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      Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data

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          Abstract

          Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution ( i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite’s Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds.

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          Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas

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            Sentinels for science: Potential of Sentinel-1, -2, and -3 missions for scientific observations of ocean, cryosphere, and land

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

              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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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                11 September 2015
                September 2015
                : 15
                : 9
                : 22956-22969
                Affiliations
                [1 ]Balaton Limnological Institute, Centre for Ecological Research, Hungarian Academy of Sciences, Klebelsberg Kuno u. 3., Tihany, H-8237, Hungary; E-Mails: zlinszky.andras@ 123456okologia.mta.hu (A.Z.); toth.viktor@ 123456okologia.mta.hu (V.R.T.)
                [2 ]University of Leicester, Centre for Landscape and Climate Research, Bennett Building, University Road, Leicester, LE1 7RH, UK; E-Mail: hb91@ 123456leicester.ac.uk
                [3 ]National Observatory of Athens, Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, Metaxa and Vas. Pavlou Str., Penteli, Athens GR-15236, Greece; E-Mail: sykioti@ 123456noa.gr
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: dimitris.stratoulias@ 123456gmail.com ; Tel.: +31-53-489-37-71; Fax: +31-53-487-44-00.
                Article
                sensors-15-22956
                10.3390/s150922956
                4610485
                26378538
                71011efd-2ca2-48a5-9c0a-240f72151318
                © 2015 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/4.0/).

                History
                : 31 July 2015
                : 01 September 2015
                Categories
                Article

                Biomedical engineering
                sentinel-2,simulation,hyperspectral,spectral response function,phragmites,macrophytes,lakeshore vegetation,habitat mapping

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