[Extraction of structured vegetation cover index for Loess Area in North Shaanxi based on TM images].
Based on the concept of structured vegetation cover index (Cs) and by using TM images as the information source, the extraction way of Cs for Loess Area in North Shaanxi by using remote sensing techniques was explored. In study area, Cs was better than the traditional projected vegetation coverage index in expressing the relationships between vegetation structure and soil erosion. The Cs was closely related to the remote sensing vegetation indices, such as green indices NDVI (Normalized Difference Vegetation Index) and MSAVI (Modified Soil Adjusted Vegetation Index), and yellow indices NDSVI (Difference Senescent Vegetation Index) and NDTI (Normalized Difference Tillage Index). The combination of the green and yellow indices could better express the effects of vegetation on soil erosion, compared with the single index. Among these remote sensing vegetation indices, the MSAVI and NDTI could be the ideal green and yellow vegetation indices for the extraction of Cs from TM images. It was possible to extract the Cs from remote sensing data through the regression analysis of Cs and remote sensing vegetation indices. However, this method was just validated and applied to the study area. Whether it could be applied to other regions was needed to be further validated due to the phonological differences from one region to another.
Chengdu Hydropower Investigation Design & Research Institute, Chengdu 610072, China. yllwn2005@163.com
Wan-Ning
WN
Lei
Zhong-Ming
ZM
Wen
D000465:Algorithms; D000531:Altitude; D002681:China; D003247:Conservation of Natural Resources; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods*; D063245:Plant Development; D006109:Poaceae / Q000254:growth & development; D017215:Satellite Communications