Spatial mapping of riparian vegetation using airborne remote sensing in a gis environment. case study: Middle rio grande river, new mexico

Abstract

This chapter demonstrates a procedure to classify riparian vegetation in the middle Rio Grande River, New Mexico, USA using high-resolution airborne remote sensing in a geographic information system (GIS) environment. Airborne multispectral digital images with spatial resolution of 0.5-meter pixels were acquired over the riparian corridor of the middle Rio Grande River, New Mexico, using the new Utah State University (USU) digital-imaging system covering approximately 175 miles (282 km). The images were corrected for vignetting effects, geometric lens distortions, rectified to 1:24,000 USGS digital ortho-photo quads as a base map, mosaicked, and classified. Areas of the vegetation classes, and in-stream features were extracted and presented. Surface-water area within the river, along with the meso-scale hydraulic features such as riffles, runs, and pools, was classified. The water-surface-area parameters were presented not as an indication of water flow volume in the river, though they could be related, but as a means of showing how changes occur as moving downstream. Analyzing the river images shows that water diversions have a significant effect on the water surface of the river. Records of river flows on the particular day confirm these classification results. Riparian-vegetation mapping using high-resolution remote sensing gives a broad and comprehensive idea about the riparian-zone health and condition along the river. In case of middle Rio Grande, the vegetation-classification image maps may help the decision makers to study and identify problems that affect the river system. This map also provides a base to monitor the riparian vegetation in future, and provides the basis for change detection resulting from any management plan applied to the river corridor with the aim of protecting and restoring the river ecosystem.