Articles | Volume 19, issue 10
https://doi.org/10.5194/tc-19-4585-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-19-4585-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Oct 2025
Research article |
| 16 Oct 2025
| 16 Oct 2025
UAV LiDAR surveys and machine learning improve snow depth and water equivalent estimates in boreal landscapes
Maiju Ylönen
CORRESPONDING AUTHOR
Water, Energy and Environmental Engineering Research Unit, University of Oulu, 90014, Oulu, Finland
Hannu Marttila
Water, Energy and Environmental Engineering Research Unit, University of Oulu, 90014, Oulu, Finland
Joschka Geissler
Faculty of Environment and Natural Sciences, University of Freiburg, 79098 Freiburg, Germany
Anton Kuzmin
Department of Geographical and Historical Studies, University of Eastern Finland, 80101, Joensuu, Finland
Pasi Korpelainen
Department of Geographical and Historical Studies, University of Eastern Finland, 80101, Joensuu, Finland
Timo Kumpula
Department of Geographical and Historical Studies, University of Eastern Finland, 80101, Joensuu, Finland
Pertti Ala-Aho
Water, Energy and Environmental Engineering Research Unit, University of Oulu, 90014, Oulu, Finland
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Eeva Järvi-Laturi, Teemu Tahvanainen, Eero Koskinen, Efrén López-Blanco, Juho Lämsä, Hannu Marttila, Mikhail Mastepanov, Riku Paavola, Maria Väisänen, and Torben R. Christensen
Biogeosciences, 22, 6343–6367, https://doi.org/10.5194/bg-22-6343-2025, https://doi.org/10.5194/bg-22-6343-2025, 2025
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Our research investigates how plant community composition influences methane emissions in a northern boreal rich fen. We measured methane fluxes year-round using manual chambers across 36 plots. Our findings suggest that sedges, particularly Carex rostrata, significantly impact the fluxes throughout the year. This study enhances our understanding of vegetation-driven methane emissions, providing valuable insights for predicting future changes in peatland methane emissions.
Alexander Störmer, Timo Kumpula, Miguel Villoslada, Pasi Korpelainen, Henning Schumacher, and Benjamin Burkhard
The Cryosphere, 19, 3949–3970, https://doi.org/10.5194/tc-19-3949-2025, https://doi.org/10.5194/tc-19-3949-2025, 2025
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Snow has a major impact on palsa dynamics, yet our understanding of its distribution at the small scale remains limited. We used unoccupied aerial system (UAS) light detection and ranging (lidar) and ground truth data in combination with machine learning to model snow distribution at three palsa sites. We identified extremes in snow depth corresponding to palsa topography, providing insights into the influence of the distribution on their dynamics. The results demonstrate the usability of machine learning and UAS lidar for small-scale snow distribution mapping.
Shaakir Shabir Dar, Eric Klein, Pertti Ala-aho, Hannu Marttila, Sonja Wahl, and Jeffrey Welker
EGUsphere, https://doi.org/10.5194/egusphere-2025-2724, https://doi.org/10.5194/egusphere-2025-2724, 2025
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Using laser based instruments, we observed snow turning directly to vapor inside the pack and at its surface. In cold, calm weather vapor moves slowly upward; on warmer, windy days air pushes vapor deeper into the snow. These dynamics control snow loss and must be included in hydrological and climate models.
Teemu Juselius-Rajamäki, Sanna Piilo, Susanna Salminen-Paatero, Emilia Tuomaala, Tarmo Virtanen, Atte Korhola, Anna Autio, Hannu Marttila, Pertti Ala-Aho, Annalea Lohila, and Minna Väliranta
Biogeosciences, 22, 3047–3071, https://doi.org/10.5194/bg-22-3047-2025, https://doi.org/10.5194/bg-22-3047-2025, 2025
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Vegetation can be used to infer the potential climate feedback of peatlands. New studies have shown the recent expansion of peatlands, but their plant community succession has not been studied. Although generally described as dry bog-type vegetation, our results show that peatland margins in a subarctic fen began as wet fen with high methane emissions and shifted to bog-type peatland area only after the Little Ice Age. Thus, they have acted as a carbon source for most of their history.
Filip Muhic, Pertti Ala-Aho, Matthias Sprenger, Björn Klöve, and Hannu Marttila
Hydrol. Earth Syst. Sci., 28, 4861–4881, https://doi.org/10.5194/hess-28-4861-2024, https://doi.org/10.5194/hess-28-4861-2024, 2024
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Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
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We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Clemens von Baeckmann, Annett Bartsch, Helena Bergstedt, Aleksandra Efimova, Barbara Widhalm, Dorothee Ehrich, Timo Kumpula, Alexander Sokolov, and Svetlana Abdulmanova
The Cryosphere, 18, 4703–4722, https://doi.org/10.5194/tc-18-4703-2024, https://doi.org/10.5194/tc-18-4703-2024, 2024
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Lakes are common features in Arctic permafrost areas. Land cover change following their drainage needs to be monitored since it has implications for ecology and the carbon cycle. Satellite data are key in this context. We compared a common vegetation index approach with a novel land-cover-monitoring scheme. Land cover information provides specific information on wetland features. We also showed that the bioclimatic gradients play a significant role after drainage within the first 10 years.
Marco M. Lehmann, Josie Geris, Ilja van Meerveld, Daniele Penna, Youri Rothfuss, Matteo Verdone, Pertti Ala-Aho, Matyas Arvai, Alise Babre, Philippe Balandier, Fabian Bernhard, Lukrecija Butorac, Simon Damien Carrière, Natalie C. Ceperley, Zuosinan Chen, Alicia Correa, Haoyu Diao, David Dubbert, Maren Dubbert, Fabio Ercoli, Marius G. Floriancic, Teresa E. Gimeno, Damien Gounelle, Frank Hagedorn, Christophe Hissler, Frédéric Huneau, Alberto Iraheta, Tamara Jakovljević, Nerantzis Kazakis, Zoltan Kern, Karl Knaebel, Johannes Kobler, Jiří Kocum, Charlotte Koeber, Gerbrand Koren, Angelika Kübert, Dawid Kupka, Samuel Le Gall, Aleksi Lehtonen, Thomas Leydier, Philippe Malagoli, Francesca Sofia Manca di Villahermosa, Chiara Marchina, Núria Martínez-Carreras, Nicolas Martin-StPaul, Hannu Marttila, Aline Meyer Oliveira, Gaël Monvoisin, Natalie Orlowski, Kadi Palmik-Das, Aurel Persoiu, Andrei Popa, Egor Prikaziuk, Cécile Quantin, Katja T. Rinne-Garmston, Clara Rohde, Martin Sanda, Matthias Saurer, Daniel Schulz, Michael Paul Stockinger, Christine Stumpp, Jean-Stéphane Venisse, Lukas Vlcek, Stylianos Voudouris, Björn Weeser, Mark E. Wilkinson, Giulia Zuecco, and Katrin Meusburger
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-409, https://doi.org/10.5194/essd-2024-409, 2024
Revised manuscript accepted for ESSD
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This study describes a unique large-scale isotope dataset to study water dynamics in European forests. Researchers collected data from 40 beech and spruce forest sites in spring and summer 2023, using a standardized method to ensure consistency. The results show that water sources for trees change between seasons and vary by tree species. This large dataset offers valuable information for understanding plant water use, improving ecohydrological models, and mapping water cycles across Europe.
Danny Croghan, Pertti Ala-Aho, Jeffrey Welker, Kaisa-Riikka Mustonen, Kieran Khamis, David M. Hannah, Jussi Vuorenmaa, Bjørn Kløve, and Hannu Marttila
Hydrol. Earth Syst. Sci., 28, 1055–1070, https://doi.org/10.5194/hess-28-1055-2024, https://doi.org/10.5194/hess-28-1055-2024, 2024
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The transport of dissolved organic carbon (DOC) from land into streams is changing due to climate change. We used a multi-year dataset of DOC and predictors of DOC in a subarctic stream to find out how transport of DOC varied between seasons and between years. We found that the way DOC is transported varied strongly seasonally, but year-to-year differences were less apparent. We conclude that the mechanisms of transport show a higher degree of interannual consistency than previously thought.
Jari-Pekka Nousu, Matthieu Lafaysse, Giulia Mazzotti, Pertti Ala-aho, Hannu Marttila, Bertrand Cluzet, Mika Aurela, Annalea Lohila, Pasi Kolari, Aaron Boone, Mathieu Fructus, and Samuli Launiainen
The Cryosphere, 18, 231–263, https://doi.org/10.5194/tc-18-231-2024, https://doi.org/10.5194/tc-18-231-2024, 2024
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The snowpack has a major impact on the land surface energy budget. Accurate simulation of the snowpack energy budget is difficult, and studies that evaluate models against energy budget observations are rare. We compared predictions from well-known models with observations of energy budgets, snow depths and soil temperatures in Finland. Our study identified contrasting strengths and limitations for the models. These results can be used for choosing the right models depending on the use cases.
Anssi Rauhala, Leo-Juhani Meriö, Anton Kuzmin, Pasi Korpelainen, Pertti Ala-aho, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
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Snow conditions in the Northern Hemisphere are rapidly changing, and information on snow depth is important for decision-making. We present snow depth measurements using different drones throughout the winter at a subarctic site. Generally, all drones produced good estimates of snow depth in open areas. However, differences were observed in the accuracies produced by the different drones, and a reduction in accuracy was observed when moving from an open mire area to forest-covered areas.
Leo-Juhani Meriö, Anssi Rauhala, Pertti Ala-aho, Anton Kuzmin, Pasi Korpelainen, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4363–4380, https://doi.org/10.5194/tc-17-4363-2023, https://doi.org/10.5194/tc-17-4363-2023, 2023
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Information on seasonal snow cover is essential in understanding snow processes and operational forecasting. We study the spatiotemporal variability in snow depth and snow processes in a subarctic, boreal landscape using drones. We identified multiple theoretically known snow processes and interactions between snow and vegetation. The results highlight the applicability of the drones to be used for a detailed study of snow depth in multiple land cover types and snow–vegetation interactions.
Mariana Verdonen, Alexander Störmer, Eliisa Lotsari, Pasi Korpelainen, Benjamin Burkhard, Alfred Colpaert, and Timo Kumpula
The Cryosphere, 17, 1803–1819, https://doi.org/10.5194/tc-17-1803-2023, https://doi.org/10.5194/tc-17-1803-2023, 2023
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The study revealed a stable and even decreasing thickness of thaw depth in peat mounds with perennially frozen cores, despite overall rapid permafrost degradation within 14 years. This means that measuring the thickness of the thawed layer – a commonly used method – is alone insufficient to assess the permafrost conditions in subarctic peatlands. The study showed that climate change is the main driver of these permafrost features’ decay, but its effect depends on the peatland’s local conditions.
Joschka Geissler, Christoph Mayer, Juilson Jubanski, Ulrich Münzer, and Florian Siegert
The Cryosphere, 15, 3699–3717, https://doi.org/10.5194/tc-15-3699-2021, https://doi.org/10.5194/tc-15-3699-2021, 2021
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The study demonstrates the potential of photogrammetry for analyzing glacier retreat with high spatial resolution. Twenty-three glaciers within the Ötztal Alps are analyzed. We compare photogrammetric and glaciologic mass balances of the Vernagtferner by using the ELA for our density assumption and an UAV survey for a temporal correction of the geodetic mass balances. The results reveal regions of anomalous mass balance and allow estimates of the imbalance between mass balances and ice dynamics.
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Short summary
We collected snow depth maps four times during the winter from two different sites and used them as input for a model to predict daily snow depth and snow water equivalent (SWE). Our results show similar snow depth patterns at different sites, with snow depths being the highest in forests and forest gaps and the lowest in open areas. The results can extend operational snow course measurements and their temporal and spatial coverage, helping hydrological forecasting and water resource management.
We collected snow depth maps four times during the winter from two different sites and used them...
