A new soil degradation method analysis by Sentinel 2 images combining spectral indices and statistics analysis: application to the Cameroonians shores of Lake Chad and its hinterland

International audienceThis paper aims to model the soil degradation risk along the Cameroonian shores of Lake Chad. The processing is based on a statistical analysis of spectral indices of sentinel 2A satellite images. A total of four vegetation indices such as the Greenness Index and Disease water stress index and nine soil indices such as moisture, brightness, or organic matter content are computed and combined to characterize vegetation cover and bare soil state, respectively. All these indices are aggregated to produce one image (independent variable) and then regressed by individual indices (dependent variable) to retrieve correlation and determination coefficients. Principal Component Analysis and factorial analysis are applied to all spectral indices 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 factorials 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 "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