Summary of Deep Learning Tools to Support Deforestation Monitoring in the Ivory Coast Using Sar and Optical Satellite Imagery, by Gabriele Sartor et al.
Deep Learning tools to support deforestation monitoring in the Ivory Coast using SAR and Optical satellite imagery
by Gabriele Sartor, Matteo Salis, Stefano Pinardi, Ozgur Saracik, Rosa Meo
First submitted to arxiv on: 16 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| 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 explores the use of satellite imagery and machine learning models to monitor deforestation in developing countries like Ivory Coast. The study compares four state-of-the-art models (U-Net, Attention U-Net, Segnet, and FCN32) on Sentinel images to create a Forest-Non-Forest map (FNF) as ground truth for forest/non-forest segmentation. The researchers aim to predict where deforestation has occurred using open datasets and overcome the limitations of RGB images by employing Synthetic Aperture Radar (SAR) acquisitions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study shows that it’s possible to create models that can classify forest and non-forest pixels in Ivory Coast, even without having a large dataset. By combining Sentinel-1, Sentinel-2, and cloud probability data, the researchers can predict where deforestation might have happened between 2019 and 2020. |
Keywords
» Artificial intelligence » Attention » Machine learning » Probability
