Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling
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 ma...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2015-09-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | http://www.mdpi.com/2072-4292/7/9/11776 |
id |
doaj-366928ccaa92477ca20b782cfcb6a90f |
---|---|
record_format |
Article |
spelling |
doaj-366928ccaa92477ca20b782cfcb6a90f2020-11-25T00:53:37ZengMDPI AGRemote Sensing2072-42922015-09-0179117761180010.3390/rs70911776rs70911776Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion ModelingSarah Malec0Derek Rogge1Uta Heiden2Arturo Sanchez-Azofeifa3Martin Bachmann4Martin Wegmann5Department of Global Change Ecology, University of Bayreuth, Bayreuth 95440, GermanyGerman Remote Sensing Data Center, Oberpfaffenhofen D-82234, GermanyGerman Remote Sensing Data Center, Oberpfaffenhofen D-82234, GermanyDepartment of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB T6G 2E3, CanadaGerman Remote Sensing Data Center, Oberpfaffenhofen D-82234, GermanyDepartment of Global Change Ecology, University of Bayreuth, Bayreuth 95440, GermanySoil 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.http://www.mdpi.com/2072-4292/7/9/11776EnMAPimaging spectroscopyspectral mixture analysissoil erosion modelingCosta Rica |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sarah Malec Derek Rogge Uta Heiden Arturo Sanchez-Azofeifa Martin Bachmann Martin Wegmann |
spellingShingle |
Sarah Malec Derek Rogge Uta Heiden Arturo Sanchez-Azofeifa Martin Bachmann Martin Wegmann Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling Remote Sensing EnMAP imaging spectroscopy spectral mixture analysis soil erosion modeling Costa Rica |
author_facet |
Sarah Malec Derek Rogge Uta Heiden Arturo Sanchez-Azofeifa Martin Bachmann Martin Wegmann |
author_sort |
Sarah Malec |
title |
Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling |
title_short |
Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling |
title_full |
Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling |
title_fullStr |
Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling |
title_full_unstemmed |
Capability of Spaceborne Hyperspectral EnMAP Mission for Mapping Fractional Cover for Soil Erosion Modeling |
title_sort |
capability of spaceborne hyperspectral enmap mission for mapping fractional cover for soil erosion modeling |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2015-09-01 |
description |
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. |
topic |
EnMAP imaging spectroscopy spectral mixture analysis soil erosion modeling Costa Rica |
url |
http://www.mdpi.com/2072-4292/7/9/11776 |
work_keys_str_mv |
AT sarahmalec capabilityofspacebornehyperspectralenmapmissionformappingfractionalcoverforsoilerosionmodeling AT derekrogge capabilityofspacebornehyperspectralenmapmissionformappingfractionalcoverforsoilerosionmodeling AT utaheiden capabilityofspacebornehyperspectralenmapmissionformappingfractionalcoverforsoilerosionmodeling AT arturosanchezazofeifa capabilityofspacebornehyperspectralenmapmissionformappingfractionalcoverforsoilerosionmodeling AT martinbachmann capabilityofspacebornehyperspectralenmapmissionformappingfractionalcoverforsoilerosionmodeling AT martinwegmann capabilityofspacebornehyperspectralenmapmissionformappingfractionalcoverforsoilerosionmodeling |
_version_ |
1725237436567519232 |