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Permafrost monitoring using remote sensing techniques is an effective approach at present. Permafrost mostly occurs below the land surface, which limits permafrost monitoring by optical remote sensing. Considering the specific hydrothermal relations between permafrost and its active layer, we developed a permafrost monitoring and classification method that integrated the ground surface soil freeze/thaw states determined by the dual-index algorithm (DIA) and the permafrost classification method based on thermal stability. The modified frost index was introduced into the method as a link between the DIA and the permafrost classification method. Northeastern China was selected to establish and verify the proposed method and to examine the changes in regional permafrost against the background of global warming from 2002 to 2017. The results showed that the ground surface soil freeze/thaw states were significantly correlated with the permafrost distribution. The spatial continuity of permafrost and its sensitivity to climate change could be effectively reflected by the modified frost index. The proposed method had a high accuracy with a classification error smaller than 3%, compared with static permafrost maps. Moreover, the proportion of permafrost decreased from 29% at the beginning of the 21st century to 22.5% at present in northeastern China over the study period. The southern permafrost boundary in the study area generally moved northward approximately 25–75 km. Additionally, the method was applied to the Northern Hemisphere (30° N – 90° N), which demonstrated its effectiveness and extended applicability. [ABSTRACT FROM AUTHOR]