State of the Art in Monitoring Methane Emissions from Arctic-boreal Wetlands and Lakes

Abstract

Highlights What are the main findings? Arctic-boreal wetlands and lakes are major but highly uncertain methane sources Small lakes and winter emissions are poorly captured in current inventories. What is the implication of the main finding? Combining top-down and bottom-up methods reduces methane estimate uncertainty. New satellites and explainable AI can strengthen high-latitude methane budgets.Highlights What are the main findings? Arctic-boreal wetlands and lakes are major but highly uncertain methane sources Small lakes and winter emissions are poorly captured in current inventories. What is the implication of the main finding? Combining top-down and bottom-up methods reduces methane estimate uncertainty. New satellites and explainable AI can strengthen high-latitude methane budgets.Abstract Arctic-boreal wetlands and lakes are among the most significant and most uncertain natural sources of atmospheric methane. Rapid Arctic amplification, permafrost thaw, hydrological change, and increasing ecosystem productivity are expected to intensify methane emissions from high-latitude landscapes. Yet, significant uncertainties persist in quantifying their magnitude, seasonality, and spatial distribution. This review synthesizes the current state of the art in monitoring methane emissions from Arctic-boreal wetlands and lakes through complementary bottom-up and top-down approaches. We examine Earth observation (EO) capabilities, including optical, thermal infrared (TIR), and synthetic aperture radar (SAR) missions, as well as new emerging satellite platforms. We also assess in situ measurement networks, wetland and lake inventories, empirical and process-based models, and atmospheric inversion frameworks. Key gaps remain in representing small waterbodies, shoreline heterogeneity, winter emissions, inventory harmonization, and integration between atmospheric retrievals and surface-based flux models. Moreover, advances in multi-sensor data fusion, explainable artificial intelligence (XAI), physics-informed inversion methods, and geospatial foundation models offer strong potential to reduce these uncertainties. A coordinated integration of satellite observations, field measurements, and transparent modeling frameworks is essential to improve Arctic-boreal methane budgets and strengthen projections of climate feedback in a rapidly warming region.

Keywords

wetlands and lakes; Earth observation; remote sensing; methane monitoring; top-down and bottom-up approaches; Eddy covariance

Published in

Remote Sensing
2026, volume: 18, number: 6, article number: 926
Publisher: MDPI

SLU Authors

• Peichl, Matthias

  • Department of Forest Ecology and Management, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Earth Observation

Publication identifier

• DOI: https://doi.org/10.3390/rs18060926

Permanent link to this page (URI)

https://res.slu.se/id/publ/146699