Process_Description:
Three datasets were provided by FEMA (William Melville III, Federal Emergency Management Agency, unpub. data, October 6, 2021) to represent density of locations for flood-related insurance claims, individual assistance applications, and repetitive losses. The three density datasets were derived from their original point feature classes in order to generalize the locational data for privacy purposes. FEMA’s preprocessing steps involving the point feature classes before providing the density datasets to the USGS are described in greater detail in this process step and were performed using ArcGIS Pro [GIS software] Version 2.8, Redlands, California: Environmental Systems Research Institute, Inc., 2021.
The insurance claims point feature class includes claim point data dating from 1975 through August 2021 with each point representing a single claim. The point feature class was converted to a density raster by calculating the magnitude-per-unit area from point features that fall within a neighborhood around each cell using the Point Density Spatial Analyst tool. Each feature (claim) was counted once according to a circular neighborhood using the default cell size (1,365 meters) and radius (11,372 meters), where the default radius is calculated as the shortest of the width or height of the extent of the input point features, in the output spatial reference (National Spatial Reference System 2011), divided by 30, with the output data area units designated as square kilometers.
The individual assistance application point feature class includes individual assistance application data dating from 2003 through July 2021 with each point representing the centroid of a 1-kilometer square grid. For each 1-kilometer square in the grid dataset, the total sum of all applications (all people who applied for damage) for flood, hurricane, tornado, and severe storm incident types had been aggregated. The centroid of each cell was calculated with the total sum of individual assistance applications retained in the resulting point feature class dataset. The point feature class was converted to a density raster by calculating the magnitude-per-unit area from point features that fall within a neighborhood around each cell using the Point Density Spatial Analyst tool. Each feature (total sum of individual assistance applications within a 1-kilometer grid cell) was counted once according to a circular neighborhood using the default cell size (1,312 meters) and radius (10,930 meters), where the default radius is calculated as the shortest of the width or height of the extent of the input point features, in the output spatial reference (National Spatial Reference System 2011), divided by 30, with the output data area units designated as square kilometers.
The repetitive loss record point feature class includes repetitive loss record data representing all losses from 1975 through August 2021 with each point representing a single repetitive loss record. The point feature class was converted to a density raster by calculating the magnitude-per-unit area from point features that fall within a neighborhood around each cell using the Point Density Spatial Analyst tool. Each feature (repetitive loss record) was counted once according to a circular neighborhood using the default cell size (1,300 meters) and radius (10,831 meters), where the default radius is calculated as the shortest of the width or height of the extent of the input point features, in the output spatial reference (National Spatial Reference System 2011), divided by 30, with the output data area units designated as square kilometers.