Abstract
The Social–Environmental System (SES) framework is crucial in understanding the intricate interplay between human societies and their environmental contexts. Despite its significance, existing SES delineation methods often rely on subjective judgment and struggle with the non-linear, multi-scale nature of SES data, leading to challenges in effective resource management and policymaking. This research addresses these gaps by proposing a novel, reproducible framework for SES boundary delineation that integrates both vector and raster data, utilizing advanced spatial optimization techniques and dimension reduction algorithms like UMAP to manage the non-linear characteristics of SES. The framework also leverages the SKATER algorithm for precise regionalization, ensuring spatial continuity and compactness while allowing user control over region selection and data dimensions. Applied to the Rio Grande/Bravo Basin, this approach demonstrates the practical utility and computational efficiency of the proposed method, offering a scalable solution adaptable to various regions. While focusing on this transboundary area, the study underscores how its framework can be generalized globally for addressing socio-environmental challenges while maintaining flexibility to accommodate local and regional specificities. The framework’s reliance on open-source tools further enhances its accessibility and reproducibility, making it a valuable contribution to SES research and practical environmental management.
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