SSSAJ Journal of Natural Resources and Life Sciences Education
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Soil Science Society of America Journal 67:289-299 (2003)
© 2003 Soil Science Society of America

DIVISION S-6—SOIL & WATER MANAGEMENT & CONSERVATION

The Spectral Reflectance Properties of Soil Structural Crusts in the 1.2- to 2.5-µm Spectral Region

E. Ben-Dor*,a, N. Goldlshlegerb, Y. Benyaminib, M. Agassib and D. G. Blumbergc

a The Remote Sensing and GIS Laboratory, The Geography and Human Environment Dep., Tel-Aviv University, P.O. Box 39040 Ramat Aviv Tel-Aviv 69978 Israel
b Erosion Research Station, Soil Conservation and Drainage Division, Ministry of Agriculture, Israel
c Dep. of Geography and Environmental Development, Ben-Gurion University of the Negev, Israel

* Corresponding author (bendor{at}post.tau.ac.il)

A controlled investigation of the spectral signature of soil's structural crust in the 1.2- to 2.5-µm spectral region was conducted to investigate the feasibility of accounting for the crust status solely from the spectral information. This research was conducted because there is no valid method for in situ assessment of soil-crust characteristics in agricultural fields while and after the crust is formed. Through the use of a laboratory rainfall simulator and a sensitive spectrometer, we showed that significant spectral differences occurred between the crust and the bulk soil for three selected soils from Israel. The study was divided into two parts: Part 1, in which qualitative observations of the three soils were conducted under one level of rainstorm energy, and Part 2, where a selected soil was further investigated under varying levels of rain energy. The spectral differences obtained for the crusted soil are related to the texture and mineralogy of the soil's surface. It was concluded that the relationship between structural crust and soil reflectance spectroscopy can be used as a tool for estimating soil properties governed by the physical crust formation, such as infiltration rate, soil runoff, and erosion. It was further suggested that this methodology be tested within a remote sensing domain, using field, air, or spaceborne hyperspectral sensors.

Abbreviations: IR, infrared • NIR, near infrared • SEP, standard error of prediciton • SWIR, short wave infrared • VIS, visible




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