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Remote Sensing–Empowered DESF Framework for Rural Spatial Reconstruction and Landscape Transformation

Publicada
Servidor
Preprints.org
DOI
10.20944/preprints202510.2316.v1

Background: Amid rapid urbanization, rural regions are undergoing profound spatial restructuring and landscape degradation. This study establishes a remote sensing–empowered integrated framework of Diagnosis–Elements–Structure–Function (DESF) to systematically investigate the mechanisms and pathways of rural spatial reconstruction and landscape reshaping. The DESF framework provides a comprehensive approach to understanding how ecological, cultural, and structural dimensions interact in reshaping rural territories. Methods: By integrating multi-source remote sensing imagery, GIS spatial analysis, and extensive field surveys, the study develops a multi-indicator rurality diagnostic model, a dual-dimensional “ecological–cultural” landscape classification system, and a spatial structure optimization module. Together, these form a four-tiered technical route encompassing data acquisition, diagnosis, reconstruction, and application. The methodological design bridges quantitative analysis and human-centered interpretation, enabling an in-depth understanding of rural transformation dynamics. Results: Empirical analysis in Quzhou County from 1985 to 2015 reveals a 40% decline in the Rurality Index, displaying a distinct “strong-south, weak-north” spatial differentiation pattern under accelerated urbanization. Landscape classification identified 108 distinct landscape elements, grouped into three major landscape assemblages—natural-ecological, agricultural-productive, and rural-living. Spatial structural analysis uncovered six dominant settlement morphologies, including fan-shaped expansion and clustered growth, reflecting a coupled nature–society dual-driven mechanism. Based on these insights, a “core preservation–peripheral integration” spatial strategy is proposed, establishing a hierarchical “central–ordinary–specialized village” system and a functional zoning model characterized by “one core, multiple nodes.”Conclusions: The study advances theoretical understanding by refining the conceptual system of “diagnosis–reconstruction” in rural spatial studies, innovates methodologically by integrating remote sensing–based quantitative diagnostics with qualitative cultural perception, and contributes practically by offering an operational spatial governance toolkit for rural revitalization. The DESF framework demonstrates strong applicability, scalability, and international reference value for sustainable rural development and policy-making under global urbanization dynamics.

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