SPATIO-TEMPORAL ASSESSMENT OF LAND USE AND LAND COVER CHANGES AND THEIR IMPACTS ON LAND SUITABILITY FOR MAIZE PRODUCTION IN FEDERAL UNIVERSITY OF AGRICULTURE ABEOKUTA, OGUN STATE, NIGERIA
Keywords:Land use, Markov-chain, GIS-parametric, Maize-suitability, Remote sensing
The main causes of land-use change are rooted in the spatiotemporal interaction between biophysical and human activities. This study identified the impacts of land use and land cover changes (LULCCs) on land suitability for the years 2000, 2010, and 2020, using Landsat satellite images. Soil samples were collected and analyzed at 0-30 cm soil depth. Principal component analysis and parametric methods were performed on the soil properties to identify suitable areas for maize production. The Markov Chain (MC) and Cellular Automata (CA) methods were utilized to simulate the LULC maps for the year 2030. The accuracy of LULC simulation models is more than 85% based on the validation results. The results of the LULCCs indicated that built-up and farmland increased by 86.99% and 7.07%, and vegetation, grassland and waterbodies decreased by 5.30%, 0.53% and 0.09% respectively. Comparing the results of the three parametric methods used showed that the Rabia equation gave higher suitability index values than the Stories and Square root methods. Multicriteria analysis of the land suitability revealed that most of the study area was marginally not suitable at 6915.4 ha (69.1%), and marginally suitable at 2598.5 ha (26%) while only a very small part of the land was moderately suitable at 298.4 ha (3.0%) and highly suitable 187.8 ha (1.9%) for maize production. The main limiting factors were slope, rainfall, temperature and erosion hazard. Thus, modelling and simulating LULCCs using the CA-Markov model plays a significant role in land use policymaking, planning and ensuring sustainable land suitability.