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Spatial stratified heterogeneity analysis of field scale permafrost in Northeast China based on optimal parameters-based geographical detector

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  • Ying Guo
  • Shuai Liu
  • Lisha Qiu
  • Chengcheng Zhang
  • Wei Shan

Abstract

Affected by global warming, the permafrost in Northeast China (NEC) has been continuously degrading in recent years. Many researchers have focused on the spatial and temporal distribution characteristics of permafrost in NEC, however, few studies have delved into the field scale. In this study, based on the Optimal Parameters-based Geographical Detector (OPGD) model and Receiver Operating Characteristic (ROC) test, the spatial stratified heterogeneity of permafrost distribution and the indicating performance of environmental variables on permafrost in NEC at the field scale were analyzed. Permafrost spatial distribution data were obtained from the Engineering Geological Investigation Reports (EGIR) of six highways located in NEC and a total of 19 environmental variables related to heat transfer, vegetation, soil, topography, moisture, and ecology were selected. The H-factors (variables with the highest contribution in factor detector results and interaction detector results): slope position (γ), surface frost number (SFN), elevation (DEM), topographic diversity (TD), and annual snow cover days (ASCD) were found to be the major contributors to the distribution of permafrost at the field scale. Among them, γ has the highest contribution and is a special explanatory variable for permafrost. In most cases, interaction can improve the impact of variables, especially the interaction between H-factors. The risk of permafrost decreases with the increase of TD, RN, and SBD, and increases with the increase of SFN. The performance of SFN to indicate permafrost distribution was found to be the best among all variables (AUC = 0.7063). There is spatial heterogeneity in the distribution of permafrost on highways in different spatial locations. This study summarized the numerical and spatial location between permafrost and different environmental variables at the field scale, and many results were found to be informative for environmental studies and engineering construction in NEC.

Suggested Citation

  • Ying Guo & Shuai Liu & Lisha Qiu & Chengcheng Zhang & Wei Shan, 2024. "Spatial stratified heterogeneity analysis of field scale permafrost in Northeast China based on optimal parameters-based geographical detector," PLOS ONE, Public Library of Science, vol. 19(2), pages 1-22, February.
    • Handle: RePEc:plo:pone00:0297029
    DOI: 10.1371/journal.pone.0297029
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    References listed on IDEAS

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    1. Wei Shan & Lisha Qiu & Ying Guo & Chengcheng Zhang & Zhichao Xu & Shuai Liu, 2022. "Spatiotemporal Distribution Characteristics of Fire Scars Further Prove the Correlation between Permafrost Swamp Wildfires and Methane Geological Emissions," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    2. Juntao Tan & Pingyu Zhang & Kevin Lo & Jing Li & Shiwei Liu, 2016. "The Urban Transition Performance of Resource-Based Cities in Northeast China," Sustainability, MDPI, vol. 8(10), pages 1-17, October.
    3. S. V. Kokelj & M. J. Palmer & T. C. Lantz & C. R. Burn, 2017. "Ground Temperatures and Permafrost Warming from Forest to Tundra, Tuktoyaktuk Coastlands and Anderson Plain, NWT, Canada," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 28(3), pages 543-551, July.
    4. Wei Shan & Chengcheng Zhang & Ying Guo & Lisha Qiu & Zhichao Xu & Yan Wang, 2022. "Spatial Distribution and Variation Characteristics of Permafrost Temperature in Northeast China," Sustainability, MDPI, vol. 14(13), pages 1-16, July.
    5. Boris K. Biskaborn & Sharon L. Smith & Jeannette Noetzli & Heidrun Matthes & Gonçalo Vieira & Dmitry A. Streletskiy & Philippe Schoeneich & Vladimir E. Romanovsky & Antoni G. Lewkowicz & Andrey Abramo, 2019. "Permafrost is warming at a global scale," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
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