Summary of Artificial Intelligence Mangrove Monitoring System Based on Deep Learning and Sentinel-2 Satellite Data in the Uae (2017-2024), by Linlin Tan and Haishan Wu
Artificial Intelligence Mangrove Monitoring System Based on Deep Learning and Sentinel-2 Satellite Data in the UAE (2017-2024)
by Linlin Tan, Haishan Wu
First submitted to arxiv on: 18 Nov 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computation (stat.CO)
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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 study combines deep learning with multispectral data from Sentinel-2 to monitor the spatiotemporal dynamics of densely distributed mangroves in the UAE, achieving an mIoU of 87.8% on the validation set. The research maps the total mangrove area in the UAE from 2017 to 2024, showing an increase of 9,142.21 hectares and corresponding carbon sequestration growth. Abu Dhabi plays a dominant role in this growth, while other emirates also contribute to stable and sustainable expansion. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Mangroves are super important for keeping our coastlines healthy and protecting animals. To understand how they’re doing, scientists need to map them regularly. Usually, they use satellite images to do this. But there’s not much research on mangroves in the UAE specifically. This study uses a special computer program called UNet++ to analyze these satellite images and track the growth of mangroves in the UAE from 2017 to 2024. The results show that more mangroves are growing, which is great news for our environment! |
Keywords
» Artificial intelligence » Deep learning » Spatiotemporal » Unet
