Senior Honors Projects, 2020-current

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Date of Graduation



Document Type


Degree Name

Bachelor of Science (BS)


Department of Integrated Science and Technology


Zachary J. Bortolot

Nathan R. Sprague

Helmut Kraenzle


Accurate impervious surface calculations are important to many municipalities due to the high volumes of surface rainwater runoff caused by high impervious surface density. Municipalities must deal with this runoff through the establishment and maintenance of drainage facilities. To help offset the added cost of these facilities, many municipalities impose taxes and fees on privately owned impervious surfaces such as homes, driveways, and patios. Currently, in order for a city like Harrisonburg to calculate tax parcel impervious surface density, aerial images must be manually digitized or mapped using computer-based classification techniques using predictive models. These methods of impervious surface calculations can cost municipalities thousands of dollars and/or hundreds of person hours. The purpose of this project is to devise and test a novel procedure for updating municipal tax parcel impervious surface calculations in an effort to help reduce the time and cost currently required to perform these updates. The procedure that was devised establishes a statistical relationship between current aerial imagery attributes (such as mean pixel value, texture, and homogeneity) and past impervious surface calculations. Tax parcels where actual impervious surface density differed greatly from the model’s expected density were flagged to be looked at manually for possible update. This procedure is useful to municipalities because it cuts costs and labor time compared to other methods currently available. Although this project is a case study for the City of Harrisonburg, this procedure could potentially be tailored to other municipalities that have access to high resolution aerial imagery and pre-existing impervious surface maps.



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