High-resolution mapping of peatland CO2 fluxes using drone multispectral images

Abstract

Large-scale mapping of ecosystem CO₂ fluxes between land and atmosphere is a challenging task. Typically, it is based on multispectral satellite images with low (∼250 m) to moderate ground pixel resolution (∼20 m). However, in small, fine-scale ecosystems such as peatlands, the representation of CO₂ fluxes heterogeneity across microhabitats is very limited by the ground pixel resolution of satellites. In this context, high ground pixel resolution of drone imagery might prove useful, alone or in synergy with large-scale satellite data, to better support field investigations and carry out rapid carbon assessment at a relatively low cost. Here, we carried out a survey of CO₂ exchanges over 4 ha of peatland during the growing season using chamber measurements, as well as simultaneous aerial multispectral orthophotographs acquired by drone. To assess the ability of drone multispectral images at providing relevant information for the prediction of CO₂ fluxes, we developed robust linear regression models and used drone imagery to map net ecosystem exchange, ecosystem respiration and gross ecosystem productivity at a very fine scale (∼5 cm). Our predictions were in the range of those found in the satellite remote sensing literature with errors lesser than 0.5 gCO₂.m⁻².h⁻¹. Our study offers new opportunities to refine large scale satellite assessment of CO₂ fluxes on small, valuable peatland areas that can be easily flown over by drone. Moreover, we believe that our results will be of interest for the scientific community as well as environmental managers wishing to carry out rapid carbon assessments of peatlands.