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An effective approach for mapping permafrost in a large area using subregion maps and satellite data

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  • Jianan Hu
  • Shuping Zhao
  • Zhuotong Nan
  • Xiaobo Wu
  • Xuehui Sun
  • Guodong Cheng

Abstract

Permafrost distribution maps are of importance for environmental assessment, climate system modeling, and practical engineering applications. The scarcity of forcing data and parameters often limits the uses of permafrost models over large areas. However, detailed data are often available in a few subregions through field investigations. In this study, we propose a novel approach for mapping permafrost distribution in a large and data‐scarce area using an empirical model with subregion permafrost maps and satellite data as inputs. The surface frost number model (FROSTNUM) was re‐inferred to include an extra soil parameter to represent the thermal and moisture conditions in soils. The optimal soil parameters were determined from the subregion maps of permafrost distribution through spatial clustering, parameter optimization, and the decision tree method. FROSTNUM was fed with satellite‐derived ground surface freezing and thawing indices to map the permafrost distribution over the study area. The proposed approach was evaluated in the Gaize area on the Qinghai–Tibet Plateau, where intensive field studies have been done. The simulated permafrost distribution is consistent with a map of permafrost distribution made from borehole observations and field surveys in Gaize. Due to excellent accuracy, the approach is effective and can be used in large areas with limited data.

Suggested Citation

  • Jianan Hu & Shuping Zhao & Zhuotong Nan & Xiaobo Wu & Xuehui Sun & Guodong Cheng, 2020. "An effective approach for mapping permafrost in a large area using subregion maps and satellite data," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 31(4), pages 548-560, October.
  • Handle: RePEc:wly:perpro:v:31:y:2020:i:4:p:548-560
    DOI: 10.1002/ppp.2068
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    References listed on IDEAS

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    1. Kjersti Gisnås & Bernd Etzelmüller & Cristian Lussana & Jan Hjort & A. Britta K. Sannel & Ketil Isaksen & Sebastian Westermann & Peter Kuhry & Hanne H. Christiansen & Andrew Frampton & Jonas Åkerman, 2017. "Permafrost Map for Norway, Sweden and Finland," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 28(2), pages 359-378, April.
    2. D. W. Riseborough, 2002. "The mean annual temperature at the top of permafrost, the TTOP model, and the effect of unfrozen water," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 13(2), pages 137-143, April.
    3. Hao Chen & Zhuotong Nan & Lin Zhao & Yongjian Ding & Ji Chen & Qiangqiang Pang, 2015. "Noah Modelling of the Permafrost Distribution and Characteristics in the West Kunlun Area, Qinghai‐Tibet Plateau, China," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 26(2), pages 160-174, April.
    4. Xiaobo Wu & Zhuotong Nan & Shuping Zhao & Lin Zhao & Guodong Cheng, 2018. "Spatial modeling of permafrost distribution and properties on the Qinghai‐Tibet Plateau," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 29(2), pages 86-99, April.
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    Cited by:

    1. Dongyu Yang & Daqing Zhan & Miao Li & Shuying Zang, 2023. "Factors Influencing the Spatiotemporal Changes of Permafrost in Northeast China from 1982 to 2020," Land, MDPI, vol. 12(2), pages 1-22, January.

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