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.

Against the background of global warming, environmental and ecological problems caused by frozen ground degradation have become a focus of attention for the scientific community. As the temperature rises, the permafrost is degrading significantly in the frozen ground region of northeast China (FGRN China). At present, research on FGRN China is based mainly on data from meteorological stations, and the research period has been short. In this study, we analyzed spatial and temporal variation in the ground surface freezing index (GFI) and ground surface thawing index (GTI) from 1900 to 2017 for FGRN China, with the air freezing index (AFI) and air thawing index (ATI) using the University of Delaware (UDEL) monthly gridded air temperature dataset. The turning point year for annual mean air temperature (AMAT) was identified as 1985, and the turning point years for GFI and GTI were 1977 and 1996. The air temperature increased by 0.01 ℃ per year during 1900-2017, and the GFI and GTI increased at rates of -0.4 and 0.5 ℃ d per year before the turning point year; after the turning point, these rates were -0.7 and -2.1 ℃ d per year. We utilized a surface frost number model to study the distribution of frozen ground in FGRN China from 1900 to 2017. When the empirical coefficient E value is 0.57, the simulated frozen ground distribution is basically consistent with the existing frozen ground maps. The total area of permafrost in FGRN China decreased by 22.66×10 4 km 2 from 1900 to 2017, and the permafrost boundary moved northward with obvious degradation. The results of this study demonstrate the trend in permafrost boundary degradation in FGRN China, and provide basic data for research on the hydrological, climate, and ecological changes caused by permafrost degradation.

Active layer thickness (ALT) of permafrost changes significantly under the combined influence of human activities and climate warming, which has a significant impact on the ecological environment, hydrology, and engineering construction in cold regions. The spatial differentiation of Active layer thickness and its influencing factors have become one of the hot topics in the field of cryopedology in recent years, but there are few studies in the Da Hinggan Ling Prefecture (DHLP). In this study, the Stefan equation was used to simulate the Active layer thickness in the Da Hinggan Ling Prefecture, and the factor detection and interaction detection functions of geodetector were used to analyze the factors affecting the spatial differentiation of Active layer thickness from both natural and humanity aspects. The results showed that Active layer thickness in the Da Hinggan Ling Prefecture ranges from 58.82 cm to 212.55 cm, the determinant coefficient R2, MAE, RMSE between simulation results and the sampling points data were 0.86, 11.25 (cm) and 13.25 (cm), respectively. Lower Active layer thickness values are mainly distributed higher elevations in the west, which are dominated by forest (average ALT: 136.94 cm) and wetlands (average ALT: 71.88 cm), while the higher values are distributed on cultivated land (average ALT: 170.35 cm) and construction land (average ALT: 176.49 cm) in the southeast. Among the influencing factors, elevation is significantly negatively correlated with ALT. followed by summer mean LST, SLHF and snow depth. NDVI and SM has the strong explanation power for the spatial differentiation of ALT in factor detection. Regarding interactions, the explanatory power of slope ∩ snow depth is the highest of 0.83, followed by the elevation ∩ distance to settlements. The results can provide reference for the formulation of ecological environmental protection and engineering construction policies in cold regions.