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[2602.17397] A High-Level Survey of Optical Remote Sensing
Summary
This article provides a comprehensive overview of optical remote sensing, highlighting advancements in computer vision and drone technology, and serves as a guide for newcomers in the field.
Why It Matters
As the use of drones equipped with RGB cameras becomes more prevalent, understanding optical remote sensing is crucial for researchers and practitioners. This survey consolidates existing literature, offering insights into methodologies and datasets, which can guide future research and applications in various fields.
Key Takeaways
- Optical remote sensing has seen significant advancements due to improvements in computer vision.
- Drones equipped with RGB cameras are becoming standard tools for remote sensing applications.
- The survey provides a holistic overview, addressing diverse tasks and methodologies in optical remote sensing.
- Key datasets and insights are presented to aid researchers entering the field.
- No existing survey offers such a comprehensive perspective on optical remote sensing.
Computer Science > Computer Vision and Pattern Recognition arXiv:2602.17397 (cs) [Submitted on 19 Feb 2026] Title:A High-Level Survey of Optical Remote Sensing Authors:Panagiotis Koletsis, Vasilis Efthymiou, Maria Vakalopoulou, Nikos Komodakis, Anastasios Doulamis, Georgios Th. Papadopoulos View a PDF of the paper titled A High-Level Survey of Optical Remote Sensing, by Panagiotis Koletsis and 5 other authors View PDF HTML (experimental) Abstract:In recent years, significant advances in computer vision have also propelled progress in remote sensing. Concurrently, the use of drones has expanded, with many organizations incorporating them into their operations. Most drones are equipped by default with RGB cameras, which are both robust and among the easiest sensors to use and interpret. The body of literature on optical remote sensing is vast, encompassing diverse tasks, capabilities, and methodologies. Each task or methodology could warrant a dedicated survey. This work provides a comprehensive overview of the capabilities of the field, while also presenting key information, such as datasets and insights. It aims to serve as a guide for researchers entering the field, offering high-level insights and helping them focus on areas most relevant to their interests. To the best of our knowledge, no existing survey addresses this holistic perspective. Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI) Cite as: arXiv:2602.17397 [cs.CV] (or...