Author(s):
Zachary D Wilson* - United States Geological Survey
Jean W Parcher - United States Geological Survey
Abstract:
Land-cover change datasets provide an essential base layer for understanding how changes in land-cover might affect water-resource issues, such as water use, surface run-off, or water quality. Land-cover change-detection procedures developed by Michael Coan and Joyce Fry of the U.S. Geological Survey (USGS) Center for Earth Resources Observation & Science (EROS) have provided a methodology for the production of land-cover change datasets using aggregated land-cover data from the National Land Cover Dataset (NLCD) 1992 and NLCD 2002 as training data. Landsat imagery from 1992 and 2002 is reclassified at Anderson Level I to produce a land-cover change dataset. This process eliminates the need to collect training data in the field. The USGS U.S.-Mexico Border Environmental Health Initiative (BEHI) is a multidisciplinary project that requires bi-nationally integrated datasets, including land-cover, to assess environmental health applications. Use of national land-cover datasets as training data along international borders is problematic, as most national datasets are created without regard for techniques used in neighboring countries. In the lower Rio Grande Valley, the BEHI project team has developed a bi-nationally integrated land-cover dataset using land-cover data from the USGS and Mexico's Instituto Nacional de Estadística, Geografía, e Informática. Using bi-nationally integrated land-cover data in conjunction with the methodology of Coan and Fry could prove to be effective in developing land-cover change datasets for application to water-resource issues along the U.S.-Mexico border.
