University of Oulu

Burdun, Iuliia, Michel Bechtold, Mika Aurela, Gabrielle De Lannoy, Ankur R. Desai, Elyn Humphreys, Santtu Kareksela, et al. “Hidden Becomes Clear: Optical Remote Sensing of Vegetation Reveals Water Table Dynamics in Northern Peatlands.” Remote Sensing of Environment 296 : 113736.

Hidden becomes clear : optical remote sensing of vegetation reveals water table dynamics in northern peatlands

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Author: Burdun, Iuliia1; Bechtold, Michel2; Aurela, Mika3;
Organizations: 1Aalto University, School of Engineering, P.O. Box 14100, FI-00076 Aalto, Finland
2KU Leuven, Heverlee, Belgium
3Finnish Meteorological Institute, Helsinki, Finland
4University of Wisconsin-Madison, Madison, USA
5Carleton University, Department of Geography & Environmental Studies, Ottawa, Canada
6Metsähallitus, Jyväskylä, Finland
7University of Tartu, Tartu, Estonia
8Ghent University, Ghent, Belgium
9University of Oulu, Oulu, Finland
10Natural Resources Institute Finland, Oulu, Finland
11University of Helsinki, Department of Forest Sciences, Helsinki, Finland
12Swedish University of Agricultural Sciences, Umeå, Sweden
13University of Eastern Finland, School of Forest Sciences, Joensuu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 8.2 MB)
Persistent link:
Language: English
Published: Elsevier, 2023
Publish Date: 2023-10-25


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.

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Series: Remote sensing of environment
ISSN: 0034-4257
ISSN-E: 1879-0704
ISSN-L: 0034-4257
Volume: 296
Article number: 113736
DOI: 10.1016/j.rse.2023.113736
Type of Publication: A1 Journal article – refereed
Field of Science: 1172 Environmental sciences
Funding: 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). ARD acknowledge support for US-Los from the US Department of Energy Ameriflux Network Management Project. EU was funded by Estonian Research Agency’s grant no. PRG1764. 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, Niemi foundation, 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.
Academy of Finland Grant Number: 341963
Detailed Information: 341963 (Academy of Finland Funding decision)
347704 (Academy of Finland Funding decision)
346163 (Academy of Finland Funding decision)
347663 (Academy of Finland Funding decision)
337550 (Academy of Finland Funding decision)
330840 (Academy of Finland Funding decision)
337064 (Academy of Finland Funding decision)
345527 (Academy of Finland Funding decision)
Dataset Reference: Sentinel-2 data are available at The in situ WT datasets are available from the authors upon request. Code in Google Earth Engine to calculate OPTRAM_NDVI parameters for wet edge and dry edge in EE_MAN peatland.
Copyright information: © 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (