Assessment of land degradation using remote sensing approach

Abstract

Land degradation leads to the alteration of ecological and economic functions due to a decrease in the productivity and quality of the land. Land degradation over Minna, Niger State, was assessed using geospatial techniques. Studies between the rainfall and NDVI used on human-induced and climate-induced land degradation were correlated. Landsat imageries on a decadal scale (2000–2019) were processed and classified using a maximum likelihood classifier. NDVI trends are not by rainfall dynamics to human actions. Averagely low, about 24.14%, correlation was found between the observed land degradation and the precipitation factor, yielding more than 50% congruence in degradation induced by human activities. The study discovered that the built-up and bare surfaces are increasing. The long-term changes in built-ups were 96% between 2000 and 2019; conversely, a sharp decrease in vegetative lands at about –19.38%. Based on the terrain analysis, locations have less steep and moderate slopes in the study area due to continuous urban expansion and demographic pressure. Consequentially, over time, available lands not degraded within the study areas would be reduced. The study recommended a proper land management system of land use allocation and land cover activities.

Keywords

• land degradation
• remote sensing and GIS techniques
• rainfall dynamics
• NDVI
• human-induced
• climate-induced and precipitation factor