How remote sensing contributes to flux upscaling in natural bog ecosystems – a case study in Estonia

The research potential to investigate and monitor a peatland site is often limited by difficult accessibility to the site, and a heterogeneous surface with diverse topography, hydrological features, and vegetation. Satellite remote sensing (RS) methods offer the advantage of past-to-present repeating cover research areas compared to field studies. Our case study examined the potential usability of applied satellite RS methods to determine greenhouse gas (GHG) fluxes in natural peatlands. Specifically, we tested several landscape indices on their correlation to GHG fluxes and basic environmental parameters.
The field campaign was carried out from 13.7.2018 to 24.7.2019 in a natural raised bog covered with young pine trees in central Estonia, measuring carbon dioxide (CO₂) and methane (CH₄) fluxes with manual static chambers, soil temperature, soil moisture, and the water table. The measured air temperature was provided by the nearest meteorological station.  

Land surface temperature (LST) was calculated from satellite Landsat-8 data using open-source code in Google Earth Engine cloud-based service. Normalized Difference Vegetation Index (NDVI), Water Index (NDWI), and Snow Index (NDSI) were calculated from Sentinel-2 data. The relationships between LST and indices with field-measured parameters were explored. Peatland site land covers were mapped using Sentinel-2 data supervised classification into dense trees, sphagnum mosses and grasses, and open water classes. The dynamics of open water locations were estimated based on the distribution of land covers for each month of study period. 

Our correlation analysis reflected different in-situ GHG dynamics throughout the investigated period and the micro-spatial heterogeneity of the land surface, with naturally wetter and dryer spots. The preliminary results show a close relationship between the in-situ measured CO₂ fluxes and LST. The CO₂ fluxes were further correlated with CH₄ fluxes. Distribution of land covers from RS can significantly improve the GHG flux upscaling process. Thus, the obtained results can further help to identify locations in peatlands with the highest risks and priorities to provide detailed in situ monitoring.

Acknowledgements:

This work was supported by the Ministry of Education, Youth and Sports of CR within the CzeCOS program (grant number LM2023048) and project AdAgriF - Advanced methods of greenhouse gases emission reduction and sequestration in agriculture and forest landscape for climate change mitigation (CZ.02.01.01/00/22_008/0004635).