%0 Dataset
%T Frozen soil map of China (2000)
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/eae13ba7-70d4-4bf5-bd2a-f31024741b12
%W NCDC
%R 10.12072/ncdc.permafrost.db7314.2026
%A Ran Youhua
%A LI Xin
%K Frozen soil;frozen soil distribution;seasonal frozen soil
%X The existing frozen soil distribution map shows significant differences in classification system, data sources, and mapping methods, reflecting China's phased understanding of the distribution of permafrost over the past half century. In order to more accurately depict the spatial distribution of frozen soil in China and accurately calculate the frozen soil area, this article systematically reviews the existing frozen soil maps, integrates multiple sets of frozen soil mapping results and simulated data of permafrost on the Qinghai Tibet Plateau, unifies the national data time phase, and develops a new version of the national frozen soil distribution map, which objectively reflects the actual distribution pattern of frozen soil in China before and after 2000.During the preparation of this data, the following principles were followed for each type of frozen soil:1. The base map adopts the Chinese permafrost zoning and type map (1:10 million) (Qiu Guoqing et al., 2000). The distribution of permafrost and permafrost in high mountains outside the Qinghai Tibet Plateau follows the original map; The boundaries between seasonal frozen soil and instantaneous frozen soil, as well as between instantaneous frozen soil and non frozen soil, remain unchanged. The distribution of permafrost in the Qinghai Tibet Plateau region and high latitude permafrost in the Northeast region is updated using the following results. 2. The distribution of high-altitude permafrost and high-altitude permafrost in the Qinghai Tibet Plateau region was updated using the simulation results of Nan Zhuo Tong et al. (2002). This model utilizes the measured annual average ground temperature data from 76 boreholes along the Qinghai Tibet Highway for regression statistical analysis, obtaining the relationship between annual average ground temperature and latitude and elevation. Based on this relationship, combined with GTOPO30 elevation data (a global 1km digital elevation model developed under the leadership