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Proceedings Paper

Assessment of aeolian desertification in Korqin Sand, China
Author(s): Cui Linli; Fan Wenyi; Shi Jun; Zhiqiang Gao
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Paper Abstract

Desertification is a worldwide concern and the assessment of aeolian desertification has become one hotspot in global ecosystem research. In this paper, hyperspectral data acquired from modular OMIS-I imaging spectrometer, combined with ETM data and field survey data, was used to assess the aeolian desertification in Korqin Sand, Inner Mongolia, China by pixel-level. The results indicated that hyperspectral image, combined with ETM image and little field works, is capable to monitor and assess desertification through quantitative retrieval of assessing parameters directly from hyperspectral data or indirectly from the encoding map by visual interpretation of hyperspectral image and ETM image. For the retrieval of vegetation biomass and coverage, polynomial fit curve is suitable to regions where shrubs and grasses coexist, while linear fit curve is suitable to single vegetation type and was highly restricted by region. The retrieval of surface soil water content based on soil thermal inertia is suitable in flat terrain and sparse vegetation, and it can resist vegetation disturbance. The algorithms for numerical evaluation and quantitative retrieval for hyperspectral image are also practicable for aeolian desertification in Korqin Sand, China.

Paper Details

Date Published: 27 September 2006
PDF: 10 pages
Proc. SPIE 6298, Remote Sensing and Modeling of Ecosystems for Sustainability III, 62981L (27 September 2006); doi: 10.1117/12.677346
Show Author Affiliations
Cui Linli, Shanghai Meteorological Bureau (China)
Fan Wenyi, Northeast Forestry Univ. (China)
Shi Jun, Shanghai Meteorological Bureau (China)
Zhiqiang Gao, Institute of Geographical Science and Natural Resources Research (China)


Published in SPIE Proceedings Vol. 6298:
Remote Sensing and Modeling of Ecosystems for Sustainability III
Wei Gao; Susan L. Ustin, Editor(s)

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