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Contenuto fornito da Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
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Mapping forests: Verifying carbon offsetting with machine learning

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Manage episode 357964857 series 2954151
Contenuto fornito da Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.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

  continue reading

26 episodi

Artwork
iconCondividi
 
Manage episode 357964857 series 2954151
Contenuto fornito da Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.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

  continue reading

26 episodi

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