Various biotic and abiotic agents are changing forests. Prolonged human activities substantially could cause not only different changes in forests but also could accelerate natural hazards in the Anthropocene. Despite several remote sensing-based research in forest changes, there is a need for a holistic study that could visualize different dimensions of anthropogenic-induced forest changes such as forest loss, forest fragmentation, and forest degradation. Besides, the effects of these changes require to be investigated in the natural hazards’ studies in forest regions. This research was accomplished for holistic assessing of long-term forest loss, forest fragmentation, and forest degradation induced by human activities such as sprawling residential areas and expanding road networks in northeast Iran. Moreover, it has investigated the significance of forest dynamics in analyzing of landslide susceptibility in the forest regions. \nThe time series of Landsat data with the contribution of aerial photos were employed to investigate long-term forest changes in three spans from 1966 to 2016. The expansion of forest roads was extracted from a combination of satellite images and topographic maps. Both pixel-and object-based approaches were used for analyzing forest changes. The spatial autocorrelation indicators and spatial regression models were applied for visualizing patterns of forest changes and possible relationships between forest changes and the expansion of residential areas and road networks. Furthermore, the detection of old and new landslide events was accomplished through Sentinel-1 and -2 images and DEM derivatives using the object-oriented random forest method. The significance of conditioning and triggering factors that control the susceptibility of protected and non-protected forests to landslides were explored using the object-based random forest approach as well.\nKey findings revealed that the expansion of residential areas and rural roads have increasingly heightened the rates of forest loss before 2000. However, the spatial patterns of forest dynamics were changed from forest loss to forest fragmentation and forest degradation– along with the expansion of forest and mine roads– since the 1980s. Although the topographic and hydrologic features were the top influential predictors that control the susceptibility of protected forests to landslides, the natural and anthropogenic triggers have obtained significant values in non-protected forests to the landslides as well; forest fragmentation and logging were the top features of anthropogenic triggers. This research verifies that influential variables are different either for detecting landslides or for assessing landslide susceptibility in different forest regions.\nThe spatial-based regression models showed higher efficiency than the traditional regression model for modelling relationships between forest changes and anthropogenic- induced drivers; however, there was no priority between spatial models. Random forest algorithm demonstrated satisfactory accuracy for mapping of both historical landslides and landslide susceptibility with higher accuracy in the protected forests.\nThis research has investigated human-induced forest changes; however, other abiotic and biotic agents may cause these changes such as climate hazards, forest fires, insect outbreaks, pathogens, and other natural hazards that need to be explored in the future studies.