Remote Sensing Video Tracking: Current Status, Challenges, and Future
With the rapid advancement of remote sensing technology, the acquisition and processing of remote sensing video data, including high-resolution satellite, hyperspectral, and SAR video, have become key research areas in remote sensing. As a crucial branch of video analysis, remote sensing video tracking enables continuous monitoring and dynamic analysis of ground targets, with widespread applications in military operations, disaster monitoring, environmental protection, and urban management. This review systematically examines the current state of remote sensing video tracking research, exploring the technological advancements of traditional and modern methods, including model-based approaches, feature-based approaches, and deep learning-based methods. The work also examines evaluation metrics and benchmark testing methodologies in remote sensing video tracking. Finally, this review highlights ten unresolved challenges in the field and offers insights into the future of next-generation artificial intelligence technologies. Through a comprehensive overview and in-depth analysis of existing technologies, this work aims to provide researchers with a systematic reference, promoting further development and innovation in remote sensing video tracking.
Authors
- Yaoyang Du
- Puhua Chen (ORCID: https://orcid.org/0000-0001-5472-1426)
- Biao Hou (ORCID: https://orcid.org/0000-0002-1996-186X)
- Xiangrong Zhang (ORCID: https://orcid.org/0000-0003-0379-2042)
- Licheng Jiao (ORCID: https://orcid.org/0000-0003-3354-9617)
- Wenping Ma (ORCID: https://orcid.org/0000-0001-8872-2195)
- Shuang Wang (ORCID: https://orcid.org/0000-0003-4940-1211)
- Qianyue Bao (ORCID: https://orcid.org/0000-0002-6025-3881)
- Jiahao Wang (ORCID: https://orcid.org/0000-0002-0375-9253)
- Xu Liu (ORCID: https://orcid.org/0000-0002-8780-5455)
- Lingling Li (ORCID: https://orcid.org/0000-0002-6130-2518)
- Fang Liu (ORCID: https://orcid.org/0000-0002-5669-9354)
- Hao Wang (ORCID: https://orcid.org/0000-0002-6956-7342)
- Long Sun (ORCID: https://orcid.org/0000-0001-7446-9336)
- Shuo Li (ORCID: https://orcid.org/0000-0002-2395-6537)
- Shuyuan Yang (ORCID: https://orcid.org/0000-0002-4796-5737)
- Jie Zhang (ORCID: https://orcid.org/0000-0001-7338-666X)
Institutions
- Xidian University (CN)
Publication Details
- Journal
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/jstars.2025.3573572
- Citations
- 7
- Primary Topic
- Remote Sensing and Land Use
- Type
- article
- Field-Weighted Citation Impact
- 9.11