Spatiotemporal analysis and modeling of land use and land cover change in Fiche Town, Central Ethiopia using geospatial techniques and MOLUSCE

Rapid urban expansion driven by population growth and socio-economic transformation has significantly altered Land Use/Land Cover (LULC) patterns, particularly in rapidly growing urban centers of developing countries. Understanding historical and future LULC dynamics is essential for promoting sustainable urban development and safeguarding surrounding agricultural resources. This study analyzed and modeled the spatiotemporal dynamics of Land use land cover change in Fiche Town, Central Ethiopia, from 2002 to 2022 and projected future scenarios for 2030, 2040, and 2050 using geospatial techniques and the MOLUSCE model. Multi-temporal satellite imagery from Landsat 7 ETM+ (2002) and Landsat 8 OLI/TIRS (2013 and 2022) was used for LULC classification. A Support Vector Machine (SVM)-based supervised classification approach was implemented in ENVI software, and classification accuracy was assessed using a confusion matrix. Spatial transition analysis was conducted using the Land Change Modeler (LCM) and the MOLUSCE plugin in QGIS. Future LULC changes were predicted using an Artificial Neural Network (ANN)-based Multi-Layer Perceptron (MLP) model trained with historical LULC maps and spatial driving factors, including Digital Elevation Model (DEM), slope, aspect, and proximity to roads. Validation of the simulated 2022 LULC map against the observed 2022 map demonstrated strong predictive performance, with an overall Kappa coefficient of 0.83 and a correctness rate of 88.8%. The results revealed substantial expansion of built-up areas, which increased from 10.43% in 2002 to 16.92% in 2013 and 25.76% in 2022. In contrast, agricultural land declined from 66.40% in 2002 to 54.93% in 2013 and further to 36.41% in 2022. Future projections indicate that built-up areas will continue to expand, reaching 29.76% in 2030, 32.31% in 2040, and 35.74% in 2050, while agricultural land is projected to decline to 29.74%, 26.56%, and 22.01%, respectively. The findings demonstrate that rapid urban growth in Fiche Town is occurring at the expense of agricultural land, posing significant challenges to environmental sustainability and local livelihoods. This study provides a robust spatial and empirical framework for policymakers, urban planners, and other stakeholders to support sustainable land-use planning and resource management strategies aimed at mitigating the loss of critical agricultural and natural resources in rapidly urbanizing Ethiopian towns.