Paper
14 July 2003 Grassland desertification monitoring by remote sensing and GIS in the upper reaches of the Yellow River, northeast Qinghai-Xizang Plateau
Yongnian Zeng, Zhaodong Feng, Guangchao Cao, Weguo Wang
Author Affiliations +
Proceedings Volume 4890, Ecosystems Dynamics, Ecosystem-Society Interactions, and Remote Sensing Applications for Semi-Arid and Arid Land; (2003) https://doi.org/10.1117/12.487568
Event: Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2002, Hangzhou, China
Abstract
The detailed land use/cover classification using remotely sensed data are the best means of delineating the surface changes for sandy desertification monitoring. The analysis of land use/cover with ancillary in GIS and in situ fieldwork shows that the land use/cover type can be used as indicators of sandy desertification severity effectively. Based on the analysis of the multi-temporal and multi-spectral Landsat TM data with ancillary data in GIS, sandy desertification of grassland was detected in 1987 and 1996. The results indicate that Gonghe Basin is one of the most desertified regions in the upper reach of the Yellow River, northeast Qinghai-Xizang Plateau. Among the sandy desertified lands, the severe and moderate sandy desertified lands are easy to expand, as well as to reverse. Therefore, these kinds of sandy desertified land will be the main conservancy areas in the future. It is necessary and urgent to combat desertification and protect environment in the upper reach of the Yellow River.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yongnian Zeng, Zhaodong Feng, Guangchao Cao, and Weguo Wang "Grassland desertification monitoring by remote sensing and GIS in the upper reaches of the Yellow River, northeast Qinghai-Xizang Plateau", Proc. SPIE 4890, Ecosystems Dynamics, Ecosystem-Society Interactions, and Remote Sensing Applications for Semi-Arid and Arid Land, (14 July 2003); https://doi.org/10.1117/12.487568
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Cited by 2 scholarly publications.
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KEYWORDS
Geographic information systems

Climatology

Ecosystems

Remote sensing

Climate change

Data modeling

Earth observing sensors

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