Population calibrated land cover impervious surface coefficients for Upper Bhima basin

Impervious surfaces can be defined as any material that prevents the infiltration of water into the soil. Impervious surfaces not only indicate urbanization, but also are major contributors to the environmental impacts of urbanization. As the natural landscape is paved over, a chain of events is initiated that typically ends in degraded water resources. This paper is an attempt to develop a multiple regression model for extraction of impervious surface at a pixel level for a watershed using IRS P-6 (USS-III) and Landsat TM image. The regression equation that was generated involved a number of parameters such as band values, NDVI, Tasseled Cap (BandII) values, slope, elevation, and population density which were used to predict the percent area that is covered with impervious surfaces. Impervious surfaces were extracted village wise and impervious surface coefficients were calculated for the entire study area. These two multi-date images are classified to obtain the land use pattern and correlate it with the impervious surface retrieved from the images. The final output obtained from regression model is critically important to the design and implementation of land use plans and strategies aimed at preventing water quality impairment from urban non-point pollution.