Cutting-edge climate research
Sylvera Research pioneers on-the-ground carbon measurement techniques to build the most accurate reference biomass dataset ever assembled. Reference data used to train transformative models estimate forest carbon with unprecedented accuracy worldwide. Learn how these insights can improve our understanding of how nature-based solutions mitigate climate change and unlock effective global policy to reach net zero goals.
The climate crisis needs better forest monitoring
Thriving forests are essential for limiting global heating. To better track forest emissions and hold the right people accountable, we need accurate, reliable, and up-to-date data. That’s where Sylvera comes in.
High uncertainties
Conventional methodologies of emissions calculations and earth observation methods rely on reference data with known significant inaccuracies.
Insufficient coverage
Limited data on the forest carbon cycle - geographically, and across ecosystems.
Inconsistencies
Data gaps, method variations, and reporting issues erode monitoring efforts.
Sensor technologies unlock powerful monitoring
We’ve pioneered the world’s most accurate measurements of above-ground biomass for forests.
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We’re now expanding our capabilities to collect calibration data for further carbon pools (below-ground biomass, soil, and others), and to validate the resulting models with direct measurements of carbon in the atmosphere.
We're seeking funding opportunities to make our proprietary data sets accessible and ensure this information is actionable for the widest possible audience.
We discovered two critical facts: carbon stocks have been significantly underestimated, and emissions from forest loss and degradation may be greater than what was previously thought.
Sylvera already uses cutting-edge laser scanning technology to collect this data on the ground.
Mozambique
In 2022, we partnered with the Government of Mozambique through the Monitoring, Reporting, and Verification Unit of the National Fund for Sustainable Development to produce a highly accurate 50,000-hectare map of the above-ground carbon stocks in Mozambique, using multi-scale lidar and machine learning. The data collection completed was equivalent to scanning seventy thousand football pitches, making
Our measurement system is underpinned by methods that are up to 13 times more accurate than conventional methodologies. Using these methods, we found classical approaches significantly underestimated the carbon stock of the sampled area. This was greatest for large trees (those above 40 cm in diameter), which only represent 10% of all trees in the study area by number yet make up 50% of the total carbon stock.
These findings will calibrate a state-of-the-art monitoring, reporting, and verification (MRV) system over the subtropical forests of Zambezia province and demonstrate that these forests are more valuable as carbon stores than previously thought. These results are currently being prepared for publication (Demol et al., in prep).
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Explore the map to see where we’ve been, and where we’re planning on sampling next.
We have built a team of experts, including a dedicated field science unit that collects calibration data on month-long expeditions in key forested areas around the world. This capability allows our in-house data scientists to build highly accurate machine learning models, integrating data from satellites and other sources, to accurately predict forest carbon stocks.
Dr Andrew Burt
Andrew heads Sylvera’s Field Data Science team. A remote sensing scientist and tropical forest ecologist, over the past decade he has helped to pioneer lidar-based methods for measuring forest structure and biomass.
Sophia Farrar
Sophia is responsible for the fundraising and scaling of field research through partnerships with foundations, international organizations, and governments. She has a background in building global, open-source datasets for humanitarian advocacy and action in the UN system.
Dr Christopher Walter
Chris leads the analysis of soil carbon and nutrient cycling in grasslands, forests, and agricultural systems. With a PhD in Biology, Chris has led continental-scale experiments to measure and model the effects of global climate change on soil carbon.
Gabija Bernotaite
Gabija is responsible for processing our lidar data. She has a background in computer science and brings a wealth of knowledge from her experience in developing time-sensitive and safety-critical algorithms to process lidar point clouds for autonomous vehicle applications.
Dr Robin Upham
Robin is responsible for developing research and analysis methods, with a particular focus on quantitative modeling and uncertainty quantification. With a PhD in Astrophysics, Robin brings experience from developing quantitative analysis methods for the ESA Euclid satellite mission.
Dr Miro Demol
Miro has a PhD focused on reducing uncertainties in terrestrial lidar-derived estimates of above-ground biomass and processes our lidar data at Sylvera. He has a background in bio-engineering and nature management, and tropical forestry.
Emily Morris
With a Master’s in Advanced Computer Science, Emily's previous work involved using machine learning for biodiversity modeling. At Sylvera, she works on data processing and modeling for various Field Data Science projects, including Peatlands, Regenerative agriculture, and Above-ground biomass.
Dr Beisit Luz Puma Vilca
Beisit leads the Sylvera field team and oversees field campaigns globally. Currently, she has been involved in campaigns in Peru, Brazil, Belize, Mozambique, Cameroon, and the United Kingdom. With a Ph.D. in Biology and over 13 years of experience, her primary research emphasis lies in plant ecophysiology. She has contributed significantly to the development and implementation of forest measurement protocols for carbon dynamics. To date, she has conducted ground measurements and collected terrestrial and airborne lidar data using drones and helicopters over different ecosystems such as tropical forests, woodlands and peatlands.
Chloe Sutcliffe
Chloe brings a rich background in ecological field research in Kenya, Madagascar, and Malawi. At Sylvera, she has collected terrestrial and airborne lidar data on complex field campaigns in Mozambique, Cameroon, and Peru, with a recent focus on leading Sylvera’s drone operations.
Beatriz Fernandes
Beatriz has a Master’s in Conservation Rural Development, and experience leading ecological field research and community development initiatives in Tanzania, Peru, and Cambodia. As part of the field team she collects airborne and terrestrial lidar data over different ecosystems.
Elise Elmendorp
Elise oversees the logistical, budgetary, and research operations of the Field Data Science team. With a Master’s in environmental management, she has substantial experience in stakeholder engagement and planning international field work across the globe.
Mikolaj Krzekotowski
With a Master's in Zoology, Mikolaj brings experience to the Field Data Science team from his previous position developing exhibitions at the Natural History Museum in London. As the field Research Technician, he is responsible for overseeing the maintenance and management of Sylvera's drones and sensing equipment, for operations in various challenging environments.
Pontus Nordin
Pontus leads Sylvera’s current research into the monitoring of peatland restoration. He has a background in particle physics and soil carbon and uses his interdisciplinary knowledge to develop new methods and sensors for Sylvera’s carbon monitoring efforts.
Dr Pedro Rodríguez-Veiga
Pedro has a PhD in Physical Geography, his research focuses on analyzing forest carbon dynamics using remote sensing technology. He has been a co-investigator on high-impact projects such as the ESA Biomass Climate Change Initiative (CCI+), the NERC-NCEO Carbon Cycle: Land, Atmosphere & Oceans Programme, and the UK Space Agency Forests 2020.
Mikolaj Krzekotowski
With a Master's in Zoology, Mikolaj brings experience to the Field Data Science team from his previous position developing exhibitions at the Natural History Museum in London. As the field Research Technician, he is responsible for overseeing the maintenance and management of Sylvera's drones and sensing equipment, for operations in various challenging environments.
Pontus Nordin
Pontus leads Sylvera’s current research into the monitoring of peatland restoration. He has a background in particle physics and soil carbon and uses his interdisciplinary knowledge to develop new methods and sensors for Sylvera’s carbon monitoring efforts.
Beatriz Fernandes
Beatriz has a Master’s in Conservation Rural Development, and experience leading ecological field research and community development initiatives in Tanzania, Peru, and Cambodia. As part of the field team she collects airborne and terrestrial lidar data over different ecosystems.
Emily Morris
With a Master’s in Advanced Computer Science, Emily's previous work involved using machine learning for biodiversity modeling. At Sylvera, she works on data processing and modeling for various Field Data Science projects, including Peatlands, Regenerative agriculture, and Above-ground biomass.
Dr Johannes Hansen
Johannes Hansen has a Ph.D. in Computational Mathematics and Geosciences with experience in Earth Observation (using SAR data in particular), physical modelling, and high-performance computing.
Dr Pedro Rodríguez-Veiga
Pedro has a PhD in Physical Geography, his research focuses on analyzing forest carbon dynamics using remote sensing technology. He has been a co-investigator on high-impact projects such as the ESA Biomass Climate Change Initiative (CCI+), the NERC-NCEO Carbon Cycle: Land, Atmosphere & Oceans Programme, and the UK Space Agency Forests 2020.
Dr Christopher Walter
Chris leads the analysis of soil carbon and nutrient cycling in grasslands, forests, and agricultural systems. With a PhD in Biology, Chris has led continental-scale experiments to measure and model the effects of global climate change on soil carbon.
Chloe Sutcliffe
Chloe brings a rich background in ecological field research in Kenya, Madagascar, and Malawi. At Sylvera, she has collected terrestrial and airborne lidar data on complex field campaigns in Mozambique, Cameroon, and Peru, with a recent focus on leading Sylvera’s drone operations.
Sophia Farrar
Sophia is responsible for the fundraising and scaling of field research through partnerships with foundations, international organizations, and governments. She has a background in building global, open-source datasets for humanitarian advocacy and action in the UN system.
Dr Beisit Luz Puma Vilca
Beisit leads the Sylvera field team and oversees field campaigns globally. Currently, she has been involved in campaigns in Peru, Brazil, Belize, Mozambique, Cameroon, and the United Kingdom. With a Ph.D. in Biology and over 13 years of experience, her primary research emphasis lies in plant ecophysiology. She has contributed significantly to the development and implementation of forest measurement protocols for carbon dynamics. To date, she has conducted ground measurements and collected terrestrial and airborne lidar data using drones and helicopters over different ecosystems such as tropical forests, woodlands and peatlands.
Elise Elmendorp
Elise oversees the logistical, budgetary, and research operations of the Field Data Science team. With a Master’s in environmental management, she has substantial experience in stakeholder engagement and planning international field work across the globe.
Dr Miro Demol
Miro has a PhD focused on reducing uncertainties in terrestrial lidar-derived estimates of above-ground biomass and processes our lidar data at Sylvera. He has a background in bio-engineering and nature management, and tropical forestry.
Dr Robin Upham
Robin is responsible for developing research and analysis methods, with a particular focus on quantitative modeling and uncertainty quantification. With a PhD in Astrophysics, Robin brings experience from developing quantitative analysis methods for the ESA Euclid satellite mission.
Gabija Bernotaite
Gabija is responsible for processing our lidar data. She has a background in computer science and brings a wealth of knowledge from her experience in developing time-sensitive and safety-critical algorithms to process lidar point clouds for autonomous vehicle applications.
Relevant publications
Discover relevant publications featuring the contributions of our team to academic literature.
