Integrating Remote Sensing and MOLUSCE to Map and Predict Land Degradation in Baton Rouge

Abstract. Land degradation, driven primarily by deforestation and urbanization, presents a growing threat to ecological integrity and sustainable development, particularly in rapidly urbanizing regions. This study analyzes historical land use and land cover (LULC) changes from 1994 to 2024 in East Baton Rouge Parish, Louisiana, and projects future trends up to 2054 using the Modules for Land Use Change Simulations (MOLUSCE) plugin in QGIS. Utilizing Landsat satellite imagery, Random Forest classification, and neural network-based predictive modeling, the study categorizes LULC into closed forest, open forest, built-up areas, and water bodies. Key findings reveal significant land degradation (~19%) between 1994 and 2024, primarily driven by forest conversion to urban areas. However, the projection for 2024–2054 indicates a trend toward stabilization, with a slight increase in closed forest cover (+12.45 million m²) and minimal urban expansion (+0.3%). The research highlights the urgency of proactive land-use planning, reforestation policies, and improved modeling techniques to mitigate long-term degradation. These insights provide vital guidance for policymakers, urban planners, and environmental stakeholders aiming to balance development and conservation in the Baton Rouge metropolitan region.