The unique feature of permafrost in the Arctic is the presence of a large amount of ice below the earth surface. Thermal degradation and subsequent permafrost destabilization causes thaw subsidence and thermokarst development. Because these processes are difficult to detect due to the lack of timely and accurate elevation datasets they have received not much attention, despite their potentially global significance through the permafrost carbon feedback. Thanks to remote sensing pioneering works in Alaska and Siberia, widespread thaw subsidence has been documented and is increasingly perceived as a potentially widespread permafrost landscape response to contemporary climate change. Clearly, however, detailed local inventories are required to calibrate regional long and short-term assessments for measuring surface deformation due to permafrost thaw. The objective of our study is to analyze time series of repeat terrestrial, air-, and space borne laser scanning (rLiDAR) for quantification of land surface lowering due to permafrost thaw, which is poorly resolved in terms of recent landscape development in the Arctic. Our work aims at finding commonalities and differences of change or no change on ground-ice-rich primary surfaces that are preserved as uplands, which cover 15 to 20% of the Teshekpuk Lake Special Area on the Arctic Coastal Plain of northern Alaska. Our approach focuses on quantifying modern thaw subsidence and thermokarst rates with high spatial resolution data over several decades as well as high temporal resolution data of inter-annual intervals. Multi-annual measurements of rLiDAR over Arctic Alaska have been made by aircraft in 2016 and in 2015+2017 through on-site surveys during field expeditions. These in situ data serve as a basis for large scale surface change assessments using time series of photogrammetrically derived elevation data from very high resolution historical aerial photographs and modern satellite imagery. The synergistic data fusion approach enhances permafrost degradation monitoring and better resolves surface deformation associated with thaw subsidence. The novel datasets also provide insights into previously unrecognized patterns of rapid permafrost thaw and related interconnections.