Accurate measurement of impervious surface (IS) cover is an essential indicator of downstream water quality and a critical input variable for many water quality and quantity models. This study compares IS estimates from a recently developed satellite imagery/land cover approach with a more traditional aerial photography/land use approach. Both approaches are evaluated against a high-quality validation set consisting of planimetric data merged with manually-delineated areas of soil disturbance. The study area is the rapidly urbanizing 127 km2 Cub Run watershed in northern Virginia, located on the fringe of the Washington, D.C. metropolitan region. Results show that photo-interpreted IS estimates of land class are higher than satellite-derived IS estimates by 100 percent or more, even in land uses conservatively assigned high IS values. Satellite-derived IS estimates by land class correlate well with planimetric reference data (r = 0.95) and with published ranges for similar sites in the region. Basin-wide mean IS values, difference grids, and regression and density plots validate the use of satellite-derived/land cover-based IS estimates over photo-interpreted/land use-based estimates. Results of this site-specific study support the use of automated, satellite-derived IS estimates for planning and management within rapidly urbanizing watersheds where a GIS system is in place, but where time-sensitive, high quality planimetric data is unavailable.
ASJC Scopus subject areas
- Computers in Earth Sciences