This paper presents methods and results of county-level population estimation using Landsat Thematic Mapper (TM) images of Denton County and Collin County in Texas. Landsat TM images acquired in March 2000 were classified into residential and non-residential classes using maximum likelihood classification and knowledge-based classification methods. Accuracy assessment results from the classified image produced using knowledge-based classification and traditional supervised classification (maximum likelihood classification) methods suggest that knowledge-based classification is more effective than traditional supervised classification methods. Furthermore, using randomly selected samples of census block groups, ordinary least squares (OLS) and geographically weighted regression (GWR) models were created for total population estimation. The overall accuracy of the models is over 96% at the county level. The results also suggest that underestimation normally occurs in block groups with high population density, whereas overestimation occurs in block groups with low population density.

The dataset was developed to support research intended to develop a spatially-explicit model that prioritizes riparian areas in terms of potential for ecosystem restoration specifically to improve water quality downstream of the riparian area, and ultimately improve drinking water quality. The model was developed and then tested on the Lewisville Lake watershed (north central Texas, just north of Dallas, Texas, USA). The dataset contains environmental data for 90 sub-watersheds that form the overall Lewisville Lake watershed with a corresponding identification map.