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

Xiaoping Wang; Ni Guo; Kai Zhang; Hong Zhao

doi:10.1117/12.813252

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7 November 2008 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

Xiaoping Wang, Ni Guo, Kai Zhang, Hong Zhao

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Proceedings Volume 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images; 71471F (2008) https://doi.org/10.1117/12.813252
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

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 (λ_red) and the water content have the best relationship, and the sensitivity for WI₁₁₈₀ and NDWI are better. And the λ_red 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.

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Xiaoping Wang, Ni Guo, Kai Zhang, and Hong Zhao "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", Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71471F (7 November 2008); https://doi.org/10.1117/12.813252

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