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Enhancing demarcation in regionalization in the eastern Qinghai-Xizang Plateau through geographically weighted

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Abstract

The eastern margin of the Qinghai-Xizang Plateau, as a critical transition zone between the plateau and the Sichuan Basin, poses substantial challenges for geographic regionalization, primarily due to its intricate terrain and climatic heterogeneity. Traditional spatial clustering methods often struggle to balance spatial continuity and attribute similarity, suffering from subjectivity and inadequate representation of topographic complexity. This study proposes a novel mountainous geographic regionalization framework that integrates topographic and climatic characteristics, using Kangding county as a typical case. Principal Component Analysis (PCA) was employed to perform dimensionality reduction on multiple environmental variables and assign relative weights. A Gaussian-weighted function was further applied to adjust attribute distances to capture spatial non-stationarity, while the geographic distance weight was systematically optimized. The partitioning outcomes were evaluated using clustering quality indicators (Davies-Bouldin index, Silhouette index, Calinski-Harabasz index) and spatial autocorrelation indicators (Moran’s I index, Moran’s Z-score). Results indicated that when the number of clusters was set to five and the geographic distance weight was 0.5, the clustering algorithm optimized the trade-off between spatial continuity and attribute similarity (Davies-Bouldin index = 1.14, Silhouette index = 0.30, Calinski-Harabasz index = 25150.91, Moran’s I = 0.97, Moran’s Z-score = 292.28). Compared to the traditional K-means clustering, this approach enhanced intra-cluster similarity (Sil) by 259% and improved spatial continuity (Moran’s I, Moran’s Z-score) by approximately 44%. This method effectively addresses the challenge of coordinating spatial constraints with attribute heterogeneity in mountainous environmental zoning, in a county scale, providing an automated, data-driven approach for geographic partitioning in complex terrains. The findings offer valuable insights for mountain ecosystem management and regional geographic studies. Our study provides a set of effective methods of demarcation of regional boundaries based on raster data, offering important insights for ecological zoning management and regional studies in mountainous environments at a small scale.

Data availability

The datasets analyzed in this study are publicly available. Climate data were obtained from the National Tibetan Plateau Data Center (https://data.tpdc.ac.cn). The DEM was acquired from the Shuttle Radar Topography Mission (SRTM, https://srtm.csi.cgiar.org/).

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Funding

This study was supported by the National Natural Science Foundation of China (42171067),and the National Key Research and Development Program of China (2023YFD1901204).

Author information

Authors and Affiliations

  1. Key Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, PR China

    Xianglong Liu, Desheng Hong, Hangtao Du, Xiaoguo Wang & Bo Zhu

  2. University of Chinese Academy of Sciences, Beijing, 100049, PR China

    Xianglong Liu, Desheng Hong & Hangtao Du

  3. Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264003, PR China

    Hongyang Dong

Authors

  1. Xianglong Liu
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  2. Desheng Hong
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  3. Hongyang Dong
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  4. Hangtao Du
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  5. Xiaoguo Wang
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  6. Bo Zhu
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Contributions

Developing the methodology, supervision, validating the results and reviewing were done by Xiaoguo Wang and Bo Zhu. applying the methodology, preparing codes, software, analyzing the data, writing the original draft were done by Xianglong Liu, Desheng Hong, Hongyang Dong and Hangtao Du. All authors reviewed the manuscript.

Corresponding author

Correspondence to
Xiaoguo Wang.

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Liu, X., Hong, D., Dong, H. et al. Enhancing demarcation in regionalization in the eastern Qinghai-Xizang Plateau through geographically weighted.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-32098-4

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  • DOI: https://doi.org/10.1038/s41598-025-32098-4

Keywords

  • Regionalization
  • Spatial cluster
  • Gaussian-weighted
  • Euclidean distance
  • Eastern Qinghai-Xizang plateau

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