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Mapping forests: Verifying carbon offsetting with machine learning
Manage episode 357964857 series 2954151
内容由Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger提供。所有播客内容（包括剧集、图形和播客描述）均由 Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品，您可以按照此处概述的流程进行操作https://zh.player.fm/legal。
In this episode Heidi Hurst returns to talk to us about how in her current role at Pachama she is using the power of machine learning to fight climate change. She discusses her work in measuring the capacity of existing forests and reforestation projects using satellite imagery.
Episode Summary
1. The importance of carbon credits verification in mitigating climate change
2. How Pachama is using machine learning and satellite imagery to verify carbon projects
3. Three types of carbon projects: avoided deforestation, reforestation, and improved forest management
4. Challenges in using satellite imagery to measure the capacity of existing forests
5. The role of multispectral imaging in measuring density of forests
6. Challenges in collecting data from dense rainforests and weather obstructions
7. The impact of machine learning on scaling up carbon verification
8. Advancements in the field of satellite imaging, particularly in small satellite constellations
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