no code implementations • 26 Jan 2022 • Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Kenza Amara, Attila Steinegger, Ce Zhang, Xiaoxiang Zhu
The potential for impact and scale of leveraging advancements in machine learning and remote sensing technologies is promising but needs to be of high quality in order to replace the current forest stock protocols for certifications.
no code implementations • 23 Jul 2021 • Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Xiaoxiang Zhu, Ce Zhang
This proposal paper describes the first systematic comparison of forest carbon estimation from aerial imagery, satellite imagery, and ground-truth field measurements via deep learning-based algorithms for a tropical reforestation project.
