Desertification poses a severe environmental threat in Katsina state, northern Nigeria. While previous studies have assessed desertification in Katsina state and Nigeria, the feature-space technique, which identifies location-specific indicator pairs, remains unexplored. This study conducted a spatio-temporal assessment (1999, 2009, 2024) using Landsat imagery to map desertification degree. Assessment indices for desertification such as albedo, LST, NDVI, SAVI, MSAVI, and MNDWI were derived. Regression analysis was conducted to identify significant negative correlations between albedo or LST and other indices. Results showed the albedo-NDVI pair had the consistent significant negative correlation (r = 0.62, 0.51, 0.63), thus leading to the construction of an albedo-NDVI feature-space and the computation of a Desertification Degree Index (DDI). The DDI classified the area into three levels: desertification, potential desertification, and non-desertification (vegetation/water). The DDI maps indicated that desertification extent increased between 1999 and 2009 but declined slightly by 2024, while potential desertification expanded continuously with 40.37%, 41.44% and 47.33% in 1999, 2009 and 2024 respectively. Non-desertification extent (vegetation) decreased steadily, reflecting increasing anthropogenic and climatic pressures. Expansion rate analysis showed that potential desertification is the fastest-growing class at 0.69% per annum, thus highlighting its role as a precursor to full desertification. The DDI maps were robustly validated using Soil Organic Carbon, which demonstrated moderate but significant negative correlations (r = 0.51, 0.593, 0.563 for 1999, 2009, 2024), thus confirming the ecological relevance of the DDI. The feature-space technique is effective in that it has provided strong correlated indicators that are location-based to the study area.
Aliyu et al. (Wed,) studied this question.