Characterization of Soil Degradation from the Cameroonians Shores of Lake Chad Combining Spectral Indexes and Statistics Analysis

Abstract

This article aims to propose a model on the soil degradation risk along the Cameroonian shores of Lake Chad based on the statistical analysis of spectral indexes of Sentinel 2A satellite images. A total of four vegetation indexes such as the Greenness Index and Disease water stress index and nine soil indexes such as moisture, brightness, or organic matter content are computed and combined to characterize vegetation cover and bare soil state, respectively. All these indexes are aggregated to produce one image (independent variable) and then regressed by individual indexes (dependent variable) to retrieve correlation and determination coefficients. Principal Component Analysis and factorial analysis are applied to all spectral indexes to summarize information, obtain factorial coordinates, and detect positive/negative correlation. The first factor contains soil information, whereas the second factor focuses on vegetation information. The final equation of the model is obtained by weighting each index with both its coefficient of determination and factorial coordinates. This result generated figures' cartography of five classes of soils potentially exposed to the risk of soil degradation. Five levels of exposition risk are obtained from the "Lower" level to the "Higher": the "Lower" and "Moderate to low" levels occupy, respectively, 25,214.35 hectares and 130,717.19 hectares; the "Moderate" level spreads 137,404.34 hectares; the "High to moderate" and "Higher" levels correspond, respectively, to 152,371.91 hectares and 29,175.73 hectares.