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The degradation of permafrost in the Earth's cold regions due to climate warming and human activities is of increasing concern because of its impact on ecosystems and land management, thus, monitoring the degradation becomes critical. This study aimed to demonstrate a method in which Sentinel-1 DInSAR and MODIS data were combined to estimate and map seasonal and long-term land surface deformation (subsidence/uplifting) and permafrost active layer thickness (ALT) in Donnelly Training Area (DTA) in Alaska. The coherence (similarity) between the paired SAR images was analyzed for their applicability. A sensitivity analysis and accuracy assessment of the estimates were conducted to account for their quality. Results showed that the estimated seasonal subsidence mainly occurring in June and July was in the range of 0 to −0.43 m, while the estimated uplifting mainly happening from September to May of next year was as great as +0.34 m. Moreover, the estimated long-term (2015 to 2018) subsidence and uplifting were mostly distributed in the southern and northern parts of DTA, respectively. The spatially variable time delays led to the ALT estimates greater along the east river and in the west and south parts, and smaller in the north parts. At the significance level of 0.05, the coherence estimates of the paired images were significantly different from zero and compared with the referenced predictions from a widely used annual prediction model, the average residual of the ALT estimates did not significantly differ from zero at the significance level of 0.05. The spatial distributions of the uncertainties for the seasonal surface deformation estimates were similar to those of the input uncertainties from the estimates of model coefficients, the phase change, the modelling error, and the image pairs. Thus, the DInSAR image based method coupled with MODIS data offered the potential of mapping and monitoring the dynamics of permafrost environment for the cold regions such as DTA in which collecting field observations is difficult and costly. This study also enhanced understanding spatiotemporal variability of permafrost deformation in DTA and provided guidelines for developing a near real-time monitoring system of the permafrost environment. • Permafrost degradation due to climate warming and human activity is of great concern. • Land surface deformation of an installation in Alaska is mapped by SAR&MODIS images. • A quality assessment of the land surface deformation estimates is conducted. • The accuracy of the estimates is compatible with that from a widely used model. • This study provides guidelines for developing a near real-time monitoring system. [ABSTRACT FROM AUTHOR]