Effects of Sample Handling on Visible and Near-Infrared Soil Reflectance

Author:

McGuirk Savannah L.12ORCID,Cairns Iver H.12,Evans Bradley J.13

Affiliation:

1. CUAVA, ARC Centre for CubeSats, UAVs, and Their Applications, University of Sydney, Camperdown, NSW, Australia

2. School of Physics, University of Sydney, NSW, Australia

3. Faculty of Science, Agriculture, Business and Law, School of Environment and Rural Science, Department of Ecosystem Management, University of New England, Armidale, NSW, Australia

Abstract

Soil reflectance is a cumulative attribute determined by interactions between light (photons) and the physical, chemical, and biological properties of soil. Soil properties such as organic matter, moisture, mineral oxide contents, soil texture, and surface roughness all influence soil reflectance at unique wavelengths. Many standard sample preparation techniques are designed to alter soil properties, so as to homogenize samples to improve the consistency of reflectance data collected. This study aims to quantify the effects of one standard sample preparation activity, drying, and repeated wetting–drying cycles on visible–near-infrared soil reflectance, by collecting reflectance data from nine samples which were dried then wetted for a total of three times. This study demonstrates the major, permanent effects of a drying and wetting cycle on soil reflectance, and then presents a model which can be used to correct for these effects. These results have direct implications for remote sensing activities, soil libraries, and soil spectral libraries. These results show that without correction, data from soil spectral libraries, spectral data collected from stored samples, and spectral data transferred between studies, have limited utility for characterizing soils as they exist in the field. Soil spectral data collected in the lab requires correction before it may be used to predict soil properties in the field, as standard sample handling procedures change intrinsic soil properties and introduce systematic error into these data.

Funder

Australian Research Council

Publisher

SAGE Publications

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