In this Smart Forests Radio episode, we speak to Professor David Coomes, Director of
conservation
.cam.ac.uk/">the University of Cambridge Conservation Research Institute (UCCRI). David uses computational technologies, from lidar to machine-learning algorithms, to estimate differences in
carbon
storage over time and across vast landscapes in response to environmental changes. Reflecting on his forest ecology research practice as it intersects with digital technologies, he discusses the importance of maintaining traditional field surveys in the world of high-resolution remote-
sensing
technologies. David also reminds us that, beyond the monetary
value
associated with the
carbon
market, forests have multiple other values, including their role in combating climate change, increasing
biodiversity
, supporting local livelihoods, and more.
Interviewers: Jennifer Gabrys and Trishant Simlai
Producer: Harry Murdoch
Listen on
podcasts
.apple.com/gb/podcast/david-coomes-seeing-the-forest-through-the-
carbon
/id1642535927?i=1000634868311">Apple,
podcasts
.google.com/feed/aHR0cHM6Ly9mZWVkLnBvZGJlYW4uY29tL3NtYXJ0Zm9yZXN0cy9mZWVkLnhtbA/episode/c21hcnRmb3Jlc3RzLnBvZGJlYW4uY29tLzBiZDM5MmQwLThlNTktMzNkMC1iNzAzLTAyMjRhY2ZlNDVhOQ?sa=X&ved=0CAUQkfYCahcKEwjwnfrgy8WCAxUAAAAAHQAAAAAQLA">Google, and Spotify.
This radio episode was produced by the Smart Forests project funded by the European Research Council. Smart Forests is led by Professor Jennifer Gabrys and is based in the Department of Sociology at the University of Cambridge.
Smart Forests Atlas materials are free to use for non-commercial purposes (with attribution) under a CC BY-NC-SA 4.0 license. To cite this radio episode: Coomes, David, Jennifer Gabrys, and Trishant Simlai, "David Coomes: Seeing the Forest through the Carbon", Smart Forests Atlas (2023), https://atlas.smartforests.net/en/radio/david-coomes. DOI: 10.5281/zenodo.10686763.
Header image: Comparison of regional forest gain maps. Image source: Du et al. "Mapping Annual Global Forest Gain From 1983 to 2021 With Landsat Imagery." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 16 (2023): 4195-4204 [figure]. Retrieved 13 November 2023, from https://ieeexplore.ieee.org/abstract/document/10103610