Factors Influencing the Spatiotemporal Changes of Permafrost in Northeast China from 1982 to 2020

• Published in: Land (Basel) Vol. 12; no. 2; p. 350
• Main Authors: Yang, Dongyu, Zhan, Daqing, Li, Miao, Zang, Shuying
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2023
• Subjects: Analysis; change trend; Climate change; Coniferous forests; Correlation analysis; Deciduous forests; Dominance; Environmental factors; Global warming; Grasslands; Heat; influencing factors; Mixed forests; Normalized difference vegetative index; northeast permafrost area; Permafrost; Precipitation; Radiation; Remote sensing; Snow; Snow cover; Snow depth; Soil degradation; Spatial analysis; surface frost number model; Surface temperature; Vegetation; China
• ISSN: 2073-445X; 2073-445X
• DOI: 10.3390/land12020350

Permafrost in northeast China, which is at the southern edge of the high-latitude permafrost belt in Eurasia, is extremely sensitive to climate warming. However, the distribution of permafrost in the region in recent years has been poorly studied, and there is a lack of understanding of the relative importance of environmental factors affecting the region. Based on observed ground surface temperature (GST) data, this study quantifies changes in the permafrost area in northeast China from 1982 to 2020 using a surface frost number model, and the influencing factors are identified based on dominance analysis and spatial correlation analysis. The results suggest that the permafrost in northeast China during the observation period underwent degradation with a degradation rate of 0.33 × 104 km2/a. In addition, the permafrost degradation also exhibited altitudinal and latitudinal zonality. Permafrost degradation under typical grassland, deciduous forest, and savannah cover was more significant than that under evergreen forest, mixed forest, and shrubbery cover. As revealed by the dominance analysis results, the annual average snow cover, annual average snow depth and annual average normalized difference vegetation index (NDVI) had the largest contributions to the variance of the permafrost area in northeast China, accounting for 88.3% of the total variance contribution of the six influencing factors. The spatial correlation results reveal that areas with a significantly increased NDVI and significantly reduced snow depth and snow cover were coincident with areas with significantly degraded permafrost. Hence, the snow cover, snow depth, and NDVI were found to have the greatest influence on the permafrost distribution in northeast China. The results of this study evidently increase the understanding of the changing permafrost in northeast China, providing important knowledge about permafrost for researchers and the related community.