Remote Sensing and GIS-Based Assessment of Agricultural Suitability in Orlu, Southeastern Nigeria Using Landsat ETM+ Imagery

Abstract

Food insecurity and land degradation remain major environmental and socio-economic challenges across sub-Saharan Africa, with southeastern Nigeria experiencing some of the most severe erosion-related losses of arable land. This study employed integrated remote sensing and GIS techniques to evaluate agricultural suitability within Orlu and its environs using Landsat Enhanced Thematic Mapper Plus (ETM+) imagery and Shuttle Radar Topographic Mission (SRTM) data. Spatial datasets including NDVI, slope gradient, drainage density, lineament density, and terrain elevation were extracted from these sources and integrated within a GIS-based multi-criteria suitability framework. Image enhancement techniques involving band ratios (3/4, 4/2, 3/1, and 5/4) and RGB composites (357, 751, and 752) were employed to improve feature discrimination. NDVI values obtained ranged from –0.22 to 0.51, indicating severe vegetation stress in erosion-prone northeastern sectors and relatively stable vegetative productivity in low-gradient southern terrains. Areas characterised by high lineament density (reaching up to 2.8 km/km²) and steep topographic gradients (>15°) were identified as erosion-prone zones unsuitable for sustainable agriculture. The integrated overlay analysis revealed that 21.1% (163.2 km²) of the study area exhibits high agricultural suitability, 42.5% (328.9 km²) moderate suitability, whereas 36.4% (281.7 km²) remains unsuitable due to steep slopes, high structural lineament density, and extensive land degradation. The study demonstrates that agricultural productivity within the study area is strongly controlled by topography, drainage configuration, vegetation density, and structural lineaments. These findings provide quantifiable baseline information for agricultural land-use planning, erosion mitigation, and sustainable food production strategies in southeastern Nigeria.