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Combining Field and Imaging Spectroscopy to Map Soil Organic Carbon in a Semiarid Environment

Bayer, Anita Daniela und Bachmann, Martin und Rogge, Derek und Müller, Andreas und Kaufmann, Hermann (2016) Combining Field and Imaging Spectroscopy to Map Soil Organic Carbon in a Semiarid Environment. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9 (9), Seiten 3997-4010. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/JSTARS.2016.2585674. ISSN 1939-1404.

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Offizielle URL: http://ieeexplore.ieee.org/document/7533510/

Kurzfassung

Semiarid regions are especially vulnerable to climate change and human-induced land-use changes and are of major importance in the context of necessary carbon sequestration and ongoing land degradation. Topsoil properties, such as soil carbon content, provide valuable indicators to these processes, and can be mapped using imaging spectroscopy (IS). In semiarid regions, this poses difficulties because models are needed that can cope with varying land surface and soil conditions, consider a partial vegetation coverage, and deal with usually low soil organic carbon (SOC) contents. We present an approach that aims at addressing these difficulties by using a combination of field and IS to map SOC in an extensively used semiarid ecosystem. In hyperspectral imagery of the HyMap sensor, the influence of nonsoil materials, i.e., vegetation, on the spectral signature of soil dominated image pixels was reduced and a residual soil signature was calculated. The proposed approach allowed this procedure up to a vegetation coverage of 40% clearly extending the mapping capability. SOC quantities are predicted by applying a spectral feature-based SOC prediction model to image data of residual soil spectra. With this approach, we could significantly increase the spatial extent for which SOC could be predicted with a minimal influence of a vegetation signal compared to previous approaches where the considered area was limited to a maximum of, e.g., 10% vegetation coverage. As a regional example, the approach was applied to a 320 km2 area in the Albany Thicket Biome, South Africa, where land cover and landuse changes have occurred due to decades of unsustainable land management. In the generated maps, spatial SOC patterns were interpreted and linked to geomorphic features and land surface processes, i.e., areas of soil erosion. It was found that the chosen approach supported the extraction of soil-related spectral image information in the semiarid region with highly varying land cover. However, the quantitative prediction of SOC contents revealed a lack in absolute accuracy.

elib-URL des Eintrags:https://elib.dlr.de/105812/
Dokumentart:Zeitschriftenbeitrag
Titel:Combining Field and Imaging Spectroscopy to Map Soil Organic Carbon in a Semiarid Environment
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Bayer, Anita DanielaAnita.Bayer (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Bachmann, MartinMartin.Bachmann (at) dlr.dehttps://orcid.org/0000-0001-8381-7662NICHT SPEZIFIZIERT
Rogge, Derekderek.rogge (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Müller, Andreasandreas.mueller (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Kaufmann, HermannGFZ PotsdamNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:August 2016
Erschienen in:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:9
DOI:10.1109/JSTARS.2016.2585674
Seitenbereich:Seiten 3997-4010
Verlag:IEEE - Institute of Electrical and Electronics Engineers
ISSN:1939-1404
Status:veröffentlicht
Stichwörter:Imaging spectroscopy (IS), land degradation, linear spectral unmixing, multiple linear regression analysis, soil organic carbon
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Vorhaben Fernerkundung der Landoberfläche (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Landoberfläche
Hinterlegt von: Rogge, Derek
Hinterlegt am:14 Nov 2016 12:46
Letzte Änderung:03 Nov 2023 07:36

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