A Cape-wide view of impervious surfaces

Locating the intensity of impervious cover on Cape Cod allows us to identify those areas at risk of water quality or natural habitat degradation.

It was necessary to create a basic GIS model in order to fill in the voids in our Impervious Surfaces map and create a Cape-wide coverage of these areas.  A set of coefficients representing the estimated number (or percentage) of impervious surfaces per statewide Massachusetts Land Use category (based on the McConnell land cover categorization) on Cape Cod was calculated. Their value is the average area of impervious surfaces for all polygons of the McConnell land use data set (where high quality data exists) divided by the total area of those polygons (e.g. Imperv. Surface Area/Land Use Area * 100). Assuming that there is a direct relationship between the area of impervious surfaces and population density, the set of coefficients was enhanced by subsetting the land use data into three population density districts and adjusting the coefficient values for each of these categories. We used US Census data from the year 2000 to divide Cape Cod into high, medium, and low population density districts.

Using these impervious surface coefficients, we interpolated or modeled, the percentage of impervious surface land for areas where no detailed geodata existed. The Impervious Surface Analysis Tool (ISAT) of Prisloe et al. (2001), an extension for ArcGIS software, estimates the amount of impervious land in a user defined polygon (or set of polygons) by overlaying the area of the polygon with a land use grid and applying the coefficient assigned to the land use codes in the value table of the grid. The output is a polygon coverage of similar extent indicating the percent imperviousness per feature. We found that after a reasonable set of impervious surfaces coefficients was established for Cape Cod that the ISAT tool was very useful in modeling the voids in our data.

In the maps below, high percentages of impervious surfaces are shown in red.  These are likely to be 'hotspots' indicating poor water quality due to impervious land cover.

Percent Impervious Surfaces per Land Cover Polygon

Percent Impervious Surfaces per Census Block Polygon

©Woods Hole Research Center, 2005