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Proceedings Paper

Estimation of the spring wheat water and chlorophyll content in rainfed agriculture areas of the Loess Plateau based on the spectral absorption feature of the liquid water and chlorophyll
Author(s): Xiaoping Wang; Ni Guo; Kai Zhang; Hong Zhao
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Paper Abstract

Because of the high water content of vegetation, water absorption feature dominate spectral reflectance of vegetation in the near-infrared region of the spectrum, and chlorophyll dominate the visible region. Previous studies have primarily related water band indices (WI) to vegetation water content. But the similar studies are vacancy in Rained Agriculture Areas of Loess. Two observation tests were carried out in arid and semi-arid area in Loess Plateau in order to find out the best preferential sensitively spectral index to water content and chlorophyll for the spring wheat and to monitor crops drought in this area. The results indicated that at leaf level the NDVI and EVI are the highest sensitive indices to the FMC and Chlorophyll, and for the leaf EWT, SAVI is the best index((r=0.738,P<0.01)); at canopy level, the red edge (λred) and the water content have the best relationship, and the sensitivity for WI1180 and NDWI are better. And the λred is also the best indictor for the chlorophyll at canopy level, the second is R670/R440, Furthmore, If considered the potential for atmospheric interference when data are collected from aircraft or satellite plarforms, So WI1180, WI1450 and NDWI may be the feasible for satellite remote sensing of vegetation water content at the canopy level. Meanwhile the NDVI and EVI may be the best index for satellite remote sensing of vegetation water content at leaf level for the arid and semiarid Rainfed Agriculture Areas of Loess Plateau.

Paper Details

Date Published: 7 November 2008
PDF: 10 pages
Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71471F (7 November 2008); doi: 10.1117/12.813252
Show Author Affiliations
Xiaoping Wang, Lanzhou Institute of Arid Meteorology (China)
Ni Guo, Lanzhou Institute of Arid Meteorology (China)
Kai Zhang, Lanzhou Institute of Arid Meteorology (China)
Hong Zhao, Lanzhou Institute of Arid Meteorology (China)


Published in SPIE Proceedings Vol. 7147:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

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