TY - JOUR
T1 - Remote sensing of the global cryosphere
T2 - Status, processes, and trends
AU - Zhang, Guoqing
AU - Xie, Hongjie
AU - Fernandez, Alfonso
AU - Kinnard, Christophe
AU - Lhermitte, Stef
PY - 2025
Y1 - 2025
N2 - Driven by rapid technological advances in cryospheric science and the emergence of new generations of remote sensing observations, this special issue of Remote Sensing of Environment, entitled “Remote sensing of the global cryosphere: status, processes, and trends”, brings together 23 studies published between 2023 and 2025. Collectively, these papers showcase how multi-sensor satellite observations, high-resolution digital elevation models (DEMs), and cutting-edge deep learning techniques are revolutionizing the monitoring of glaciers, snow, glacial lakes, permafrost, sea ice, and ice shelves across the Earth's three poles: the Arctic (including Greenland), Antarctica, and High Mountain Asia (the Third Pole). These studies integrate diverse datasets – including multisource DEMs, optical, thermal, and passive microwave imageries, as well as RADAR, LiDAR, and GRACE observations - to quantify glacier mass balance, map glacial lakes, assess permafrost thermal conditions, classify sea-ice types, and detect icebergs. We organize the publications by major cryospheric themes and their distribution across polar regions and summarize the dominant remote sensing datasets and methodologies employed. Finally, we outline future directions, emphasizing multi-sensor data fusion, physics-informed modeling, and AI-driven approaches to improve predictions of cryospheric change under a warming climate.
AB - Driven by rapid technological advances in cryospheric science and the emergence of new generations of remote sensing observations, this special issue of Remote Sensing of Environment, entitled “Remote sensing of the global cryosphere: status, processes, and trends”, brings together 23 studies published between 2023 and 2025. Collectively, these papers showcase how multi-sensor satellite observations, high-resolution digital elevation models (DEMs), and cutting-edge deep learning techniques are revolutionizing the monitoring of glaciers, snow, glacial lakes, permafrost, sea ice, and ice shelves across the Earth's three poles: the Arctic (including Greenland), Antarctica, and High Mountain Asia (the Third Pole). These studies integrate diverse datasets – including multisource DEMs, optical, thermal, and passive microwave imageries, as well as RADAR, LiDAR, and GRACE observations - to quantify glacier mass balance, map glacial lakes, assess permafrost thermal conditions, classify sea-ice types, and detect icebergs. We organize the publications by major cryospheric themes and their distribution across polar regions and summarize the dominant remote sensing datasets and methodologies employed. Finally, we outline future directions, emphasizing multi-sensor data fusion, physics-informed modeling, and AI-driven approaches to improve predictions of cryospheric change under a warming climate.
KW - Glacial lake
KW - Glacier
KW - Ice sheet
KW - Permafrost
KW - Remote sensing
KW - Sea ice
KW - Snow
UR - http://www.scopus.com/inward/record.url?scp=105027857097&partnerID=8YFLogxK
U2 - 10.1016/j.rse.2025.115220
DO - 10.1016/j.rse.2025.115220
M3 - Editorial
AN - SCOPUS:105027857097
SN - 0034-4257
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
M1 - 115220
ER -