Potential for using remote sensing to estimate carbon fluxes across northern peatlands – A review

Abstract

Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use change. Current field-based methods of estimating annual carbon exchange between peatlands and the atmosphere include flux chambers and eddy covariance towers. However, remote sensing has several advantages over these traditional approaches in terms of cost, spatial coverage and accessibility to remote locations. In this paper, we outline the basic principles of using remote sensing to estimate ecosystem carbon fluxes and explain the range of satellite data available for such estimations, considering the indices and models developed to make use of the data. Past studies, which have used remote sensing data in comparison with ground-based calculations of carbon fluxes over Northern peatland landscapes, are discussed, as well as the challenges of working with remote sensing on peatlands. Finally, we suggest areas in need of future work on this topic. We conclude that the application of remote sensing to models of carbon fluxes is a viable research method over Northern peatlands but further work is needed to develop more comprehensive carbon cycle models and to improve the long-term reliability of models, particularly on peatland sites undergoing restoration.

Changes in carbon flux and spectral reflectance of Sphagnum mosses as a result of simulated drought

“…The success of the NDVI in matching the GPP results from group E is encouraging for researchers who use spectral indices to gain information about peat bogs from remote sensing. The NDVI is widely used as a method of estimating plant health from remote sensing(Lees et al, 2018), and our work with Sphagnum proves that this index can be a useful tool in peat bog ecosystems, particularly in hot and dry seasons when drought damage is predicted.ACKNOWLEDGEMENTSThanks are due to the Forsinard Flows RSPB reserve for allowing us to collect Sphagnum samples for this work and also to Stephen Fry and Vicky Russell at the Chobham Common NNR for allowing us to collect a few Sphagnum samples for sampling and storage methods testing.Thanks to Mike Lees for making the 40 Sphagnum sample collars.Thanks to Mhairi Coyle for reviewing the manuscript, and to the two anonymous reviewers for their helpful comments.AUTHORS' CONTRIBUTIONSKJL led the experimental work of this project, the data analysis, and the drafting of the manuscript. JMC contributed particularly to the experiment design and statistical analysis of the study, and RREA was instrumental in site selection and sample collection.…”

“…The normalized difference vegetation index (NDVI), which we consider in this study, is a widely used spectral index that can be easily calculated from satellite or unmanned aerial vehicle data. Validation of this in the laboratory is particularly useful for researchers using remote sensing over peatlands at large scales (Lees, Quaife, Artz, Khomik, & Clark, 2018).…”

Temporal Variation of Ecosystem Scale Methane Emission From a Boreal Fen in Relation to Temperature, Water Table Position, and Carbon Dioxide Fluxes

“…In such models the methane production typically depends on the available carbon pool development (Li et al, 2016;Oikawa et al, 2017;Raivonen et al, 2017;Tian et al, 2010;Walter & Heimann, 2000;Wania et al, 2010;Watts et al, 2013;Zhuang et al, 2004), in line with our findings. Also, the possibility to remotely observe abiotic and biotic parameters controlling the carbon dioxide exchange of wetland ecosystems (Aurela et al, 2004;Lees et al, 2018;Rinne et al, 2009) may be linked to methane emissions from northern peatlands. However, in order to better understand the dynamic links between carbon dioxide fluxes and methane emission, measurements of seasonal development of substrate and dissolved methane pools within anoxic peat layers would be crucial.…”

Long-Term Peatland Condition Assessment via Surface Motion Monitoring Using the ISBAS DInSAR Technique over the Flow Country, Scotland

“…Given the vast extent of these peatlands and their dynamic nature, any monitoring system should be continuous over space and time [22]. Various methods of surveying peatland surface motion, such as site surveys (PVC tubes, Levelling and Differential Global Positioning system (DGPS), terrestrial LiDAR) and remote sensing via airborne platforms, are limited [9].…”