| Technology and Methodology |
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The Hyperspectral Remote Sensing Estimation Models of Total Biomass and True LAI of Wheat |
| HOU Xue-hui1,2, NIU Zheng1, HUANG Ni1, XU Shi-guang1 |
1. The State Key Laboratory of Remote Sensing Science, Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China;
2. Graduate University of Chinese Academy of Science, Beijing 100049, China |
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Abstract Based on the spectral first order differential techniques and equivalent MODIS vegetation index according to spectral response function using the field sampling survey, this paper built the hyperspectral remote sensing estimation models for total biomass and LAI of wheat named Jingdong 12. The research shows that: 1the largest correlation between total dry biomass and canopy spectra lies at 552 nm and 721 nm, and the relationship between LAI and canopy spectral is significant in the band range of 400~1 100 nm; 2the relationship between red edge position (REP) and wheat biomass is most significant, with R being 0.818; 3in the 6 vegetation indices similarly to MODIS-VI, EVI is most sensitive to total dry biomass; 4the linear model using REP estimation biomass is the best,with R2 being 0.669 4. Exponential model between LAI and EVI has the strongest fitting degree, with R2 being 0.94. Using field spectral data and band response function to retrieve wheat parameters can provide important research methods for making use of satellite remote sensing data characterized by large area, non-destruction and acquisition of timely ground vegetation information.
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| Keywords
non-coherent decomposition
polarimetric decomposition
scattering mechanism
radar vegetation index
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Issue Date: 13 November 2012
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2012,
Vol. 24
