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Understanding the patterns of land degradation indicators can help to identify areas under threat as basis for designing and implementing site-specific management options. This study sort to identify and assess the patterns of land degradation indicators in selected districts of western Kenya. The study employed the use of Land Degradation Sampling Framework (LDSF) to characterize the sites. LDSF a spatially stratified, random sampling design framework consisting of 10km×10km blocks and clusters of plots. The study broadly identified and classified the indicators and attributes of land degradation into soil and site stability, hydrologic function and biotic integrity. Assessment of general vegetation structure showed that over 70% of the land was under cropland with forests accounting for 8% of the area. Sheet erosion was the major form of soil loss. High variability was observed for the soil properties and this can be due to both inherent soil characteristics as well as land management practices. There was distinct variation in the soil properties between the topsoil (0–20cm) and the subsoil (20–30cm) with the topsoil having higher values for most of the parameters compared to the subsoil. Using coefficient of variation (CV) as criteria for expressing variability, Ca, TON, Mg, SOC and silt were most variable soil properties for the 0–20cm depth. Moderate variability (CV 0.15–0.35) was observed for CEC, P, K and clay while Na, Sand and pH had the least variability (CV
