Permafrost is strongly associated with human well-being and has become a frontier of cryospheric science. Professor Guodong Cheng is one of the most outstanding geocryologists in China. He was elected as an academician of the Chinese Academy of Sciences in 1993 and served as the president of the International Permafrost Association from 1993-1998. In the early 1980s, Professor Cheng proposed the hypothesis of the repeated-segregation mechanism for the formation of thick-layered ground ice near the permafrost table. Subsequently, in the early 2000s, he proposed the proactive roadbed cooling concept and led the successful development of a series of specific engineering measures that were fully applied in the Qinghai-Tibet Railway Project. Furthermore, he developed a conceptual model to describe the influences of changing permafrost on the groundwater system and discovered the sink-holing effect (channeling with improved hydraulic conductivity of warming permafrost). Professor Cheng has also developed theories on the three-dimensional zonation and proposed a classification system and an altitude model for high-altitude permafrost distribution. On this special occasion of Professor Cheng's 80th birthday, this paper summarizes his outstanding achievements on permafrost science, hoping the permafrost research community will carry forward the momentum to further advance permafrost science worldwide.

High-resolution permafrost mapping is an important direction in permafrost research. Arxan is a typical area with permafrost degradation and is situated on the southern boundary of the permafrost region in Northeast China. With the help of Google Earth Engine (GEE), the maximum entropy classifier (MaxEnt) is used for permafrost mapping using the land surface temperature (LST) of different seasons, deviation from mean elevation (DEV), solar radiation (SR), normalized difference vegetation index (NDVI), and normalized difference water index (NDWI) as the characteristic variables. The prior data of permafrost distribution were primarily based on 201 borehole data and field investigation data. A permafrost probability (PP) distribution map with a resolution of 30 m was obtained. The receiver operating characteristic (ROC) curve was used to test the distribution results, with an area under the curve (AUC) value of 0.986. The results characterize the distribution of permafrost at a high resolution. Permafrost is mainly distributed in the Greater Khingan Mountains (GKM) in the research area, which run from the northeast to the southwest, followed by low-altitude area in the northwest. According to topographic distribution, permafrost is primarily found on slope surfaces, with minor amounts present in peaks, ridges, and valleys. The employed PP distribution mapping method offers a suggestion for high-resolution permafrost mapping in permafrost degradation areas.

Permafrost is a key element of the cryosphere and an essential climate variable in the Global Climate Observing System. There is no remote-sensing method available to reliably monitor the permafrost thermal state. To estimate permafrost distribution at a hemispheric scale, we employ an equilibrium state model for the temperature at the top of the permafrost (TTOP model) for the 2000-2016 period, driven by remotely-sensed land surface temperatures, down-scaled ERA-Interim climate reanalysis data, tundra wetness classes and landcover map from the ESA Landcover Climate Change Initiative (CCI) project. Subgrid variability of ground temperatures due to snow and landcover variability is represented in the model using subpixel statistics. The results are validated against borehole measurements and reviewed regionally. The accuracy of the modelled mean annual ground temperature (MAGT) at the top of the permafrost is +/- 2 degrees C when compared to permafrost borehole data. The modelled permafrost area (MAGT 0) is around 21 x 10(6) km(2) (22% of exposed land area), which is approximately 2 x 10(6) km(2) less than estimated previously. Detailed comparisons at a regional scale show that the model performs well in sparsely vegetated tundra regions and mountains, but is less accurate in densely vegetated boreal spruce and larch forests.

Permafrost distribution in the Qinghai-Tibet Engineering Corridor (QTEC) is of growing interest due to the increase in infrastructure development in this remote area. Empirical models of mountain permafrost distribution have been established based on field sampled data, as a tool for regional-scale assessments of its distribution. This kind of model approach has never been applied for a large portion of this engineering corridor. In the present study, this methodology is applied to map permafrost distribution throughout the QTEC. After spatial modelling of the mean annual air temperature distribution from MODIS-LST and DEM, using high-resolution satellite image to interpret land surface type, a permafrost probability index was obtained. The evaluation results indicate that the model has an acceptable performance. Conditions highly favorable to permafrost presence (70%) are predicted for 60.3% of the study area, declaring a discontinuous permafrost distribution in the QTEC. This map is useful for the infrastructure development along the QTEC. In the future, local ground-truth observations will be required to confirm permafrost presence in favorable areas and to monitor permafrost evolution under the influence of climate change.

A functional model of the permafrost-climate system is applied at national scale, to produce a map of near-surface ground temperatures in the permafrost regions of Canada. The TTOP model links the temperature at the top of permafrost (TTOP) to the climate through seasonal surface transfer functions and subsurface thermal properties. The parameters in the model were compiled at national scale for Canada, although the topographic effects of the Western Cordillera were not incorporated into the analysis. The objective of the study was accomplished by implementing the TTOP model within a Geographical Information System. The TTOP map is evaluated against the published Ground Temperature Map of Canada. The published map shows ground temperatures according to a scale of temperature classes, so TTOP values were categorized into the same classes. Across the permafrost regions of Canada, 72.1% of the area is in the same class in both maps, while 27.7% differs by one temperature class. Only 0.2% of the area differs by two temperature classes. The results suggest that the TTOP model can provide a rational and functional basis for relating near-surface permafrost temperature and climate at national and regional scales. The model could be applied to the assessment of climate change impacts on the magnitude and distribution of permafrost temperatures. Copyright (C) 2001 John Wiley & Sons, Ltd.