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      Evaluation of Sentinel-2 Red-Edge Bands for Empirical Estimation of Green LAI and Chlorophyll Content

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          Abstract

          ESA’s upcoming satellite Sentinel-2 will provide Earth images of high spatial, spectral and temporal resolution and aims to ensure continuity for Landsat and SPOT observations. In comparison to the latter sensors, Sentinel-2 incorporates three new spectral bands in the red-edge region, which are centered at 705, 740 and 783 nm. This study addresses the importance of these new bands for the retrieval and monitoring of two important biophysical parameters: green leaf area index (LAI) and chlorophyll content (Ch). With data from several ESA field campaigns over agricultural sites (SPARC, AgriSAR, CEFLES2) we have evaluated the efficacy of two empirical methods that specifically make use of the new Sentinel-2 bands. First, it was shown that LAI can be derived from a generic normalized difference index (NDI) using hyperspectral data, with 674 nm with 712 nm as best performing bands. These bands are positioned closely to the Sentinel-2 B4 (665 nm) and the new red-edge B5 (705 nm) band. The method has been applied to simulated Sentinel-2 data. The resulting green LAI map was validated against field data of various crop types, thereby spanning a LAI between 0 and 6, and yielded a RMSE of 0.6. Second, the recently developed “Normalized Area Over reflectance Curve” (NAOC), an index that derives Ch from hyperspectral data, was studied on its compatibility with simulated Sentinel-2 data. This index integrates the reflectance curve between 643 and 795 nm, thereby including the new Sentinel-2 bands in the red-edge region. We found that these new bands significantly improve the accuracy of Ch estimation. Both methods emphasize the importance of red-edge bands for operational estimation of biophysical parameters from Sentinel-2.

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          Models of vegetation canopy reflectance and their use in estimation of biophysical parameters from reflectance data

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            Remote Estimation of Crop Chlorophyll Content Using Spectral Indices Derived From Hyperspectral Data

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              Detection of Vegetation Stress Via a New High Resolution Fluorescence Imaging System

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel, Switzerland)
                Molecular Diversity Preservation International (MDPI)
                1424-8220
                2011
                8 July 2011
                : 11
                : 7
                : 7063-7081
                Affiliations
                Department of Earth Physics and Thermodynamics, Image Processing Laboratory, Universidad de Valencia, P.O. Box 22085, Paterna E-46071,Valencia, Spain; E-Mails: jochem.verrelst@ 123456uv.es (J.V.); luis.alonso@ 123456uv.es (L.A.); jose.moreno@ 123456uv.es (J.M.)
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: delegido@ 123456uv.es ; Tel.: +34-963-544-068; Fax: +34-963-543-261.
                Article
                sensors-11-07063
                10.3390/s110707063
                3231680
                22164004
                0e0c50df-5989-43ec-9a6c-ed90e78287e3
                © 2011 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                : 15 May 2011
                : 1 July 2011
                : 2 July 2011
                Categories
                Article

                Biomedical engineering
                sentinel-2,red-edge,lai,naoc,ndi,chlorophyll
                Biomedical engineering
                sentinel-2, red-edge, lai, naoc, ndi, chlorophyll

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