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A Comparison of Feature-Based MLR and PLS Regression Techniques for the Prediction of Three Soil Constituents in a Degraded South African Ecosystem

DOI: 10.1155/2012/971252

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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. 1. Introduction 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 thus 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 particularly in agricultural ecosystems directly linked to crop production. In semiarid regions, 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 particular the depletion of carbon inventories in soils is accentuated by soil degradation and erosion [1] and directly causes not only environmental but also economical problems. 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. Chemical and physical soil attributes can serve as tracers to assess and monitor such phenomena. However, a mapping of their spatial distribution and temporal development is limited using conventional soil analyses since this would require intensive sampling and analysis efforts. Despite that, field and imaging spectroscopy

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