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Building an exposed soil composite processor (SCMaP) for mapping spatial and temporal characteristics of soils with Landsat imagery (1984-2014)

Rogge, Derek und Bauer, Agnes und Zeidler, Julian und Müller, Andreas und Esch, Thomas und Heiden, Uta (2018) Building an exposed soil composite processor (SCMaP) for mapping spatial and temporal characteristics of soils with Landsat imagery (1984-2014). Remote Sensing of Environment, 205, Seiten 1-17. Elsevier. doi: 10.1016/j.rse.2017.11.004. ISSN 0034-4257.

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Offizielle URL: http://www.sciencedirect.com/science/article/pii/S003442571730514X

Kurzfassung

Abstract Soil information with high spatial and temporal resolution is crucial to assess potential soil degradation and to achieve sustainable productivity and ultimately food security. The spatial resolution of existing soil maps can commonly be too coarse to account for local soil variations and owing to the cost and resource needs required to update information these maps lack temporal information. With improved computational processing capabilities, increased data storage and most recently, the increasing amount of freely available data (e.g. Landsat, Sentinel-2A/B), remote sensing imagery can be integrated into existing soil mapping approaches to increase temporal and spatial resolution of soil information. Satellite multi-temporal data allows for generating cloud-free, radiometrically and phenologically consistent pixel based image composites of regional scale. Such data sets are of particular use for extracting soil information in areas of intermediate climate where soils are rarely exposed. The Soil Composite Mapping Processor (SCMaP) is a new approach designed to make use of per-pixel compositing to overcome the issue of limited soil exposure. The objective of this paper is to demonstrate the automated processors ability to handle large image databases to build multispectral reflectance composite base data layers that can support large scale top soil analyses. The functionality of the 5SCMaP6 is demonstrated using Landsat imagery over Germany from 1984 to 2014 applied over 5 year periods. Three primary product levels are generated that will allow for a long term assessment and distribution of soils that include the distribution of exposed soils, a statistical information related to soil use and intensity and the generation of exposed soil reflectance image composites. The resulting composite maps provide useful value-added information on soils with the exposed soil reflectance composites showing high spatial coverage that correlate well with existing soil maps and the underlying geological structural regions.

elib-URL des Eintrags:https://elib.dlr.de/116026/
Dokumentart:Zeitschriftenbeitrag
Titel:Building an exposed soil composite processor (SCMaP) for mapping spatial and temporal characteristics of soils with Landsat imagery (1984-2014)
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Rogge, Derekderek.rogge (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Bauer, Agnesagnesbauer (at) gmx.netNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Zeidler, Julianjulian.zeidler (at) dlr.dehttps://orcid.org/0000-0001-9444-2296NICHT SPEZIFIZIERT
Müller, Andreasandreas.mueller (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Esch, Thomasthomas.esch (at) dlr.dehttps://orcid.org/0000-0002-5868-9045NICHT SPEZIFIZIERT
Heiden, Utauta.heiden (at) dlr.dehttps://orcid.org/0000-0002-3865-1912NICHT SPEZIFIZIERT
Datum:Februar 2018
Erschienen in:Remote Sensing of Environment
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:205
DOI:10.1016/j.rse.2017.11.004
Seitenbereich:Seiten 1-17
Verlag:Elsevier
ISSN:0034-4257
Status:veröffentlicht
Stichwörter:Soil mapping Image composites Landsat Automated processors
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 - Fernerkundung u. Geoforschung
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Landoberfläche
Hinterlegt von: Zeidler, Julian
Hinterlegt am:27 Nov 2017 10:01
Letzte Änderung:02 Nov 2023 11:58

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