Article

[Progress in retrieving vegetation water content under different vegetation coverage condition based on remote sensing spectral information].

Laboratory for Remote Sensing and Climate Information Sciences, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
Guang pu xue yu guang pu fen xi = Guang pu (impact factor: 0.84). 06/2010; 30(6):1638-42. pp.1638-42
Source: PubMed

ABSTRACT The present paper reviews the progress in the methods of retrieving vegetation water content using remote sensing spectral information, including vegetation spectral reflectance information (VIR, SWIR, and NIR) to directly extract vegetation water content and establish vegetation water indices (WI), i. e. NDWI = (R860 - R1 240)/(R860 + R1 240) and PWI = R970/R900; and using radiation transfer (RT) model such as PROSPAIL to detect plant water content information. The authors analyze the method of retrieving vegetation water content under low crop coverage condition. The plant water can be estimated by using canopy physiological parameters firstly, and using vegetation indices and radiation transfer model secondly, which can eliminate soil background effect. The estimated agricultural drought and vegetation water content by using multi-angle polarized reflectance and bi-directional reflectance (BRDF) was discussed in this paper. In the end, the possible development trend of retrieval methods for plant water information under plant low coverage conditions was discussed.

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Keywords

canopy physiological parameters
 
estimated agricultural drought
 
i. e. NDWI
 
low crop coverage condition
 
multi-angle polarized reflectance
 
plant low coverage conditions
 
plant water
 
plant water content information
 
plant water information
 
possible development trend
 
present paper reviews
 
radiation transfer
 
radiation transfer model
 
retrieval methods
 
retrieving vegetation water content
 
soil background effect
 
vegetation indices
 
vegetation spectral reflectance information
 
vegetation water content
 
vegetation water indices
 

Jia-Hua Zhang