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Proceedings Paper

Using spectroscopy and satellite imagery to assess the total iron content of soils in the Judean Desert (Israel)
Author(s): T. Jarmer
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Paper Abstract

Reflectance measurements have been convex-hull-normalized to derive individual absorption features and the continuous spectra were used to calculate color parameters according to the Commission Internationale de l'Eclairage (CIE) color scheme. Subsequently, derived parameters of the convex hull normalized iron absorption band in the near infrared around 0.9 μm and the CIE-chromaticity coordinates were tested for their significance to predict the total iron content. Accordingly, a method for spectral detection of total iron content was generated based on statistical analysis which allows the prediction of the soils total iron content of the investigated soils with a cross-validated r2 above 0.8. Since C.I.E. color coordinates were found to be well suitable parameters for predicting total iron content of soils under laboratory conditions, the reflectance values of the Landsat-TM bands were transformed into C.I.E. color coordinates. Subsequently, the C.I.E. based model approach was adopted to a Landsat image with low vegetation cover from July 1998 to predict spatial distribution of the soils total iron content. The transfer of the regression model to the satellite image allowed for prediction of the total iron content. Concentrations obtained from the satellite image are in accordance with the concentration range of the chemical analysis. The predicted total iron concentrations reflect the geographic conditions and show a dependence on the annual rainfall amount. A general trend to decreasing concentrations of total iron can be stated with increasing aridity. Furthermore, local conditions are well reflected by the predicted concentrations.

Paper Details

Date Published: 19 October 2012
PDF: 8 pages
Proc. SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 853129 (19 October 2012); doi: 10.1117/12.970492
Show Author Affiliations
T. Jarmer, Univ. of Osnabrück (Germany)


Published in SPIE Proceedings Vol. 8531:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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