Permafrost thickness serves as a critical indicator of hydrogeological conditions in cold regions and significantly influences the safety of engineering infrastructure. Due to the combined effects of climate, ecology, and human activities, the thermal characteristics and spatial distribution of permafrost in the Greater and Lesser Khingan Mountains of Northeast China exhibit high complexity, rendering existing permafrost thickness estimation methods largely inapplicable in this region. We developed an integrated estimation framework that bridges the gap between limited deep ground temperature measurements and regional-scale mapping. To overcome the scarcity of deep borehole (>20m) data, a physical-statistical inversion method was employed to derive permafrost base depths from shallow borehole temperature profiles, thereby expanding the foundational dataset to 104 representative sites. Integrating these ground observations with satellite-derived products (e.g., MODIS NDVI) and auxiliary environmental covariates (e.g., DEM-based topography and gridded climatic data), a Random Forest algorithm (RF) was applied to generate a 1 km-resolution permafrost thickness distribution map across Northeast China with a classification accuracy of 0.74. The results indicate that the average permafrost thickness in the study area is 47.71 ± 10 m, exhibiting a spatial pattern of thicker in the north and west, thinner in the south and east, and greater in mountainous areas than in plains. The top three influencing factors of permafrost thickness are atmospheric precipitation, surface thawing degree days (TDDs), and topographic position index (TPI), revealing that the thickness of discontinuous permafrost in northeastern China is primarily governed by local factors such as soil moisture, represented by the thick permafrost existed under a small patch of ground surface. This study provides a new methodological framework for estimating permafrost thickness in regions with limited ground temperature gradient measurement in deep boreholes.
Lu et al. (Wed,) studied this question.