Summary of Solid Waste Detection, Monitoring and Mapping in Remote Sensing Images: a Survey, by Piero Fraternali et al.
Solid Waste Detection, Monitoring and Mapping in Remote Sensing Images: A Survey
by Piero Fraternali, Luca Morandini, Sergio Luis Herrera González
First submitted to arxiv on: 14 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper reviews various approaches to detect and monitor illegal solid waste disposal sites using remote sensing technology. The authors leverage Earth Observation (EO) satellites and their sensors to identify, monitor, and assess suitable locations for new landfills. Techniques include waste site detection, dumping site monitoring, and assessment of landfill suitability. The review provides a comprehensive overview of the approaches, techniques, and data sources used in current state-of-the-art solid waste detection models. Additionally, it identifies open issues and discusses potential research directions to improve the effectiveness and reduce costs of these methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us find and track places where people are throwing away trash illegally. This is important because dirty water and soil can hurt animals and humans. The old way of finding these trash sites was slow and expensive, so scientists found a faster and cheaper way using special cameras in space. They looked at how to use these images to find new trash sites and make sure the right places are chosen for new landfills. This paper shows all the different ways they did this and talks about what data sources they used. It also points out what’s still missing and gives ideas for where to go next. |
