Advancing geospatial methods for addressing global resource and sustainability challenges

Rising demands on global resources and ecosystems require advanced geospatial methods to support monitoring, modeling, and sustainable management. However, challenges remain in integrating remote sensing, environmental process models, machine learning, spatial statistics, and hybrid systems to capture nonlinear processes and multi-scale interactions. The Special Issue on “Advancing geospatial methods for sustainable resource management” presents recent studies addressing biodiversity conservation, carbon and land use, urban material flows, waste monitoring, and supply chain equity. This editorial introduces a structured framework that connects geospatial methods from data acquisition to complex system modeling to five key resource and sustainability challenges. The framework identifies new directions for methodological innovation, multi-source data integration, and interdisciplinary applications that inform policy and advance circular economy transitions. Strengthening geospatial integration through advanced methods and cross-sector collaboration remains essential for effective sustainable resource management within complex socio-ecological systems.