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Proceedings Paper

The impacts of bandwidths on the estimation of leaf chlorophyll concentration using normalized difference vegetation indices
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Paper Abstract

The aim of this work is to estimate leaf chlorophyll concentration with 6 different normalized difference vegetation indices (NDVIs) under 4 bandwidths (1, 5, 10 and 20 nm). A popular leaf radiative transfer model(i.e. PROSPECT) was used to simulate the leaf reflectance spectra from 400-800nm under varying chlorophyll concentrations. Then 6 combinations of bands sensitive to chlorophyll concentrations were chosen for the calculation of their NDVIs. Simulated spectral response functions were applied to calculate the synthesis reflectance spectra at the intervals of 5, 10 and 20 nm respectively, and then corresponding NDVIs were calculated. The change of correlation coefficients between the NDVIs and the leaf chlorophyll concentrations were examined. Results showed that some NDVIs had a good performance with increasing bandwidth, whereas response of different NDVIs to the 4 bandwidths were different generally. Our results suggested that the improvement of spectral resolution was not necessary for some NDVIs to estimate leaf chlorophyll.

Paper Details

Date Published: 8 October 2014
PDF: 7 pages
Proc. SPIE 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI, 922111 (8 October 2014); doi: 10.1117/12.2061290
Show Author Affiliations
Mingliang Ma, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Runhe Shi, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Pudong Liu, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Hong Wang, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Wei Gao, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Colorado State Univ. (United States)


Published in SPIE Proceedings Vol. 9221:
Remote Sensing and Modeling of Ecosystems for Sustainability XI
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

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