Due to the effects of global climate change, the permafrost temperature in the Qinghai-Tibet Plateau (QTP) has rapidly increased over the past decades. The development of thermokarst landforms is one distinctive indicator of permafrost degradation, while the change of the rate of permafrost degradation in recent 10 years has not been systematically investigated in QTP. In this paper, the annual average growth rate (AAGR) of ground deformation, the change of thaw slump areas, and the change of active layer thickness (ALT) of thermokarst landforms are monitored integrating SAR (synthetic aperture radar) and optical images for years 2007 to 2020 in Qilian Mountain, northern QTP. The ground deformation rate and seasonal amplitude were estimated by InSAR method, and the descending and ascending InSAR data are compared the validate the results. Based on the deformation results, AAGR was introduced to evaluate the permafrost degradation degree. Moreover, the ALT were estimated based on the seasonal deformation amplitude and Stefan model. The spatio-temporal characteristics of ground deformation and its relationship with thaw slump and temperature are explored. Experimental results show that the deformation rate increased about 150 % from 2007 to 10 to 2017-20. The maximum AAGR of deformation rate in the study area can reach 20.6 %. The thaw slump area has an obvious trend of expansion from 2009 to 2015, and its distribution agreed well with the deformation map. The ALT results ranged from 0.5 m to 2.8 m, indicating an obvious increase trend from 2007 to 2020. Based on the estimated increased ground deformation, thaw slump area, and ALT, it is inferred that frozen ground was undergoing serious degradation in the last 10 years. This study demonstrates the capability of multi-temporal InSAR in observing the accelerated permafrost thaw-freezing process and monitoring the permafrost parameters.

The combined effect of climate change and accelerated economic development in Northern regions increases the threat of permafrost related surface deformation to buildings and transportation infrastructure. Satellite based InSAR provides a means for monitoring infrastructure that may be both remote and spatially extensive. However, permafrost poses challenges for InSAR monitoring due to the complex temporal deformation patterns caused by both seasonal active layer fluctuations and long-term changes in permafrost thickness. These dynamics suggest a need for increasing the temporal resolution of multi-temporal InSAR methods. To address this issue we have developed a method that combines and jointly processes two or more same side geometry InSAR stacks to provide a high-temporal resolution estimate of surface deformation. The method allows for combining stacks from more than a single SAR sensor and for a combination of frequency bands. Data for this work have been collected and analysed for an area near the community of Umiujaq, Quebec in Northern Canada and include scenes from RADARSAT-2, TerraSAR-X and COSMO-SkyMed. Multiple stack based surface deformation estimates are compared for several cases including results from the three sensors individually and for all sensors combined. The test cases show substantially similar surface deformation results which correlate well with surficial geology. The best spatial coverage of coherent targets was achieved when data from all sensors were combined. The proposed multiple stack method is demonstrated to improve the estimation of surface deformation in permafrost affected areas and shows potential for deriving InSAR based permafrost classification maps to aid in the monitoring of Northern infrastructure.