DocumentCode :
2104971
Title :
Land cover conversion and degradation analyses through coupled soil-plant biophysical parameters derived from hyperspectral EO-1 Hyperion
Author :
Huete, Alfredo ; Miura, Tomoaki ; Gao, Xiang
Author_Institution :
Dept. of Soil Water & Environ. Sci., Arizona Univ., Tucson, AZ, USA
Volume :
2
fYear :
2002
fDate :
2002
Firstpage :
799
Abstract :
Conversion and degradation in arid, semi-arid, and dry sub-humid areas result from various factors, including climate variations and human activity, and can lead to desertification. The process of degradation results in simultaneous and complex variations of many interrelated and coupled soil-vegetation parameters. General information and data regarding the degree and extent of land degradation and the resulting impacts remain poorly understood and remote sensing can play a major role by providing a quantifiable and replicable technique for monitoring and assessing the extent and severity of soil degradation. We investigated various ´optical´ indicators and early warning signals of land degradation and desertification with the use of hyperspectral remote sensing data derived from EO-1 Hyperion and AVIRIS sensors. Utilizing spectral mixture analysis, we analyzed simultaneous spatial variations in vegetation cover, species, physiognomy, albedo, and soil properties at various sites representing different stages of land degradation in the Mendoza region of Argentina and at sites in the Southwest U.S.A. We found that both soil and vegetation parameters were required to characterize the unstable and spatially variable landscape dynamics found in actively degrading environments.
Keywords :
terrain mapping; vegetation mapping; 400 to 2500 nm; AVIRIS; Argentina; Mendoza region; Southwest USA; albedo; arid areas; climate variations; coupled soil-plant biophysical parameters; desertification; dry subhumid areas; early warning; human activity; hyperspectral EO-1 Hyperion; hyperspectral remote sensing data; land cover conversion; land cover degradation analyses; landscape dynamics; monitoring; physiognomy; remote sensing; semi-arid areas; soil degradation; soil properties; soil-vegetation parameters; vegetation cover; vegetation species; Biomedical optical imaging; Degradation; Humans; Hyperspectral imaging; Hyperspectral sensors; Optical sensors; Remote monitoring; Soil; Spectral analysis; Vegetation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
Print_ISBN :
0-7803-7536-X
Type :
conf
DOI :
10.1109/IGARSS.2002.1025690
Filename :
1025690
Link To Document :
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