Monitoring and predicting the influences of land use/land cover change on cropland characteristics and drought severity using remote sensing techniques

The Federal University of Technology at Akure (FUTA) in Nigeria is experiencing ongoing development that is leading to the replacement of agricultural and forestry land cover types. This study aimed to assess and predict changes in land use/land cover (LULC) types and their impact on crop characteristics in 17 plots of FUTA from 1991 to 2031. Crop characteristics were evaluated using the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), normalized difference moisture index (NDMI), vegetation condition index (VCI), watershed delineation, and spectral characteristics using Landsat imageries. The land change modeler in TerraSet software was used to predict future LULC scenarios. Results showed an increase in built-up areas (15%) and bare land areas (14%), but a reduction of 19% in light vegetation cover from 1991 to 2021. The predicted LULC map illustrated a decrease in light vegetation area (11%) and an increase in built-up area (19%) from 1991 to 2031. NDVI values denoting vegetation health and coverage extent, and NDWI & NDMI values indicating water stress in vegetation and soil showed that palm tree (Plot 1) had the highest average indices values (0.31, 0.34, and 0.06, respectively), while mixed cropping of cassava, cashew, and potatoes (Plot 6) had the lowest average indices values (0.23, 0.28, and −0.029 respectively). This indicates that Plot 1 (palm tree) had better vegetation health with higher green canopy coverage and lower water stress in vegetation and soil compared to Plot 6 (cassava, cashew, and mixed potato vegetation). Drought analysis (VCI) showed that light drought areas became severe drought areas during 2001–2021 in Plots 4 and 6. The reduction of green cover and growing built-up areas accelerated the increase in drought severity. This study advocates for sustainable land use management to manage water stress and drought at the field level.