TY - JOUR
T1 - Hidden becomes clear : Optical remote sensing of vegetation reveals water table dynamics in northern peatlands
AU - Burdun, Iuliia
AU - Bechtold, Michel
AU - Aurela, Mika
AU - De Lannoy, Gabrielle
AU - Desai, Ankur R.
AU - Humphreys, Elyn
AU - Kareksela, Santtu
AU - Komisarenko, Viacheslav
AU - Liimatainen, Maarit
AU - Marttila, Hannu
AU - Minkkinen, Kari
AU - Nilsson, Mats B.
AU - Ojanen, Paavo
AU - Salko, Sini Selina
AU - Tuittila, Eeva Stiina
AU - Uuemaa, Evelyn
AU - Rautiainen, Miina
N1 - | openaire: EC/H2020/771049/EU//FREEDLES
Funding Information:
This study was mainly funded by the Academy of Finland (PEATSPEC, decision no 341963). This study has also received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 771049, MR). The text reflects only the authors' view, and the Agency is not responsible for any use that may be made of the information it contains. We thank the Estonian Weather Service for providing us with the data for EE_MAN and EE_LIN peatlands. ARD acknowledge support for US-Los from the US Department of Energy Ameriflux Network Management Project. EU was funded by Mobilitas+ program grant no. MOBERC34. HM acknowledged support for the Pallas site from Maa- ja Vesitekniikan tuki ry, Academy of Finland (grants 347704, 346163, 347663) and Freshwater competence centre. ML acknowledges support for Ruukki site from the Centre for Economic Development, Transport and the Environment, Ministry of Agriculture and Forestry of Finland, Suoviljelysyhdistys and Kone Foundation. MB acknowledges funding from the Research Foundation - Flanders (FWO) (FWO.G095720N). EST acknowledge support from Academy of Finland Flagship funding for ACCC (grant No. 337550) and for the BorPeat project (330840) and infrastructure (337064, 345527). SK's work and the Finnish peatland restoration monitoring network were funded by the Finnish Ministry of the Environment. CA-MER research was conducted with logistical support from the National Capital Commission and financial support from the Ontario Ministry of Environment, Conservation and Parks. We express our gratitude to the anonymous reviewers who helped us to improve the clarity, precision, and relevance of the article.
Funding Information:
This study was mainly funded by the Academy of Finland (PEATSPEC, decision no 341963 ). This study has also received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 771049 , MR). The text reflects only the authors' view, and the Agency is not responsible for any use that may be made of the information it contains. We thank the Estonian Weather Service for providing us with the data for EE_MAN and EE_LIN peatlands. ARD acknowledge support for US-Los from the US Department of Energy Ameriflux Network Management Project. EU was funded by Mobilitas+ program grant no. MOBERC34. HM acknowledged support for the Pallas site from Maa- ja Vesitekniikan tuki ry, Academy of Finland (grants 347704 , 346163 , 347663 ) and Freshwater competence centre. ML acknowledges support for Ruukki site from the Centre for Economic Development, Transport and the Environment, Ministry of Agriculture and Forestry of Finland , Suoviljelysyhdistys and Kone Foundation. MB acknowledges funding from the Research Foundation - Flanders (FWO) ( FWO.G095720N ). EST acknowledge support from Academy of Finland Flagship funding for ACCC (grant No. 337550 ) and for the BorPeat project ( 330840 ) and infrastructure ( 337064 , 345527 ). SK's work and the Finnish peatland restoration monitoring network were funded by the Finnish Ministry of the Environment. CA-MER research was conducted with logistical support from the National Capital Commission and financial support from the Ontario Ministry of Environment, Conservation and Parks. We express our gratitude to the anonymous reviewers who helped us to improve the clarity, precision, and relevance of the article.
Publisher Copyright:
© 2023
PY - 2023/10/1
Y1 - 2023/10/1
N2 - The water table and its dynamics are one of the key variables that control peatland greenhouse gas exchange. Here, we tested the applicability of the Optical TRApezoid Model (OPTRAM) to monitor the temporal fluctuations in water table over intact, restored (previously forestry-drained), and drained (under agriculture) northern peatlands in Finland, Estonia, Sweden, Canada, and the USA. More specifically, we studied the potential and limitations of OPTRAM using water table data from 2018 through 2021, across 53 northern peatland sites, i.e., covering the largest geographical extent used in OPTRAM studies so far. For this, we calculated OPTRAM based on Sentinel-2 data with the Google Earth Engine cloud platform. First, we found that the choice of vegetation index utilised in OPTRAM does not significantly affect OPTRAM performance in peatlands. Second, we revealed that the tree cover density is a major factor controlling the sensitivity of OPTRAM to water table dynamics in peatlands. Tree cover density greater than 50% led to a clear decrease in OPTRAM performance. Finally, we demonstrated that the relationship between water table and OPTRAM often disappears when WT deepens (ranging between 0 to −100 cm, depending on the site location). We identified that the water table where OPTRAM ceases to be sensitive to variations is highly site-specific. Overall, our results support the application of OPTRAM to monitor water table dynamics in intact and restored northern peatlands with low tree cover density (below 50%) when the water table varies from shallow to moderately deep. Our study makes significant steps towards the broader implementation of optical remote sensing data for monitoring peatlands subsurface moisture conditions over the northern region.
AB - The water table and its dynamics are one of the key variables that control peatland greenhouse gas exchange. Here, we tested the applicability of the Optical TRApezoid Model (OPTRAM) to monitor the temporal fluctuations in water table over intact, restored (previously forestry-drained), and drained (under agriculture) northern peatlands in Finland, Estonia, Sweden, Canada, and the USA. More specifically, we studied the potential and limitations of OPTRAM using water table data from 2018 through 2021, across 53 northern peatland sites, i.e., covering the largest geographical extent used in OPTRAM studies so far. For this, we calculated OPTRAM based on Sentinel-2 data with the Google Earth Engine cloud platform. First, we found that the choice of vegetation index utilised in OPTRAM does not significantly affect OPTRAM performance in peatlands. Second, we revealed that the tree cover density is a major factor controlling the sensitivity of OPTRAM to water table dynamics in peatlands. Tree cover density greater than 50% led to a clear decrease in OPTRAM performance. Finally, we demonstrated that the relationship between water table and OPTRAM often disappears when WT deepens (ranging between 0 to −100 cm, depending on the site location). We identified that the water table where OPTRAM ceases to be sensitive to variations is highly site-specific. Overall, our results support the application of OPTRAM to monitor water table dynamics in intact and restored northern peatlands with low tree cover density (below 50%) when the water table varies from shallow to moderately deep. Our study makes significant steps towards the broader implementation of optical remote sensing data for monitoring peatlands subsurface moisture conditions over the northern region.
KW - Bogs
KW - Fens
KW - Sentinel-2
KW - Soil moisture
KW - Sphagnum
KW - SWIR
KW - Vegetation cover
KW - Wetland
UR - http://www.scopus.com/inward/record.url?scp=85165944968&partnerID=8YFLogxK
U2 - 10.1016/j.rse.2023.113736
DO - 10.1016/j.rse.2023.113736
M3 - Article
AN - SCOPUS:85165944968
SN - 0034-4257
VL - 296
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
M1 - 113736
ER -