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A Comparison of Feature-Based MLR and PLS Regression Techniques for the Prediction of Three Soil Constituents in a Degraded South African Ecosystem

Bayer, Anita und Bachmann, Martin und Müller, Andreas und Kaufmann, Hermann (2012) A Comparison of Feature-Based MLR and PLS Regression Techniques for the Prediction of Three Soil Constituents in a Degraded South African Ecosystem. Applied and Environmental Soil Science, 2012, Seiten 1-20. Hindawi Publishing Corporation. DOI: 10.1155/2012/971252.

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Offizielle URL: http://www.hindawi.com/journals/aess/2012/971252/

Kurzfassung

The accurate assessment of selected soil constituents can provide valuable indicators to identify and monitor land changes coupled with degradation which are frequent phenomena in semiarid regions. Two approaches for the quantification of soil organic carbon, iron oxides, and clay content based on field and laboratory spectroscopy of natural surfaces are tested. (1) A physical approach which is based on spectral absorption feature analysis is applied. For every soil constituent, a set of diagnostic spectral features is selected and linked with chemical reference data by multiple linear regression (MLR) techniques. (2) Partial least squares regression (PLS) as an exclusively statistical multivariate method is applied for comparison. Regression models are developed based on extensive ground reference data of 163 sampled sites collected in the Thicket Biome, South Africa, where land changes are observed due to intensive overgrazing. The approaches are assessed upon their prediction performance and significance in regard to a future quantification of soil constituents over large areas using imaging spectroscopy.

Dokumentart:Zeitschriftenbeitrag
Titel:A Comparison of Feature-Based MLR and PLS Regression Techniques for the Prediction of Three Soil Constituents in a Degraded South African Ecosystem
Autoren:
AutorenInstitution oder E-Mail-Adresse der Autoren
Bayer, Anitaanita.bayer@dlr.de
Bachmann, Martinmartin.bachmann@dlr.de
Müller, Andreasandreas.mueller@dlr.de
Kaufmann, Hermanncharly@gfz-potsdam.de
Datum:2012
Erschienen in:Applied and Environmental Soil Science
Referierte Publikation:Ja
In Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Nein
Band:2012
DOI :10.1155/2012/971252
Seitenbereich:Seiten 1-20
Verlag:Hindawi Publishing Corporation
Name der Reihe:Quantitative Soil Spectroscopy
Status:veröffentlicht
Stichwörter:Imaging Spectroscopy, Soil organic carbon, degradation, South Africa, Iron oxides, multiple linear regression analysis, partial least regression analysis
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
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Landoberfläche
Hinterlegt von: Anita Daniela Bayer
Hinterlegt am:28 Nov 2012 10:45
Letzte Änderung:12 Dez 2013 21:50

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