<![CDATA[Tree planting is a proven strategy for climate resilience, contributing to carbon sequestration, air quality improvement, and urban heat mitigation. However, conventional approaches often lack precision and scalability. This study proposes a novel integrated framework that combines Geographic Information Systems (GIS), Internet of Things (IoT) sensors, remote sensing (Sentinel-1 and Sentinel-2), and artificial intelligence (AI) to optimize urban forestry. Unlike previous research that treats these technologies separately, our approach fuses multi-source spatial data, real-time IoT monitoring, and AI-driven predictive analytics for evidence-based decision-making. Pilot projects in Sukabumi and Bogor (Indonesia) validate the framework: tree survival rates improved by 20%, urban heat islands were reduced by up to 2°C, and maintenance costs decreased by 10%. These findings demonstrate that geospatial-IoT-AI integration not only strengthens environmental resilience but also delivers measurable economic and social benefits for sustainable urban ecosystems.]]>
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