dc.description.abstract | This study investigates the dynamic interplay between environmental services (ES) and human systems across multiple spatial scales, examining the supply of ES by natural ecosystems, the impacts of human actions mediated by socio-political institutions, and their effects on environmental and social subsystems. Emphasizing the pivotal role of these interactions within landscape planning, the research highlights the absence of explicit boundary mapping for fundamental Social-Environmental System (SES) units. To address this gap, a unified, structured framework is introduced, integrating Geographic Information Systems (GIS), dimension reduction, and regionalization techniques to effectively delineate and characterize socio-environmental units. This framework uniquely combines raster and vector data across various scales and dimensions, utilizing spatial optimization techniques to control the spatial properties of the resulting SES units. Advanced dimension reduction algorithms are incorporated to accommodate the non-linear characteristics of SES, enhancing the precision of the delineation process.
Utilizing the socio-environmental geodatabase of the Rio Grande/Bravo basin, the research demonstrates the practical application of the framework. This basin, encompassing diverse cultures, ecosystems, and economies, serves as an ideal case study for testing the methodology. The delineation process considers various factors, including administrative boundaries, estimated total quantities, compactness, spatial contiguity, and similarity in socio-environmental characteristics. A key objective is to enhance the accessibility, reproducibility, and scalability of the methodology by employing open-source Python packages. Addressing computational demands, the study employs the Uniform Manifold Approximation and Projection (UMAP) algorithm for dimension reduction, facilitating efficient processing.
This methodological framework advances the understanding of interactions between environmental and socio-economic subsystems, promoting sustainable resource governance. The proposed framework supports sustainable landscape planning and resource management through robust regionalization and interdisciplinary synthesis, making it transferable to other research contexts using diverse data formats and spatial scales. | en_US |