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Remote Sens. 2015, 7(9), 11776-11800; doi:10.3390/rs70911776

Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling

1
Department of Global Change Ecology, University of Bayreuth, Bayreuth 95440, Germany
2
German Remote Sensing Data Center, Oberpfaffenhofen D-82234, Germany
3
Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB T6G 2E3, Canada
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Saskia Foerster, Véronique Carrere, Michael Rast, Karl Staenz, Ioannis Gitas and Prasad S. Thenkabail
Received: 29 May 2015 / Revised: 7 September 2015 / Accepted: 8 September 2015 / Published: 15 September 2015
View Full-Text   |   Download PDF [26324 KB, uploaded 15 September 2015]   |  

Abstract

Soil erosion can be linked to relative fractional cover of photosynthetic-active vegetation (PV), non-photosynthetic-active vegetation (NPV) and bare soil (BS), which can be integrated into erosion models as the cover-management C-factor. This study investigates the capability of EnMAP imagery to map fractional cover in a region near San Jose, Costa Rica, characterized by spatially extensive coffee plantations and grazing in a mountainous terrain. Simulated EnMAP imagery is based on airborne hyperspectral HyMap data. Fractional cover estimates are derived in an automated fashion by extracting image endmembers to be used with a Multiple End-member Spectral Mixture Analysis approach. The C-factor is calculated based on the fractional cover estimates determined independently for EnMAP and HyMap. Results demonstrate that with EnMAP imagery it is possible to extract quality endmember classes with important spectral features related to PV, NPV and soil, and be able to estimate relative cover fractions. This spectral information is critical to separate BS and NPV which greatly can impact the C-factor derivation. From a regional perspective, we can use EnMAP to provide good fractional cover estimates that can be integrated into soil erosion modeling. View Full-Text
Keywords: EnMAP; imaging spectroscopy; spectral mixture analysis; soil erosion modeling; Costa Rica EnMAP; imaging spectroscopy; spectral mixture analysis; soil erosion modeling; Costa Rica
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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

Malec, S.; Rogge, D.; Heiden, U.; Sanchez-Azofeifa, A.; Bachmann, M.; Wegmann, M. Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling. Remote Sens. 2015, 7, 11776-11800.

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