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Remote Sens. 2016, 8(11), 947; doi:10.3390/rs8110947

Development of a New BRDF-Resistant Vegetation Index for Improving the Estimation of Leaf Area Index

1
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
College of Geometrics, Xi’an University of Science and Technology, Xi’an 710054, China
*
Author to whom correspondence should be addressed.
Academic Editors: Jose Moreno and Prasad S. Thenkabail
Received: 12 August 2016 / Revised: 1 November 2016 / Accepted: 3 November 2016 / Published: 12 November 2016
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Abstract

The leaf area index (LAI) is one of the most important Earth surface parameters used in the modeling of ecosystems and their interaction with climate. Numerous vegetation indices have been developed to estimate the LAI. However, because of the effects of the bi-directional reflectance distribution function (BRDF), most of these vegetation indices are also sensitive to the effect of BRDF. In this study, we aim to present a new BRDF-resistant vegetation index (BRVI), which is sensitive to the LAI but insensitive to the effect of BRDF. Firstly, the BRDF effects of different bands were investigated using both simulated data and in-situ measurements of winter wheat made at different growth stages. We found bi-directional shape similarity in the solar principal plane between the green and the near-infrared (NIR) bands and between the blue and red bands for farmland soil conditions and with medium chlorophyll content level. Secondly, the consistency of the shape of the BRDF across different bands was employed to develop a new BRDF-resistant vegetation index for estimating the LAI. The reflectance ratios of the NIR band to the green band and the blue band to the red band were reasonably assumed to be resistant to the BRDF effects. Nevertheless, the variation amplitude of the bi-directional reflectance in the solar principal plane was different for different bands. The divisors in the two reflectance ratios were improved by combining the reflectances at the red and green bands. The new BRVI was defined as a normalized combination of the two improved reflectance ratios. Finally, the potential of the proposed BRVI for estimation of the LAI was evaluated using both simulated data and in-situ measurements and also compared to other popular vegetation indices. The results showed that the influence of the BRDF on the BRVI was the weakest and that the BRVI retrieved LAI values well, with a coefficient of determination (R2) of 0.84 and an RMSE of 0.83 for the field data and with an R2 of 0.97 and an RMSE of 0.25 for the simulated data. It was concluded, therefore, that the new BRVI is resistant to BRDF effect and is also promising for use in estimating the LAI. View Full-Text
Keywords: bidirectional reflectance distribution function (BRDF); multi-angular; LAI; BRDF-resistant vegetation index (BRVI); vegetation indices bidirectional reflectance distribution function (BRDF); multi-angular; LAI; BRDF-resistant vegetation index (BRVI); vegetation indices
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MDPI and ACS Style

Zhang, S.; Liu, L.; Liu, X.; Liu, Z. Development of a New BRDF-Resistant Vegetation Index for Improving the Estimation of Leaf Area Index. Remote Sens. 2016, 8, 947.

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