The city of Lansing, Michigan asked Barr to develop a more accurate method of calculating non-residential stormwater utility fees than the rough estimates it had been using, which didn’t fairly represent the actual amounts of runoff from individual properties. Our solution was to create a landcover-classification system based on a dataset of high-resolution aerial images, which the city can analyze alongside its parcel data to determine the percentage of each property that is impervious to rainwater (i.e., covered by buildings and/or hard materials like concrete, asphalt, and rocks).
Barr used near-infrared imagery from the USDA’s National Agriculture Imagery Program to identify first the distribution of pervious and impervious surfaces across the city, and then the percent of impervious surface on each non-residential parcel. We also classified the different types of pervious cover (such as grass, trees, and soil). Finally, we helped Lansing staff members clean up the existing parcel data by removing inaccurate or duplicate information before the city appended the new dataset to the its parcel information.
This GIS-based method of analyzing properties has given the city of Lansing an accurate, objective way to determine stormwater fees for owners of non-residential land parcels.
Senior Water Resources Engineer GIS Coordinator