Identification of Roads for Urban Runoff Pollution Management

Urban roads are identified as major sources of many pollutants and the runoff from these areas discharges high pollution mass loads to receiving waters. Identifying roads is important for effective urban runoff and non point source pollution management. However, public land use information usually does not provide detailed road information. In this research, we identified roads and streets in an urban area to estimate their runoff pollution. We used high resolution multi-spectral imagery i.e. IKONOS. The classified image was used to estimate urban runoff pollutant mass loads and compared them to the estimates using public land use information. The results show that the pollutant load estimation was improved by using high resolution imagery because of the extracted road information. The overall results of this work suggest that using high resolution multi-spectral data is a promising way to estimate overall stormwater pollutant loads. This method could be used as an alternative method of estimating limits for the US EPA´s total maximum daily loads control strategies.