During 2002, significant progress was made in current land-use mapping, vegetation surveys, remote data classification, data acquisition, geographic information system (GIS) development, and analysis/modeling in the GIS environment. The land-use maps graphically indicate how growth in population has impacted natural vegetation. Analysis of 1995 and 1960 land-use data shows an explosive growth of residential urban parcels, particularly in the McAllen-Pharr-Edinburg area. Mapping of woodlands shows very little of this category left in Hidalgo County. Climate data indicate "heat islands" encircling both the McAllen and Brownsville urban areas. We continued using large-scale photography with 1-m resolution in conjunction with field surveys and high-resolution (4 to 7 m), spectrally calibrated hyperspectral data to train classification algorithms for analysis of riparian vegetation in the Santa Ana National Wildlife Refuge. These analyses were used to scale upward using medium-resolution Landsat 7 Thematic Mapper (TM) data that cover the entire Lower Rio Grande Valley. One element of the methodology is to use the interpretative capabilities of a GIS to examine linkages between riparian ecology and parameters such as geology, topography, soils, water quality, hydrology, and land cover/land use.

This ongoing assessment of southwestern U.S. riparian ecosystems along the Lower Rio Grande Valley of Texas and Mexico is supported by a grant from the U.S. Environmental Protection Agency's Science to Achieve Results program. Riparian ecosystems of the southwestern United States are among the most productive ecosystems of North America, but these ecosystems are generally in decline. In this project, researchers are working to collect and analyze high-resolution, remotely sensed data from multiple sensors; integrate existing and new field data and remotely sensed data into a GIS; determine whether native vegetation communities are maintaining themselves and identify the factors that perpetuate these communities; interpret spatial and temporal variations in riparian habitats; and develop a foundation for future analysis of riparian floodplain communities by linking local and remotely sensed regional data using GIS.

In 2003 we will continue acquiring additional data, classifying and ground-truthing remotely sensed data, completing vegetation transects, entering data into our GIS, analyzing and applying models to define riparian relationships with other mapped characteristics, and presenting results in publications and at conferences.