Abstract
The accurate assessment of selected soil constituents can provide valuable indicators to identify and monitor land changes coupled with degradation which are frequent phenomena in semiarid regions. Two approaches for the quantification of soil organic carbon, iron oxides, and clay content based on field and laboratory spectroscopy of natural surfaces are tested. (1) A physical approach which is based on spectral absorption feature analysis is applied. For every soil constituent, a set of diagnostic spectral features is selected and linked with chemical reference data by multiple linear regression (MLR) techniques. (2) Partial least squares regression (PLS) as an exclusively statistical multivariate method is applied for comparison. Regression models are developed based on extensive ground reference data of 163 sampled sites collected in the Thicket Biome, South Africa, where land changes are observed due to intensive overgrazing. The approaches are assessed upon their prediction performance and significance in regard to a future quantification of soil constituents over large areas using imaging spectroscopy.
Highlights
The soil as upper layer of the Earth’s surface is the most important layer for energy and nutrition flows necessary for the development of vegetation and of key importance for landscape analysis
Approach A: Multiple Linear Regression of Spectral Feature Parameters. This approach applies a set of spectral features, found in previous literature to be characteristic for soil organic carbon, iron oxides, and clay content for subsequent multiple linear regression analysis
The ratio of performance to deviation (RPD) is defined as the ratio of the standard deviation of the reference samples divided by the root mean square error (RMS)
Summary
The soil as upper layer of the Earth’s surface is the most important layer for energy and nutrition flows necessary for the development of vegetation and of key importance for landscape analysis. The characterization of an ecosystem’s soil condition and its spatial and temporal changes are vital indicators for soil health and in agricultural ecosystems directly linked to crop production. Land cover changes coupled with degradation and soil erosion are frequent phenomena which may be the result of long-term management practices or may be linked to climate change. In the semiarid subtropical Thicket Biome as part of the Eastern Cape Province of South Africa, land changes are observed due to decades of overgrazing by goats. This has caused the unique ecosystem to change from dense shrubland with a high rate of carbon sequestration in vegetation and peripheral soils to an open savannah-like system. A mapping of their spatial distribution and temporal development is limited using conventional soil analyses since this would require intensive sampling and analysis efforts
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