Remote sensing of the mountain cryosphere: Current capabilities and future opportunities for research

被引:24
作者
Taylor, Liam S. [1 ]
Quincey, Duncan J. [1 ]
Smith, Mark W. [1 ]
Baumhoer, Celia A. [2 ]
McMillan, Malcolm [3 ]
Mansell, Damien T. [4 ]
机构
[1] Univ Leeds, Leeds, W Yorkshire, England
[2] German Aerosp Ctr DLR, Cologne, Germany
[3] Univ Lancaster, Lancaster, England
[4] Univ Exeter, Exeter, Devon, England
来源
PROGRESS IN PHYSICAL GEOGRAPHY-EARTH AND ENVIRONMENT | 2021年 / 45卷 / 06期
关键词
Earth observation; glacier; satellite; technology; snow; artificial intelligence; DEBRIS-COVERED GLACIERS; FROM-MOTION PHOTOGRAMMETRY; UNMANNED AERIAL SYSTEMS; MAPPING SNOW DEPTH; MASS-LOSS; SATELLITE IMAGERY; ALPINE TERRAIN; CLIMATE-CHANGE; HETEROGENEOUS CHANGES; CORDILLERA BLANCA;
D O I
10.1177/03091333211023690
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Remote sensing technologies are integral to monitoring the mountain cryosphere in a warming world. Satellite missions and field-based platforms have transformed understanding of the processes driving changes in mountain glacier dynamics, snow cover, lake evolution, and the associated emergence of hazards (e.g. avalanches, floods, landslides). Sensors and platforms are becoming more bespoke, with innovation being driven by the commercial sector, and image repositories are more frequently open access, leading to the democratisation of data analysis and interpretation. Cloud computing, artificial intelligence, and machine learning are rapidly transforming our ability to handle this exponential increase in data. This review therefore provides a timely opportunity to synthesise current capabilities in remote sensing of the mountain cryosphere. Scientific and commercial applications were critically examined, recognising the technologies that have most advanced the discipline. Low-cost sensors can also be deployed in the field, using microprocessors and telecommunications equipment to connect mountain glaciers to stakeholders for real-time monitoring. The potential for novel automated pipelines that can process vast volumes of data is also discussed, from reimagining historical aerial imagery to produce elevation models, to automatically delineating glacier boundaries. Finally, the applications of these emerging techniques that will benefit scientific research avenues and real-world societal programmes are discussed.
引用
收藏
页码:931 / 964
页数:34
相关论文
共 50 条
[31]   Observation and Monitoring of Mangrove Forests Using Remote Sensing: Opportunities and Challenges [J].
Giri, Chandra .
REMOTE SENSING, 2016, 8 (09)
[32]   Remote sensing for urban heat island research: Progress, current issues, and perspectives [J].
Diem, Phan Kieu ;
Nguyen, Can Trong ;
Diem, Nguyen Kieu ;
Diep, Nguyen Thi Hong ;
Thao, Pham Thi Bich ;
Hong, Tran Gia ;
Phan, Thanh Noi .
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2024, 33
[33]   Remote sensing of mangroves using unmanned aerial vehicles: current state and future directions [J].
Zimudzi, Edward ;
Sanders, Ian ;
Rollings, Nicholas ;
Omlin, Christian W. .
JOURNAL OF SPATIAL SCIENCE, 2021, 66 (02) :195-212
[34]   Global techno-politics: A review of the current status and opportunities for future research [J].
Yan, Jie ;
Leidner, Dorothy E. ;
Peters, Uchenna .
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2024, 75
[35]   A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops [J].
Gautam, Deepak ;
Pagay, Vinay .
AGRONOMY-BASEL, 2020, 10 (01)
[36]   AI Augmentation to Remote Sensing Imagery in Forestry Conservation & Restoration for Increased Responsive Capabilities [J].
Gandikota, Dhanuj Mount ;
Gladkova, Taissa ;
Tran, Kha-Ai ;
Bapat, Sanika ;
Richkus, Jenn ;
Arnold, Jeffrey .
2022 IEEE APPLIED IMAGERY PATTERN RECOGNITION WORKSHOP, AIPR, 2022,
[37]   Explainable Multimodal Learning in Remote Sensing: Challenges and Future Directions [J].
Guenther, Alexander ;
Najjar, Hiba ;
Dengel, Andreas .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2024, 21 :1-5
[38]   AI Security for Geoscience and Remote Sensing: Challenges and future trends [J].
Xu, Yonghao ;
Bai, Tao ;
Yu, Weikang ;
Chang, Shizhen ;
Atkinson, Peter M. ;
Ghamisi, Pedram .
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2023, 11 (02) :60-85
[39]   Remote Sensing of Surface Melt on Antarctica: Opportunities and Challenges [J].
Husman, Sophie de Roda ;
Hu, Zhongyang ;
Wouters, Bert ;
Munneke, Peter Kuipers ;
Veldhuijsen, Sanne ;
Lhermitte, Stef .
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2023, 16 :2462-2480
[40]   Satellite remote sensing for applied ecologists: opportunities and challenges [J].
Pettorelli, Nathalie ;
Laurance, William F. ;
O'Brien, Timothy G. ;
Wegmann, Martin ;
Nagendra, Harini ;
Turner, Woody .
JOURNAL OF APPLIED ECOLOGY, 2014, 51 (04) :839-848