Publication

Abstract : In an era where rapid urbanization and environmental degradation often clash, balancing development with ecological preservation has become a critical challenge. This work presents a practical framework for optimizing decisions around deforestation, with afforestation serving as a vital complement to maintain ecological stability. The model uses straightforward algorithms and real-time data to evaluate the connections between tree cover, air quality, and pollution levels. By analyzing spatial data on plant species distributions and pollution trends, the framework employs clustering techniques like DBSCAN and decision-making methods such as AHP and TOPSIS to identify deforestation zones that would minimize environmental harm. Results show a significant improvement in air quality with selected regions experiencing a 31.1% increase in AQI compared to the average. Additionally, the framework highlights the importance of afforestation in restoring lost tree cover and reducing the long-term ecological impact of deforestation. By harnessing real-time data and insights on tree species and their distribution, this model offers a clear pathway toward cleaner air, healthier ecosystems, and sustainable development. This approach offers actionable insights into sustainable land management.