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This article in SSSAJ

  1. Vol. 72 No. 4, p. 1113-1123
     
    Received: Nov 15, 2007


    * Corresponding author(s): bendor@post.tau.ac.il
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doi:10.2136/sssaj2006.0059

A Novel Method of Classifying Soil Profiles in the Field using Optical Means

  1. Eyal Ben-Dor *,
  2. Daniela Heller and
  3. Alexandra Chudnovsky
  1. Remote Sensing and GIS Lab., Geography and Human Environment Dep., Tel-Aviv Univ., P.O. Box 39040, Ramat Aviv, Tel-Aviv 69978, Israel

Abstract

The rationale of this study was to develop a new, objective method for characterizing soil profiles in the field by using the optical means commonly available to most users. For that purpose, we used a field spectrometer (analytical spectral device, ASD) and a specific accessory used to read subsoil reflectance data, together with a multivariate spectral analysis approach. To that end, we developed and constructed a housing assembly that can be adapted to any portable field spectrometer, thus making subsoil spectral readings possible. This accessory, the sub-surface spectral head device (termed 3S-HeD), penetrates into the subsoil profile after a small hole, the size of the accessory, is drilled in the soil. To examine and demonstrate this idea, we selected and studied four different soil profiles from semiarid environments during the summer. Soil samples were taken from the drilled holes (40), near trenches (30), and a local soil bank (90). All of these samples were mixed together to create a working group against which multivariate spectral models were run, using the spectral and traditional soil laboratory information. The physical and chemical properties examined were soil moisture (SM), soil organic matter (OM), soil carbonates (SC), free iron oxides (Fed), and specific surface area (SSA). Spectra along the profile in the drilled holes were acquired by the 3S-HeD and by a contact probe in nearby trenches and in the soil bank. The models were generated for each property separately by running several spectral manipulations and by applying partial least squares regression (PLSR) analyses. The models' performances were tested against an external fixed group that was selected before the spectral analytical procedure. The 3S-HeD assembly was used to further examine the area of the drilled holes at 10-cm vertical increments. In addition, soil color was extracted from the spectroscopy using several indices and further used to characterize the soil profile. Soil description by the traditional observation methods at nearby trenches and by the proposed optical method were in good agreement. It was concluded that by properly combining information obtained from the field spectrometer, the optical head assembly hooked to the spectrometer, and appropriate multivariate models it is possible to describe quantitatively and objectively the entire soil profile in situ. Importantly, this can be done without opening trenches or sending samples to the laboratory. This work demonstrated an application within four different soil profiles. However, validation of the method over independent locations is still required. Nevertheless, we concluded that the concept presented here can be further employed in developing a robust soil mapping method.

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