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.
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.