[en] Soil Organic Carbon (SOC) is one of the key soil properties, but the large spatial variation makes continuous mapping a complex task. Imaging spectroscopy has proven to be an useful technique for mapping of soil properties, but the applicability decreases rapidly when fields are partially covered with vegetation. In this paper we show that with only a few percent fractional maize cover the accuracy of a Partial Least Square Regression (PLSR) based SOC prediction model drops dramatically. However, this problem can be solved with the use of spectral unmixing techniques. First, the fractional maize cover is determined with linear spectral unmixing, taking the illumination and observation angles into account. In a next step the influence of maize is filtered out from the spectral signal by a new procedure termed Residual Spectral Unmixing (RSU). The residual soil spectra resulting from this procedure are used for mapping of SOC using PLSR, which could be done with accuracies comparable to studies performed on bare soil surfaces (Root Mean Standard Error of Calibration = 1.34 g/kg and Root Mean Standard Error of Prediction = 1.65 g/kg). With the presented RSU approach it is possible to filter out the influence of maize from the mixed spectra, and the residual soil spectra contain enough information for mapping of the SOC distribution within agricultural fields. This can improve the applicability of airborne imaging spectroscopy for soil studies in temperate climates, since the use of the RSU approach can extend the flight-window which is often constrained by the presence of vegetation.
Disciplines :
Agriculture & agronomy
Author, co-author :
Bartholomeus, Harm
Kooistra, Lammert
Stevens, Antoine
van Leeuwen, Martin
van Wesemael, Bas
Ben-Dor, Eyal
Tychon, Bernard ; Université de Liège - ULiège > Département des sciences et gestion de l'environnement > Département des sciences et gestion de l'environnement
Language :
English
Title :
Soil Organic Carbon mapping of partially vegetated agricultural fields with imaging spectroscopy
Publication date :
February 2011
Journal title :
International Journal of Applied Earth Observation and Geoinformation
ISSN :
1569-8432
eISSN :
1872-826X
Publisher :
Elsevier Science, Amsterdam, Netherlands
Volume :
13
Issue :
1
Pages :
81-88
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
BELSPO - SPP Politique scientifique - Service Public Fédéral de Programmation Politique scientifique
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