ABSTRACT
CONTENTS 1.1 Introduction ................................................................................................... 3 1.2 Methods.......................................................................................................... 5
1.2.1 Landsat Image Acquisition, Rectification, and Land Cover Classification.......................................................................... 6
1.2.2 Development of Impervious Surface Regression Models.......... 8 1.2.3 Impervious Surface Classification.................................................. 9 1.2.4 Accuracy Assessment..................................................................... 10
1.3 Results and Discussion .............................................................................. 10 1.4 Conclusions.................................................................................................. 17 Acknowledgments ............................................................................................... 17 References ............................................................................................................. 18
Impervious surfaces are defined as any surface that water cannot infiltrate. These surfaces are primarily associated with transportation (streets, highways, parking lots, sidewalks) and buildings. Expansion of impervious surfaces increases water runoff and is a primary determinant of stormwater runoff volumes, water quality of lakes and streams, and stream habitat quality in urbanized areas. Increases in impervious surfaces, and accompanying phosphorous, sediment, and thermal loads, can have profound negative impacts on lakes and streams and habitat for fisheries. Percent impervious surface area has emerged as a key factor to explain and generally predict the degree of impact severity on streams and watersheds. It has been generally found that most stream health indicators decline when the
impervious area of a watershed exceeds 10% (Schueler, 1994). Arnold and Gibbons (1996) suggest that impervious surface area provides a measure of land use that is closely correlated with these impacts and more generally that the amount of impervious surface in a landscape is an important indicator of environmental and habitat quality in urban areas. In the area of urban climate, Yuan and Bauer (2006) have recently documented a strong relationship between the amount of impervious surface area and land surface temperatures or the urban heat island effect. It follows that impervious surface information is fundamental for watershed planning and management and for urban planning and policy.
