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Remote Sens. 2015, 7(11), 15361-15387; doi:10.3390/rs71115361

Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale

1
Geoinformation in Environmental Planning Lab, Technische Universität Berlin, Straße des 17. Juni 145, D-10623 Berlin, Germany
2
Helmholz Centre Potsdam-GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
3
Division of Forest, Nature and Landscape, Department of Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200E, BE-3001 Leuven, Belgium
4
Geomatics Lab, Department of Biosystems, KU Leuven, Willem de Croylaan 34, BE-3001 Leuven, Belgium
5
Department of Compuational Landscape Ecology, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, D-04318 Leipzig, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Karl Staenz, Saskia Foerster, Véronique Carrere, Michael Rast, Clement Atzberger and Prasad S. Thenkabail
Received: 3 July 2015 / Revised: 5 November 2015 / Accepted: 9 November 2015 / Published: 18 November 2015
View Full-Text   |   Download PDF [3712 KB, uploaded 25 November 2015]   |  

Abstract

Forest biochemical and biophysical variables and their spatial and temporal distribution are essential inputs to process-orientated ecosystem models. To provide this information, imaging spectroscopy appears to be a promising tool. In this context, the present study investigates the potential of spectral unmixing to derive sub-pixel crown component fractions in a temperate deciduous forest ecosystem. However, the high proportion of foliage in this complex vegetation structure leads to the problem of saturation effects, when applying broadband vegetation indices. This study illustrates that multiple endmember spectral mixture analysis (MESMA) can contribute to overcoming this challenge. Reference fractional abundances, as well as spectral measurements of the canopy components, could be precisely determined from a crane measurement platform situated in a deciduous forest in North-East Germany. In contrast to most other studies, which only use leaf and soil endmembers, this experimental setup allowed for the inclusion of a bark endmember for the unmixing of components within the canopy. This study demonstrates that the inclusion of additional endmembers markedly improves the accuracy. A mean absolute error of 7.9% could be achieved for the fractional occurrence of the leaf endmember and 5.9% for the bark endmember. In order to evaluate the results of this field-based study for airborne and satellite-based remote sensing applications, a transfer to Airborne Imaging Spectrometer for Applications (AISA) and simulated Environmental Mapping and Analysis Program (EnMAP) and Sentinel-2 imagery was carried out. All sensors were capable of unmixing crown components with a mean absolute error ranging between 3% and 21%. View Full-Text
Keywords: MESMA; forest; endmembers; bark; NDVI; upscaling; EnMAP; Sentinel-2 MESMA; forest; endmembers; bark; NDVI; upscaling; EnMAP; Sentinel-2
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Clasen, A.; Somers, B.; Pipkins, K.; Tits, L.; Segl, K.; Brell, M.; Kleinschmit, B.; Spengler, D.; Lausch, A.; Förster, M. Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale. Remote Sens. 2015, 7, 15361-15387.

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