million hectares and (2) the area outside and within 10 km of each protected area. We used “Last of the Wild’s” V. 2 (2005) for North America as the data source for Human Footprint™ values with spatial reference. This paper is about the technical problems we encountered using ArcGIS 9.3 and Spatial Analyst to accomplish this task in a timely manner. We wrote several scripts to automate processes and address overlapping polygons resulting from zone calculations of 10 km around each protected area (doughnut-shaped polygons defining the zones from which to calculate mean HF adjacent to protected areas). We learned that Spatial Analyst does not honor the object integrity of overlapping polygons when using them to define zones for calculating zonal statistics from raster data. We tried alternative solutions including the use of Hawth’s Analysis Tools v3.27 (Zonal Statistics [++]) and writing scripts in Visual Basic 6.0 to separate overlapping polygons and to calculate zonal statistics both as a table and output raster. One of the four scripts resulting from this project was written to calculate the 10 km zone around each Protected Area polygon. This script can be used to calculate a separate ‘doughnut’ polygon for any distance outside of any size polygon, even if it shares boundaries with other polygons. We also discovered that the zonal statistics function in Spatial Analyst does not calculate all of the zones in a large dataset even if the polygons do not overlap. Our solution for this problem is described in this paper as an iterative process ending with another custom script to define the raster value located under the ‘label point’ of each polygon in a dataset. Ultimately, we successfully calculated the mean Human Footprint™ from a spatially defined raster both inside and outside the nearly 200,000 polygons defining the boundaries of Protected Areas in North America (http://cec.org/atlas).  MCFNS 2(2):138-144.

Keywords


Conservation biology, Human Footprint™, protected areas, scripts

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