Project highlights

  • Understanding carbon sequestration in forested tropical peatlands
  • Evidence-based and transparent approach to validating carbon credits schemes
  • Use of novel technology for new insight and data-driven decision making


Tropical forests are recognised as globally important carbon stores, sequestering significant quantities of atmospheric carbon dioxide aboveground in the vegetation. Less well understood are tropical peatlands, which not only sequester substantial carbon in plant biomass, but also can store carbon to significant depth in the soil and are amongst the most carbon dense ecosystems on Earth. Tropical peatland ecosystems can continue to sequester carbon while they remain flooded, but many are frequently drained for agricultural production. Both tropical forests and peatlands are under substantial threats from land use and climate change – maintaining and enhancing these carbon stores is crucial for climate change mitigation.

To offset their emissions, many businesses are investing in carbon credit schemes which focus on removing atmospheric carbon dioxide through planting trees and/or conserving and regenerating existing areas of forest and peatland. Underpinning all such schemes is the need to accurately quantify carbon storage baselines, and to carry out regular monitoring to ensure the additionality and permanence of stored carbon.

Conventional approaches for achieving this are often labour intensive and expensive, requiring ongoing measurements in the field. A range of new remote sensing technologies, when combined with a comprehensive understanding of tropical forest and tropical peatland ecosystem dynamics, have the potential to develop new approaches for validating such schemes. Working to meet the needs of businesses developing carbon credits, the project proposes to develop novel methodologies for cost-effective monitoring of carbon storage and sequestration in tropical forests and peatlands. In the long-term this will help businesses by allowing them to scale their projects and achieve cost-savings through monitoring projects more rapidly. This will be achieved through a combination of synthesising existing datasets, developing new models, and through optional fieldwork primarily focussing on poorly mapped tropical peatlands in Central America (Panama and Costa Rica).


Cranfield University


  • Climate and Environmental Sustainability
  • Organisms and Ecosystems


Project investigator


How to apply


The project will review how current carbon credit schemes quantify carbon storage and the monitoring requirements that are in place to measure success. This will involve investigation of sources of error in the datasets and methodology used to validate how conservation and regeneration programmes affect the amount of sequestered carbon alongside how baseline carbon stocks are determined. New approaches, using remote sensing technology combined with field measurements, will developed for measuring above and belowground carbon storage. This will be achieved through identification of a set of target variables for modelling forest peatland carbon that can be measured from space. The approaches developed will be critically evaluated for their accuracy and efficiency compared to existing technology and how they can be scaled into operational tools for validating carbon credit schemes. This may be supported by optional fieldwork to generate new measurements in poorly mapped peatland regions (in particular across Central America).

Training and skills

Additional training in will be provided for image processing and machine learning through taught short courses in advanced remote sensing delivered at Cranfield University. Further training will also be made available in common ecological measurement techniques used to quantify forest and peat carbon storage.

Partners and collaboration

This project has been co-developed with the help of industry leading carbon credit agencies to reflect the growing need for accountability in the trading of carbon credits and the long-term yield of investments in regeneration and conservation programmes. The student benefit from supervisor links with industry and the wider scientific community involved in the mapping of global carbon sequestered in tropical forested peatlands.

Further details

To apply please visit:

Possible timeline

Year 1

Review of current carbon credit schemes, monitoring requirements, sources of error and estimation of baseline carbon sequestration.

Year 2

Field data collection and development of novel technologies for monitoring tropical peatland forest.

Year 3

Critical evaluation of new approaches for validating carbon credits.

The standard model at Cranfield University is the production of peer-reviewed papers during the course of the studentship.  Placements will be for periods of between 1 week to 3.

Further reading

Dargie, G.C., Lewis, S.L., Lawson, I.T., Mitchard, E.T., Page, S.E., Bocko, Y.E. and Ifo, S.A., 2017. Age, extent and carbon storage of the central Congo Basin peatland complex. Nature542(7639), pp.86-90.

Draper, F.C., Roucoux, K.H., Lawson, I.T., Mitchard, E.T., Coronado, E.N.H., Lähteenoja, O., Montenegro, L.T., Sandoval, E.V., Zaráte, R. and Baker, T.R., 2014. The distribution and amount of carbon in the largest peatland complex in Amazonia. Environmental Research Letters9(12), p.124017.


International travel for the purposes of field work (likely focussing on easily reached but poorly mapped peatlands in Central America , specifically Costa Rica and Panama) may be affected by current and future changes in government policy relating to outbreaks of COVID-19. This will be mitigated through use of alternative datasets already collected as part of prior work or by national agencies and NGOs. The topic can also be shifted to focus more on the remote retrieval of peatland forest attributes in different regions, including the UK. The is also a risk to student engagement and involvement in conferences and with industry collaborators. This risk will be mitigated using online resources and wider support from Cranfield University and CENTA.