Summary of Analyzing Decades-long Environmental Changes in Namibia Using Archival Aerial Photography and Deep Learning, by Girmaw Abebe Tadesse et al.
Analyzing Decades-Long Environmental Changes in Namibia Using Archival Aerial Photography and Deep Learning
by Girmaw Abebe Tadesse, Caleb Robinson, Gilles Quentin Hacheme, Akram Zaytar, Rahul Dodhia, Tsering Wangyal Shawa, Juan M. Lavista Ferres, Emmanuel H. Kreike
First submitted to arxiv on: 12 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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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 The paper explores object detection in historical aerial photographs of Namibia to identify long-term environmental changes. It proposes a workflow for analyzing historical aerial imagery using a deep semantic segmentation model on sparse hand-labels and evaluates different training strategies. The results demonstrate the benefits of these strategies, achieving an average F1 score of 0.661 and 0.755 for the 1943 and 1972 imagery, respectively. The study identifies changes in waterhole, Omuti homestead, and Big tree sizes between 1943 and 1972, reflecting local environmental effects. This work highlights the potential of historical aerial photographs in understanding long-term environmental changes beyond Namibia. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper uses old pictures from the air to see how the environment changed over time in a place called Namibia. They want to find things like waterholes, homes, and big trees and figure out if they got bigger or smaller over the years. They use a special computer model to help them do this and try different ways to make it work better. The results show that some things got bigger while others got smaller, which might be because of changes people made after World War II. This study shows how old pictures can help us understand what happened to the environment in the past. |
Keywords
» Artificial intelligence » F1 score » Object detection » Semantic segmentation
