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Remote sensing estimation models of wetland vegetation LAI in Sanjiang Plain.

JIN Hua-an1,2; LIU Dian-wei1;WANG Zong-ming1;SONG Kai-shan1;LI Fang1; YANG Fei1,2;DU Jia1,2;LI Feng-xiu1,2    

  1. 1Northeast Institute of Geography and Agricultural Ecology, Chinese Academy of Sciences, Changchun 130012, China; 2Graduate University of Chinese Academy of Sciences, Beijing 100039, China
  • Received:2007-10-11 Revised:1900-01-01 Online:2008-05-10 Published:2008-05-10

Abstract: By using the normalized difference vegetation index (NDVI) extracted from CBERS-02 data and the leaf area index (LAI) data obtained from field measurement, this paper analyzed the relationships between the NDVI and the LAI of total samples of meadow, marsh vegetation, shrubs, and islanded forests of the wetland vegetation in Honghe Nature Reserve of Sanjiang Plain. The linear and non-linear regression models between NDVI and LAI of different wetland vegetation types were established, and the spatial distribution of LAI in the Honghe Nature Reserve was mapped. The results showed that it was unsatisfactory for the whole samples to estimate the LAI, with the correlation coefficient being only 0.523. After the total samples were divided into four vegetation types, i.e., meadow vegetation, marsh vegetation, shrub and islanded forest, the correlation coefficients and the estimation accuracy were improved evidently. Cubic-equations-were found to be the best in the different forms of the regression models for retrieving the LAI of wetland vegetation by using CBERS data, with the R2 value being 0.723, 0.588, 0.837, and 0.720, respectively. It was indicated that with the combination of field-measured data and remote sensing-based vegetation classification, CBERS-02 data could be used for the larger scale estimation of the physiological parameters of wetland vegetation.

Key words: Korqin sandy land, Spatial heterogeneity, Water content in sand layer, Pattern of plant community