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Proceedings Paper

The generation of China land surface datasets for CLM
Author(s): Haiying Li; Hongchun Peng; Xin Li; Frank Veroustraete
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Paper Abstract

Community land model or common land model (CLM) describes the exchange of the fluxes of energy, mass and momentum between the earth's surface and the planetary boundary layer. This model is used to simulate the environmental changes in China. Hence, it requires a complete parameters field of the land surface. The present paper focuses on making the surface datasets of CLM in China. In the present paper, vegetation was divided into 39 Plant Function Types (PFTs) of China from its classification map. The land surface datasets were created using vegetation type, five land cover types (lake, wetland, glacier, urban and vegetated), monthly maximum Normalized Difference Vegetation Index (NDVI) derived from SPOT_VGT data and soil properties data. The percentages of glacier, lake and wetland were derived from their own vector maps of China. The fractional coverage of PFTs was derived from China vegetation map. Time-independent vegetation biophysical parameters, such as canopy top and bottom heights and other vegetation parameters related to photosynthesis, were based on the values documented in literatures. The soil color dataset was derived from landuse and vegetation data based on their correspondent relationship. The soil texture (clay%, sand% and silt%) came from global dataset. Time-dependent vegetation biophysical parameters, such as leaf area index(LAI) and fractional absorbed photosynthetically active radiation(FPAR), were calculated from one year of NDVI monthly maximum value composites for the China region based on equations given in Sellers et al. (1996a,b) and Los et al. (2000). The resolution of these datasets for CLM is 1km.

Paper Details

Date Published: 31 October 2005
PDF: 11 pages
Proc. SPIE 5983, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology V, 59831W (31 October 2005); doi: 10.1117/12.627606
Show Author Affiliations
Haiying Li, Cold and Arid Regions Environmental and Engineering Research Institute, CAS (China)
Hongchun Peng, Cold and Arid Regions Environmental and Engineering Research Institute, CAS (China)
Xin Li, Cold and Arid Regions Environmental and Engineering Research Institute, CAS (China)
Frank Veroustraete, Flemish Institute for Technological Research (Belgium)


Published in SPIE Proceedings Vol. 5983:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology V
Manfred Ehlers; Ulrich Michel, Editor(s)

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