# Remote Sensing of Environmental Changes in Cold Regions: Methods, Achievements and Challenges
###### Abstract  
Cold regions, including high-latitude and high-altitude landscapes, are experiencing profound environmental changes driven by global warming. With the advance of earth observation technology, remote sensing has become increasingly important for detecting, monitoring, and understanding environmental changes over vast and remote regions. This paper provides an overview of recent achievements, challenges, and opportunities for land remote sensing of cold regions by (a) summarizing the physical principles and methods in remote sensing of selected key variables related to ice, snow, permafrost, water bodies, and vegetation; (b) highlighting recent environmental nonstationarity occurring in the Arctic, Tibetan Plateau, and Antarctica as detected from satellite observations; (c) discussing the limits of available remote sensing data and approaches for regional monitoring; and (d) exploring new opportunities from next-generation satellite missions and emerging methods for accurate, timely, and multi-scale mapping of cold regions. remote sensing; cryosphere; climate change; northern high latitudes; Antarctica; Tibetan Plateau 1  
destabilization and melting of ice above the 0 \({}^{\circ}\)C isotherm [7; 8], lengthening the annual non-frozen season [9; 10], and thawing of carbon-rich permafrost soils [11]. Recent region-wide warming trends have altered vegetation, and interactions and feedbacks between the water, energy, and carbon cycles [12; 13; 14]; these changes have also resulted in a myriad of impacts to landscape function and ecosystem services [15]. Warmer temperatures have reduced the duration of seasonal snow and ice cover over land, ocean, and inland water bodies [16; 17; 18; 19]. Longer snow and ice-free seasons have led to lower surface albedos and greater net energy loading, reinforcing regional warming trends [20; 21; 22]. The alteration of seasonal snow and ice cover has also altered wildlife habitats and human mobility, including degrading the stability of snow and ice cover for winter travel [23]. Permafrost soils are estimated to store up to 1,600 billion tonnes of soil carbon, representing roughly twice the amount of carbon stored in the atmosphere [11]. Warming soils have promoted permafrost degradation and active layer deepening, enhancing the mobilization and potential transfer of soil carbon to the atmosphere [24; 25]. Ground surface deformation from degrading permafrost has also increased the risk of damage to human infrastructure, including roads, pipelines, and buildings [26]. Changes in permafrost properties greatly impact the surface water budget because the soil ice layers form a relatively impermeable barrier to soil drainage [27]. Surface subsidence into the water table driven by the thawing of ice rich soils has increased surface water inundation and lake expansion in continuous permafrost areas (where more than 80% of the ground is underlain by permafrost). In contrast, extensive draining of lakes and wetlands has been observed in more degraded permafrost areas [28; 29; 30]. Satellite observations have indicated vegetation greening over northern latitude tundra, attributed to enhanced vegetation growth from a longer frost-free season, contrasting with vegetation browning in boreal forest and some tundra regions, that may result from greater drought stress due to warmer temperatures and a longer frost-free season [31]. Boreal forests have also been affected by an increase in the frequency and severity of wildfires exacerbated by warmer and drier conditions, and insect-related disturbances [32; 33]. The net effect of these changes is a complex snow/ice, vegetation, soil, and wetland mosaic where the terrestrial water, carbon, and energy cycles are strongly coupled and interactive with the climate. Remote sensing provides an unprecedented approach for characterizing the timing, magnitude, and patterns of environmental changes. This is especially advantageous for geographically remote cold regions, where site observations are often spatially sparse and temporally limited.