Separation of soil and canopy reflectance signatures of Mid German agricultural soils

T. Behrens, K. Gregor and W. Diepenbrock
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T. Behrens: Institute of Agronomy and Crop Science, Martin-Luther-University, Halle-Wittenberg, Germany
K. Gregor: Institute of Agronomy and Crop Science, Martin-Luther-University, Halle-Wittenberg, Germany
W. Diepenbrock: Institute of Agronomy and Crop Science, Martin-Luther-University, Halle-Wittenberg, Germany

Plant, Soil and Environment, 2005, vol. 51, issue 7, 296-303

Abstract: Remote sensing can provide visual indications of crop growth during production season. In past, spectral optical estimations were well performed in the ability to be correlated with crop and soil properties but were not consistent within the whole production season. To better quantify vegetation properties gathered via remote sensing, models of soil reflectance under changing moisture conditions are needed. Signatures of reflected radiation were acquired for several Mid German agricultural soils in laboratory and field experiments. Results were evaluated at near-infrared spectral region at the wavelength of 850 nm. The selected soils represented different soil colors and brightness values reflecting a broad range of soil properties. At the wavelength of 850 nm soil reflectance ranged between 10% (black peat) and 74% (white quartz sand). The reflectance of topsoils varied from 21% to 32%. An interrelation was found between soil brightness rating values and spectral optical reflectance values in form of a linear regression. Increases of soil water content from 0% to 25% decreased signatures of soil reflectance at 850 nm of two different soil types about 40%. The interrelation of soil reflectance and soil moisture revealed a non-linear exponential function. Using knowledge of the individual signature of soil reflectance as well as the soil water content at the measurement, soil reflectance could be predicted. As a result, a clear separation is established between soil reflectance and reflectance of the vegetation cover if the vegetation index is known.

Keywords: near-infrared; reflectance; regression analysis; soil brightness; soil moisture; soil type (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlpse:v:51:y:2005:i:7:id:3589-pse

DOI: 10.17221/3589-PSE

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