Failing septic systems contribute to compromised surface and ground water quality. Counties and regulatory agencies seeking to develop strategies to mitigate this potential source of pollution require, but typically lack, a digitized septic system database which can be logistically expensive to develop. To support that effort, a toolkit to locate and date septic systems was developed and tested in Jackson County, Georgia. Multi-temporal, high-resolution aerial imagery was classified using a supervised support vector machine algorithm to identify buildings. The building classification resulted in a 79% accuracy, and the results were geoprocessed with necessary vector layers in a GIS framework to develop Septic System Automated Location Tool (SSALT). The validation of SSALT with geocoded septic permits for Jackson county showed that 83% parcels were correctly identified to be on septic systems, 7% were incorrectly assigned on septic systems while 10% of parcels identified on septic systems did not contain a building.
