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  "description" : "\u003cDIV STYLE=\"text-align:Left;\"\u003e\u003cDIV\u003e\u003cDIV\u003e\u003cP\u003e\u003cSPAN\u003eSurface Temperature (°F) Difference from County Mean by Census Block.\u003c/SPAN\u003e\u003c/P\u003e\u003cP\u003e\u003cSPAN\u003eThe Remote Sensing Lab's \u003c/SPAN\u003e\u003cA href=\"http://rslab.gr:80/downloads_LandsatLST.html\" STYLE=\"text-decoration:underline;\"\u003e\u003cSPAN\u003eLandsat Land Surface Temperature\u003c/SPAN\u003e\u003c/A\u003e\u003cSPAN\u003e webpage was used to determine the eight, hottest, mostly cloud free days for the region from 2014-2017.\u003c/SPAN\u003e\u003c/P\u003e\u003cP\u003e\u003cSPAN\u003eEight rasters (representing data for the aforementioned eight, hottest, mostly cloud free days for the region) were downloaded from the Landsat Land Surface Temperature page.  Each was then smoothed using Esri's \u003c/SPAN\u003e\u003cA href=\"https://desktop.arcgis.com:443/en/arcmap/latest/tools/spatial-analyst-toolbox/focal-statistics.htm\" STYLE=\"text-decoration:underline;\"\u003e\u003cSPAN\u003eFocal Statistics\u003c/SPAN\u003e\u003c/A\u003e\u003cSPAN\u003e tool to fill in cloud gaps.  Then, the \u003c/SPAN\u003e\u003cA href=\"https://desktop.arcgis.com:443/en/arcmap/latest/tools/spatial-analyst-toolbox/raster-calculator.htm\" STYLE=\"text-decoration:underline;\"\u003e\u003cSPAN\u003eRaster Calculator\u003c/SPAN\u003e\u003c/A\u003e\u003cSPAN\u003e tool was used to average each of the eight images.  The images were then cut to the region's boundary.  They were further divided into county, tract, block group, and block level geographies.   The \u003c/SPAN\u003e\u003cA href=\"https://desktop.arcgis.com:443/en/arcmap/latest/tools/spatial-analyst-toolbox/zonal-statistics.htm\" STYLE=\"text-decoration:underline;\"\u003e\u003cSPAN\u003eZonal Statistics\u003c/SPAN\u003e\u003c/A\u003e\u003cSPAN\u003e tool was then used to find an average surface temperature for each geography.  The difference between the smaller geographies and the regional or county geographies, depending on the analysis, was determined and each was mapped.\u003c/SPAN\u003e\u003c/P\u003e\u003cP\u003e\u003cSPAN\u003eFor the temperature score, the same standard deviation process as the Indicators of Potential Disadvantage (IPDs) was used, assigning a score of 0-4 depending on the number of standard deviations from the regional or county average outlined in the IPD methodology.  This was done for the region as a whole and then for each block, block group, or tract relative to its county.\u003c/SPAN\u003e\u003c/P\u003e\u003cP\u003e\u003cSPAN\u003eFor additional information, see DVRPC's \u003c/SPAN\u003e\u003cA href=\"https://www.dvrpc.org:443/energyclimate/extremeheat\" STYLE=\"text-decoration:underline;\"\u003e\u003cSPAN\u003eMunicipal Management of Extreme Heat\u003c/SPAN\u003e\u003c/A\u003e\u003cSPAN\u003e webpage.\u003c/SPAN\u003e\u003c/P\u003e\u003c/DIV\u003e\u003c/DIV\u003e\u003c/DIV\u003e", 
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