Diego Saez Gil - How Pachama Uses Tech to Solve Climate Change

TL;DR

Pachama uses remote sensing (lidar, satellite imagery) and convolutional neural networks to verify carbon storage in forests, reducing certification costs and increasing transparency. The company then operates a marketplace that directly connects forest-project developers with corporate buyers of carbon credits.

Key insights

• Less than 2% of the $80 billion flowing annually into carbon markets goes to forest projects, mainly because certification is slow (2 years) and expensive ($100,000–$400,000) due to manual tree-counti
• Pachama trains deep learning models (convolutional neural networks) on lidar point clouds and satellite data, achieving <15% error in estimating forest carbon stocks when validated against ground-trut
• The company plans to use NASA’s GEDI lidar data (released November 2018) to expand its model globally, enabling planet-wide carbon monitoring.