Articles | Volume 14, issue 11
https://doi.org/10.5194/essd-14-4967-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4967-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
11 Nov 2022
Data description paper |
| 11 Nov 2022
SiDroForest: a comprehensive forest inventory of Siberian boreal forest investigations including drone-based point clouds, individually labeled trees, synthetically generated tree crowns, and Sentinel-2 labeled image patches
Femke Geffen
CORRESPONDING AUTHOR
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Research Unit Potsdam, Germany
University of Potsdam, Institute of Biochemistry and Biology, Potsdam, Germany
Birgit Heim
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Research Unit Potsdam, Germany
Frederic Brieger
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Research Unit Potsdam, Germany
Carleton University, Department of Geography and Environmental Studies Ottawa, Canada
Rongwei Geng
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Research Unit Potsdam, Germany
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
University of the Chinese Academy of Sciences, Beijing, China
Iuliia A. Shevtsova
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Research Unit Potsdam, Germany
University of Potsdam, Institute of Biochemistry and Biology, Potsdam, Germany
Luise Schulte
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Research Unit Potsdam, Germany
University of Potsdam, Institute of Biochemistry and Biology, Potsdam, Germany
Simone M. Stuenzi
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Research Unit Potsdam, Germany
Humboldt-Universität zu Berlin, Geography Department, Unter den Linden, Berlin, Germany
Nadine Bernhardt
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Research Unit Potsdam, Germany
Julius Kühn-Institut Bundesforschungsinstitut für Kulturpflanzen, Quedlinburg, Germany
Elena I. Troeva
Institute for Biological Problems of the Cryolithozone, Russian Academy of Sciences, Siberian Branch, Yakutsk, Russia
Luidmila A. Pestryakova
North-Eastern Federal University of Yakutsk, Institute of Natural Sciences (NEFU), Yakutsk, Russia
Evgenii S. Zakharov
Institute for Biological Problems of the Cryolithozone, Russian Academy of Sciences, Siberian Branch, Yakutsk, Russia
North-Eastern Federal University of Yakutsk, Institute of Natural Sciences (NEFU), Yakutsk, Russia
Bringfried Pflug
German Aerospace Center (DLR), Berlin, Germany
Ulrike Herzschuh
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Research Unit Potsdam, Germany
University of Potsdam, Institute of Biochemistry and Biology, Potsdam, Germany
University of Potsdam, Institute of Environmental Science and Geography, Potsdam, Germany
Alfred Wegener Institute (AWI) Helmholtz Centre for Polar and Marine Research, Research Unit Potsdam, Germany
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Simeon Lisovski, Alexandra Runge, Iuliia Shevtsova, Nele Landgraf, Anne Morgenstern, Ronald Reagan Okoth, Matthias Fuchs, Nikolay Lashchinskiy, Carl Stadie, Alison Beamish, Ulrike Herzschuh, Guido Grosse, and Birgit Heim
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-36, https://doi.org/10.5194/essd-2023-36, 2023
Preprint under review for ESSD
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The Lena Delta is the largest river delta in the Arctic, and represents a biodiversity hotspot. Here, we describe multiple field datasets and a detailed habitat classification map for the Lena Delta. We present context and methods of these openly available datasets and show how they can improve our understanding of the rapidly changing Arctic tundra system.
Philip Meister, Anne Alexandre, Hannah Bailey, Philip Barker, Boris K. Biskaborn, Ellie Broadman, Rosine Cartier, Bernhard Chapligin, Martine Couapel, Jonathan R. Dean, Bernhard Diekmann, Poppy Harding, Andrew C. G. Henderson, Armand Hernandez, Ulrike Herzschuh, Svetlana S. Kostrova, Jack Lacey, Melanie J. Leng, Andreas Lücke, Anson W. Mackay, Eniko Katalin Magyari, Biljana Narancic, Cécile Porchier, Gunhild Rosqvist, Aldo Shemesh, Corinne Sonzogni, George E. A. Swann, Florence Sylvestre, and Hanno Meyer
Clim. Past Discuss., https://doi.org/10.5194/cp-2022-96, https://doi.org/10.5194/cp-2022-96, 2023
Preprint under review for CP
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Atoms of the element Oxygen exists in different varieties which have slightly different masses and behave differently in the global water cycle during e.g. rain formation and evaporation. Diatoms are microscopic algaea which use oxygen in building their shells and thereby store the oxygen signature of the water they live in. We have compiled and analyzed previously published data from diatoms from lake sediments around the globe and found common patterns suggesting a common climate signal.
Furong Li, Marie-José Gaillard, Xianyong Cao, Ulrike Herzschuh, Shinya Sugita, Jian Ni, Yan Zhao, Chengbang An, Xiaozhong Huang, Yu Li, Hongyan Liu, Aizhi Sun, and Yifeng Yao
Earth Syst. Sci. Data, 15, 95–112, https://doi.org/10.5194/essd-15-95-2023, https://doi.org/10.5194/essd-15-95-2023, 2023
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The objective of this study is present the first gridded and temporally continuous quantitative plant-cover reconstruction for temperate and northern subtropical China over the last 12 millennia. The reconstructions are based on 94 pollen records and include estimates for 27 plant taxa, 10 plant functional types, and 3 land-cover types. The dataset is suitable for palaeoclimate modelling and the evaluation of simulated past vegetation cover and anthropogenic land-cover change from models.
Timon Miesner, Ulrike Herzschuh, Luidmila A. Pestryakova, Mareike Wieczorek, Evgenii S. Zakharov, Alexei I. Kolmogorov, Paraskovya V. Davydova, and Stefan Kruse
Earth Syst. Sci. Data, 14, 5695–5716, https://doi.org/10.5194/essd-14-5695-2022, https://doi.org/10.5194/essd-14-5695-2022, 2022
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We present data which were collected on expeditions to the northeast of the Russian Federation. One table describes the 226 locations we visited during those expeditions, and the other describes 40 289 trees which we recorded at these locations. We found out that important information on the forest cannot be predicted precisely from satellites. Thus, for anyone interested in distant forests, it is important to go to there and take measurements or use data (as presented here).
Boris K. Biskaborn, Amy Forster, Gregor Pfalz, Lyudmila A. Pestryakova, Kathleen Stoof-Leichsenring, Jens Strauss, Tim Kröger, and Ulrike Herzschuh
EGUsphere, https://doi.org/10.5194/egusphere-2022-985, https://doi.org/10.5194/egusphere-2022-985, 2022
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Sediment cores from a mountain lake in the Russian Arctic were investigated for micro algae, organic matter and mercury, dated back to the last glacial. The species assemblages responded strongly to environmental changes such as Younger Dryas cold event and the Holocene Thermal Maximum. Organic carbon correlated with rates of micro algae deposition only during warm episodes, but not during the cold glacial. This highlights the importance of pristine lakes as carbon sinks during climate warming.
Ulrike Herzschuh, Chenzhi Li, Thomas Böhmer, Alexander K. Postl, Birgit Heim, Andrei A. Andreev, Xianyong Cao, Mareike Wieczorek, and Jian Ni
Earth Syst. Sci. Data, 14, 3213–3227, https://doi.org/10.5194/essd-14-3213-2022, https://doi.org/10.5194/essd-14-3213-2022, 2022
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Pollen preserved in environmental archives such as lake sediments and bogs are extensively used for reconstructions of past vegetation and climate. Here we present LegacyPollen 1.0, a dataset of 2831 fossil pollen records from all over the globe that were collected from publicly available databases. We harmonized the names of the pollen taxa so that all datasets can be jointly investigated. LegacyPollen 1.0 is available as an open-access dataset.
Manuel Chevalier, Anne Dallmeyer, Nils Weitzel, Chenzhi Li, Jean-Philippe Baudouin, Ulrike Herzschuh, Xianyong Cao, and Andreas Hense
EGUsphere, https://doi.org/10.5194/egusphere-2022-489, https://doi.org/10.5194/egusphere-2022-489, 2022
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Data-data and data-model biome comparisons are commonly based on comparing single biome estimates. While this approach generates good results over large temporal and spatial scales, reducing pollen assemblages to a single biome can oversimplify the vegetation signal preserved in pollen samples. We propose to use a multivariate metric, the Earth Movers' Distance (EMD), to include more details about the vegetation structure when performing such comparisons.
Moritz Langer, Jan Nitzbon, Brian Groenke, Lisa-Marie Assmann, Thomas Schneider von Deimling, Simone Maria Stuenzi, and Sebastian Westermann
EGUsphere, https://doi.org/10.5194/egusphere-2022-473, https://doi.org/10.5194/egusphere-2022-473, 2022
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We present a model capable of simulating the evolution of Arctic permafrost over centuries to millennia, taking into account highly uncertain soil and snow properties. We find that permafrost warming occurs primarily in three "hotspot" regions. The extent of near-surface permafrost has decreased substantially since 1850, with the largest area losses occurring in the last 50 years. Volcanic eruptions were shown to have counteracted the loss of near-surface permafrost for only a few decades.
Sebastian Westermann, Thomas Ingeman-Nielsen, Johanna Scheer, Kristoffer Aalstad, Juditha Aga, Nitin Chaudhary, Bernd Etzelmüller, Simon Filhol, Andreas Kääb, Cas Renette, Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Robin B. Zweigel, Léo Martin, Sarah Morard, Matan Ben-Asher, Michael Angelopoulos, Julia Boike, Brian Groenke, Frederieke Miesner, Jan Nitzbon, Paul Overduin, Simone M. Stuenzi, and Moritz Langer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-127, https://doi.org/10.5194/gmd-2022-127, 2022
Preprint under review for GMD
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The CryoGrid community model is a new tool for simulating ground temperatures and the water and ice balance in cold regions. It is a modular design which makes it possible to test different schemes to simulate for example permafrost ground in an efficient way. The model contains tools to simulate frozen and unfrozen ground, snow, glaciers and other massive ice bodies, as well as water bodies.
Ramesh Glückler, Rongwei Geng, Lennart Grimm, Izabella Baisheva, Ulrike Herzschuh, Kathleen R. Stoof-Leichsenring, Stefan Kruse, Andrei Andreev, Luidmila Pestryakova, and Elisabeth Dietze
EGUsphere, https://doi.org/10.5194/egusphere-2022-395, https://doi.org/10.5194/egusphere-2022-395, 2022
Preprint archived
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Despite rapidly intensifying wildfire seasons in Siberian boreal forests, little is known about long-term relationships between changes in vegetation and shifts in wildfire activity. Using lake sediment proxies, we reconstruct such environmental changes over the past 10,800 years in Central Yakutia. We find that a more open forest may facilitate increased amounts of vegetation burning. The present-day dense larch forest might yet be mediating the current climate-driven wildfire intensification.
Ulrike Herzschuh, Thomas Böhmer, Manuel Chevalier, Anne Dallmeyer, Chenzhi Li, Xianyong Cao, Raphaël Hébert, Odile Peyron, Larisa Nazarova, Elena Y. Novenko, Jungjae Park, Natalia A. Rudaya, Frank Schlütz, Lyudmila S. Shumilovskikh, Pavel E. Tarasov, Yongbo Wang, Ruilin Wen, Qinghai Xu, and Zhuo Zheng
EGUsphere, https://doi.org/10.5194/egusphere-2022-127, https://doi.org/10.5194/egusphere-2022-127, 2022
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A mismatch between model- and proxy-based Holocene climate change may partially originate from the poor spatial coverage of climate reconstructions. Here we investigate quantitative reconstructions of mean annual temperature and annual precipitation from 1676 pollen records in the Northern Hemisphere. Trends show strong latitudinal patterns and differ between (sub-)continents. Our work contributes to a better understanding of the global means.
Chenzhi Li, Alexander K. Postl, Thomas Böhmer, Xianyong Cao, Andrew M. Dolman, and Ulrike Herzschuh
Earth Syst. Sci. Data, 14, 1331–1343, https://doi.org/10.5194/essd-14-1331-2022, https://doi.org/10.5194/essd-14-1331-2022, 2022
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Here we present a global chronology framework of 2831 palynological records, including globally harmonized chronologies covering up to 273 000 years. A comparison with the original chronologies reveals a major improvement according to our assessment. Our chronology framework and revised chronologies will interest a broad geoscientific community, as it provides the opportunity to make use in synthesis studies of, for example, pollen-based vegetation and climate change.
Stefan Kruse, Simone M. Stuenzi, Julia Boike, Moritz Langer, Josias Gloy, and Ulrike Herzschuh
Geosci. Model Dev., 15, 2395–2422, https://doi.org/10.5194/gmd-15-2395-2022, https://doi.org/10.5194/gmd-15-2395-2022, 2022
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We coupled established models for boreal forest (LAVESI) and permafrost dynamics (CryoGrid) in Siberia to investigate interactions of the diverse vegetation layer with permafrost soils. Our tests showed improved active layer depth estimations and newly included species growth according to their species-specific limits. We conclude that the new model system can be applied to simulate boreal forest dynamics and transitions under global warming and disturbances, expanding our knowledge.
R. de los Reyes, K. Alonso, M. Bachmann, E. Carmona, M. Langheinrich, R. Müller, B. Pflug, and R. Richter
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-1-W1-2021, 9–12, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-9-2022, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-9-2022, 2022
Ulrike Herzschuh, Thomas Böhmer, Chenzhi Li, Manuel Chevalier, Anne Dallmeyer, Xianyong Cao, Nancy H. Bigelow, Larisa Nazarova, Elena Y. Novenko, Jungjae Park, Odile Peyron, Natalia A. Rudaya, Frank Schlütz, Lyudmila S. Shumilovskikh, Pavel E. Tarasov, Yongbo Wang, Ruilin Wen, Qinghai Xu, and Zhuo Zheng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-38, https://doi.org/10.5194/essd-2022-38, 2022
Revised manuscript under review for ESSD
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Climate reconstruction from proxy data can help evaluate climate models. Here we present pollen-based reconstructions of mean July temperature, mean annual temperature, and annual precipitation from 2594 pollen records from the Northern Hemisphere using three reconstruction methods (WA-PLS, WA-PLS_tailored, MAT). Since no global or hemispheric synthesis of quantitative precipitation changes are available for the Holocene so far, this dataset will be of great value to the geoscientific community.
Anne Dallmeyer, Martin Claussen, Stephan J. Lorenz, Michael Sigl, Matthew Toohey, and Ulrike Herzschuh
Clim. Past, 17, 2481–2513, https://doi.org/10.5194/cp-17-2481-2021, https://doi.org/10.5194/cp-17-2481-2021, 2021
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Using the comprehensive Earth system model, MPI-ESM1.2, we explore the global Holocene vegetation changes and interpret them in terms of the Holocene climate change. The model results reveal that most of the Holocene vegetation transitions seen outside the high northern latitudes can be attributed to modifications in the intensity of the global summer monsoons.
Stuart A. Vyse, Ulrike Herzschuh, Gregor Pfalz, Lyudmila A. Pestryakova, Bernhard Diekmann, Norbert Nowaczyk, and Boris K. Biskaborn
Biogeosciences, 18, 4791–4816, https://doi.org/10.5194/bg-18-4791-2021, https://doi.org/10.5194/bg-18-4791-2021, 2021
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Lakes act as important stores of organic carbon and inorganic sediment material. This study provides a first investigation into carbon and sediment accumulation and storage within an Arctic glacial lake from Far East Russia. It shows that major shifts are related to palaeoclimate variation that affects the development of the lake and its surrounding catchment. Spatial differences to other lake systems from other regions may reflect variability in processes controlled by latitude and altitude.
Ramesh Glückler, Ulrike Herzschuh, Stefan Kruse, Andrei Andreev, Stuart Andrew Vyse, Bettina Winkler, Boris K. Biskaborn, Luidmila Pestryakova, and Elisabeth Dietze
Biogeosciences, 18, 4185–4209, https://doi.org/10.5194/bg-18-4185-2021, https://doi.org/10.5194/bg-18-4185-2021, 2021
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Data about past fire activity are very sparse in Siberia. This study presents a first high-resolution record of charcoal particles from lake sediments in boreal eastern Siberia. It indicates that current levels of charcoal accumulation are not unprecedented. While a recent increase in reconstructed fire frequency coincides with rising temperatures and increasing human activity, vegetation composition does not seem to be a major driver behind changes in the fire regime in the past two millennia.
Lydia Stolpmann, Caroline Coch, Anne Morgenstern, Julia Boike, Michael Fritz, Ulrike Herzschuh, Kathleen Stoof-Leichsenring, Yury Dvornikov, Birgit Heim, Josefine Lenz, Amy Larsen, Katey Walter Anthony, Benjamin Jones, Karen Frey, and Guido Grosse
Biogeosciences, 18, 3917–3936, https://doi.org/10.5194/bg-18-3917-2021, https://doi.org/10.5194/bg-18-3917-2021, 2021
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Our new database summarizes DOC concentrations of 2167 water samples from 1833 lakes in permafrost regions across the Arctic to provide insights into linkages between DOC and environment. We found increasing lake DOC concentration with decreasing permafrost extent and higher DOC concentrations in boreal permafrost sites compared to tundra sites. Our study shows that DOC concentration depends on the environmental properties of a lake, especially permafrost extent, ecoregion, and vegetation.
Jens A. Hölemann, Bennet Juhls, Dorothea Bauch, Markus Janout, Boris P. Koch, and Birgit Heim
Biogeosciences, 18, 3637–3655, https://doi.org/10.5194/bg-18-3637-2021, https://doi.org/10.5194/bg-18-3637-2021, 2021
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The Arctic Ocean receives large amounts of river water rich in terrestrial dissolved organic matter (tDOM), which is an important component of the Arctic carbon cycle. Our analysis shows that mixing of three major freshwater sources is the main factor that regulates the distribution of tDOM concentrations in the Siberian shelf seas. In this context, the formation and melting of the land-fast ice in the Laptev Sea and the peak spring discharge of the Lena River are of particular importance.
Iuliia Shevtsova, Ulrike Herzschuh, Birgit Heim, Luise Schulte, Simone Stünzi, Luidmila A. Pestryakova, Evgeniy S. Zakharov, and Stefan Kruse
Biogeosciences, 18, 3343–3366, https://doi.org/10.5194/bg-18-3343-2021, https://doi.org/10.5194/bg-18-3343-2021, 2021
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In the light of climate changes in subarctic regions, notable general increase in above-ground biomass for the past 15 years (2000 to 2017) was estimated along a tundra–taiga gradient of central Chukotka (Russian Far East). The greatest increase occurred in the northern taiga in the areas of larch closed-canopy forest expansion with Cajander larch as a main contributor. For the estimations, we used field data (taxa-separated plant biomass, 2018) and upscaled it based on Landsat satellite data.
Simone Maria Stuenzi, Julia Boike, William Cable, Ulrike Herzschuh, Stefan Kruse, Luidmila A. Pestryakova, Thomas Schneider von Deimling, Sebastian Westermann, Evgenii S. Zakharov, and Moritz Langer
Biogeosciences, 18, 343–365, https://doi.org/10.5194/bg-18-343-2021, https://doi.org/10.5194/bg-18-343-2021, 2021
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Boreal forests in eastern Siberia are an essential component of global climate patterns. We use a physically based model and field measurements to study the interactions between forests, permanently frozen ground and the atmosphere. We find that forests exert a strong control on the thermal state of permafrost through changing snow cover dynamics and altering the surface energy balance, through absorbing most of the incoming solar radiation and suppressing below-canopy turbulent fluxes.
Mareike Wieczorek and Ulrike Herzschuh
Earth Syst. Sci. Data, 12, 3515–3528, https://doi.org/10.5194/essd-12-3515-2020, https://doi.org/10.5194/essd-12-3515-2020, 2020
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Relative pollen productivity (RPP) estimates are used to estimate vegetation cover from pollen records. This study provides (i) a compilation of northern hemispheric RPP studies, allowing researchers to identify suitable sets for their study region and to identify data gaps for future research, and (ii) taxonomically harmonized, unified RPP sets for China, Europe, North America, and the whole Northern Hemisphere, generated from the available studies.
Basil A. S. Davis, Manuel Chevalier, Philipp Sommer, Vachel A. Carter, Walter Finsinger, Achille Mauri, Leanne N. Phelps, Marco Zanon, Roman Abegglen, Christine M. Åkesson, Francisca Alba-Sánchez, R. Scott Anderson, Tatiana G. Antipina, Juliana R. Atanassova, Ruth Beer, Nina I. Belyanina, Tatiana A. Blyakharchuk, Olga K. Borisova, Elissaveta Bozilova, Galina Bukreeva, M. Jane Bunting, Eleonora Clò, Daniele Colombaroli, Nathalie Combourieu-Nebout, Stéphanie Desprat, Federico Di Rita, Morteza Djamali, Kevin J. Edwards, Patricia L. Fall, Angelica Feurdean, William Fletcher, Assunta Florenzano, Giulia Furlanetto, Emna Gaceur, Arsenii T. Galimov, Mariusz Gałka, Iria García-Moreiras, Thomas Giesecke, Roxana Grindean, Maria A. Guido, Irina G. Gvozdeva, Ulrike Herzschuh, Kari L. Hjelle, Sergey Ivanov, Susanne Jahns, Vlasta Jankovska, Gonzalo Jiménez-Moreno, Monika Karpińska-Kołaczek, Ikuko Kitaba, Piotr Kołaczek, Elena G. Lapteva, Małgorzata Latałowa, Vincent Lebreton, Suzanne Leroy, Michelle Leydet, Darya A. Lopatina, José Antonio López-Sáez, André F. Lotter, Donatella Magri, Elena Marinova, Isabelle Matthias, Anastasia Mavridou, Anna Maria Mercuri, Jose Manuel Mesa-Fernández, Yuri A. Mikishin, Krystyna Milecka, Carlo Montanari, César Morales-Molino, Almut Mrotzek, Castor Muñoz Sobrino, Olga D. Naidina, Takeshi Nakagawa, Anne Birgitte Nielsen, Elena Y. Novenko, Sampson Panajiotidis, Nata K. Panova, Maria Papadopoulou, Heather S. Pardoe, Anna Pędziszewska, Tatiana I. Petrenko, María J. Ramos-Román, Cesare Ravazzi, Manfred Rösch, Natalia Ryabogina, Silvia Sabariego Ruiz, J. Sakari Salonen, Tatyana V. Sapelko, James E. Schofield, Heikki Seppä, Lyudmila Shumilovskikh, Normunds Stivrins, Philipp Stojakowits, Helena Svobodova Svitavska, Joanna Święta-Musznicka, Ioan Tantau, Willy Tinner, Kazimierz Tobolski, Spassimir Tonkov, Margarita Tsakiridou, Verushka Valsecchi, Oksana G. Zanina, and Marcelina Zimny
Earth Syst. Sci. Data, 12, 2423–2445, https://doi.org/10.5194/essd-12-2423-2020, https://doi.org/10.5194/essd-12-2423-2020, 2020
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The Eurasian Modern Pollen Database (EMPD) contains pollen counts and associated metadata for 8134 modern pollen samples from across the Eurasian region. The EMPD is part of, and complementary to, the European Pollen Database (EPD) which contains data on fossil pollen found in Late Quaternary sedimentary archives. The purpose of the EMPD is to provide calibration datasets and other data to support palaeoecological research on past climates and vegetation cover over the Quaternary period.
Heike H. Zimmermann, Kathleen R. Stoof-Leichsenring, Stefan Kruse, Juliane Müller, Ruediger Stein, Ralf Tiedemann, and Ulrike Herzschuh
Ocean Sci., 16, 1017–1032, https://doi.org/10.5194/os-16-1017-2020, https://doi.org/10.5194/os-16-1017-2020, 2020
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This study targets high-resolution, diatom-specific sedimentary ancient DNA using a DNA metabarcoding approach. Diatom DNA has been preserved with substantial taxonomic richness in the eastern Fram Strait over the past 30 000 years with taxonomic composition being dominated by cold-water and sea-ice-associated diatoms. Taxonomic reorganisations took place after the Last Glacial Maximum and after the Younger Dryas. Peak proportions of pennate diatoms might indicate past sea-ice presence.
Elisabeth Dietze, Kai Mangelsdorf, Andrei Andreev, Cornelia Karger, Laura T. Schreuder, Ellen C. Hopmans, Oliver Rach, Dirk Sachse, Volker Wennrich, and Ulrike Herzschuh
Clim. Past, 16, 799–818, https://doi.org/10.5194/cp-16-799-2020, https://doi.org/10.5194/cp-16-799-2020, 2020
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Long-term climate change impacts on fire, vegetation and permafrost in the Arctic are uncertain. Here, we show the high potential of organic compounds from low-temperature biomass burning to serve as proxies for surface fires in lake deposits. During warm periods of the last 430 000 years, surface fires are closely linked to the larch taiga forest with its moss–lichen ground vegetation that isolates the permafrost. They have reduced in warm–wet, spruce–dominated and cool–dry steppe environments.
Xianyong Cao, Fang Tian, Andrei Andreev, Patricia M. Anderson, Anatoly V. Lozhkin, Elena Bezrukova, Jian Ni, Natalia Rudaya, Astrid Stobbe, Mareike Wieczorek, and Ulrike Herzschuh
Earth Syst. Sci. Data, 12, 119–135, https://doi.org/10.5194/essd-12-119-2020, https://doi.org/10.5194/essd-12-119-2020, 2020
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Pollen percentages in spectra cannot be utilized to indicate past plant abundance directly because of the different pollen productivities among plants. In this paper, we applied relative pollen productivity estimates (PPEs) to calibrate plant abundances during the last 40 kyr using pollen counts from 203 pollen spectra in northern Asia. Results indicate the vegetation are generally stable during the Holocene and that climate change is the primary factor.
Caroline Coch, Bennet Juhls, Scott F. Lamoureux, Melissa J. Lafrenière, Michael Fritz, Birgit Heim, and Hugues Lantuit
Biogeosciences, 16, 4535–4553, https://doi.org/10.5194/bg-16-4535-2019, https://doi.org/10.5194/bg-16-4535-2019, 2019
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Climate change affects Arctic ecosystems. This includes thawing of permafrost (ground below 0 °C) and an increase in rainfall. Both have substantial impacts on the chemical composition of river water. We compared the composition of small rivers in the low and high Arctic with the large Arctic rivers. In comparison, dissolved organic matter in the small rivers is more susceptible to degradation; thus, it could potentially increase carbon dioxide emissions. Rainfall events have a similar effect.
Boris K. Biskaborn, Larisa Nazarova, Lyudmila A. Pestryakova, Liudmila Syrykh, Kim Funck, Hanno Meyer, Bernhard Chapligin, Stuart Vyse, Ruslan Gorodnichev, Evgenii Zakharov, Rong Wang, Georg Schwamborn, Hannah L. Bailey, and Bernhard Diekmann
Biogeosciences, 16, 4023–4049, https://doi.org/10.5194/bg-16-4023-2019, https://doi.org/10.5194/bg-16-4023-2019, 2019
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To better understand time-series data in lake sediment cores in times of rapidly changing climate, we study within-lake spatial variabilities of environmental indicator data in 38 sediment surface samples along spatial habitat gradients in the boreal deep Lake Bolshoe Toko (Russia). Our methods comprise physicochemical as well as diatom and chironomid analyses. Species diversities vary according to benthic niches, while abiotic proxies depend on river input, water depth, and catchment lithology.
Xianyong Cao, Fang Tian, Furong Li, Marie-José Gaillard, Natalia Rudaya, Qinghai Xu, and Ulrike Herzschuh
Clim. Past, 15, 1503–1536, https://doi.org/10.5194/cp-15-1503-2019, https://doi.org/10.5194/cp-15-1503-2019, 2019
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The high-quality pollen records (collected from lakes and peat bogs) of the last 40 ka cal BP form north Asia are homogenized and the plant abundance signals are calibrated by the modern relative pollen productivity estimates. Calibrated plant abundances for each site are generally consistent with in situ modern vegetation, and vegetation changes within the regions are characterized by minor changes in the abundance of major taxa rather than by invasions of new taxa during the last 40 ka cal BP.
Bennet Juhls, Pier Paul Overduin, Jens Hölemann, Martin Hieronymi, Atsushi Matsuoka, Birgit Heim, and Jürgen Fischer
Biogeosciences, 16, 2693–2713, https://doi.org/10.5194/bg-16-2693-2019, https://doi.org/10.5194/bg-16-2693-2019, 2019
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In this article, we present the variability and characteristics of dissolved organic matter at the fluvial–marine transition in the Laptev Sea from a unique dataset collected during 11 Arctic expeditions. We develop a new relationship between dissolved organic carbon (DOC) and coloured dissolved organic matter absorption, which is used to estimate surface water DOC concentration from space. We believe that our findings help current efforts to monitor ongoing changes in the Arctic carbon cycle.
Stefan Kruse, Alexander Gerdes, Nadja J. Kath, Laura S. Epp, Kathleen R. Stoof-Leichsenring, Luidmila A. Pestryakova, and Ulrike Herzschuh
Biogeosciences, 16, 1211–1224, https://doi.org/10.5194/bg-16-1211-2019, https://doi.org/10.5194/bg-16-1211-2019, 2019
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How fast might the arctic treeline in northern central Siberia migrate northwards under current global warming? To answer this, we newly parameterized dispersal processes in the individual-based and spatially explicit model LAVESI-WIND based on parentage analysis. Simulation results show that northernmost open forest stands are migrating at an unexpectedly slow rate into tundra. We conclude that the treeline currently lags behind the strong warming and will remain slow in the upcoming decades.
Stefan Kruse, Alexander Gerdes, Nadja J. Kath, and Ulrike Herzschuh
Geosci. Model Dev., 11, 4451–4467, https://doi.org/10.5194/gmd-11-4451-2018, https://doi.org/10.5194/gmd-11-4451-2018, 2018
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It is of major interest to estimate feedbacks of arctic ecosystems to global warming in the upcoming decades. However, the speed of this response is driven by the potential of species to migrate and the timing and spatial scale for this is rather uncertain. To close this knowledge gap, we updated a very detailed vegetation model by including seed and pollen dispersal driven by wind speed and direction. The new model can substantially help in unveiling the important drivers of migration dynamics.
Sophia Walther, Luis Guanter, Birgit Heim, Martin Jung, Gregory Duveiller, Aleksandra Wolanin, and Torsten Sachs
Biogeosciences, 15, 6221–6256, https://doi.org/10.5194/bg-15-6221-2018, https://doi.org/10.5194/bg-15-6221-2018, 2018
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We explored the timing of the peak of the short annual growing season in tundra ecosystems as indicated by an extensive suite of satellite indicators of vegetation productivity. Delayed peak greenness compared to peak photosynthesis is consistently found across years and land-cover classes. Plants also experience growth after optimal conditions for assimilation regarding light and temperature have passed. Our results have implications for the modelling of the circumpolar carbon balance.
Romy Zibulski, Felix Wesener, Heinz Wilkes, Birgit Plessen, Luidmila A. Pestryakova, and Ulrike Herzschuh
Biogeosciences, 14, 1617–1630, https://doi.org/10.5194/bg-14-1617-2017, https://doi.org/10.5194/bg-14-1617-2017, 2017
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We investigated variations of isotopic and biochemical parameters in arctic mosses. We were able to differentiate habitat groups of mosses (classified by moisture gradient) by elemental content and isotopic ratios (δ13C, δ15N). Some species showed intraspecific variability in their isotopic composition along the moisture gradient. Furthermore n-alkanes showed interesting patterns for species identification.
Anne Dallmeyer, Martin Claussen, Jian Ni, Xianyong Cao, Yongbo Wang, Nils Fischer, Madlene Pfeiffer, Liya Jin, Vyacheslav Khon, Sebastian Wagner, Kerstin Haberkorn, and Ulrike Herzschuh
Clim. Past, 13, 107–134, https://doi.org/10.5194/cp-13-107-2017, https://doi.org/10.5194/cp-13-107-2017, 2017
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The vegetation distribution in eastern Asia is supposed to be very sensitive to climate change. Since proxy records are scarce, hitherto a mechanistic understanding of the past spatio-temporal climate–vegetation relationship is lacking. To assess the Holocene vegetation change, we forced the diagnostic biome model BIOME4 with climate anomalies of different transient climate simulations.
Heike Hildegard Zimmermann, Elena Raschke, Laura Saskia Epp, Kathleen Rosmarie Stoof-Leichsenring, Georg Schwamborn, Lutz Schirrmeister, Pier Paul Overduin, and Ulrike Herzschuh
Biogeosciences, 14, 575–596, https://doi.org/10.5194/bg-14-575-2017, https://doi.org/10.5194/bg-14-575-2017, 2017
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Organic matter stored in permafrost will start decomposing due to climate warming. To better understand its composition in ice-rich Yedoma, we analyzed ancient sedimentary DNA, pollen and non-pollen palynomorphs throughout an 18.9 m long permafrost core. The combination of both proxies allow an interpretation both of regional floristic changes and of the local environmental conditions at the time of deposition.
Liv Heinecke, Steffen Mischke, Karsten Adler, Anja Barth, Boris K. Biskaborn, Birgit Plessen, Ingmar Nitze, Gerhard Kuhn, Ilhomjon Rajabov, and Ulrike Herzschuh
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-34, https://doi.org/10.5194/cp-2016-34, 2016
Revised manuscript not accepted
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The climate history of the Pamir Mountains (Tajikistan) during the last ~29 kyr was investigated using sediments from Lake Karakul as environmental archive. The inferred lake level was highest from the Late Glacial to the early Holocene and lake changes were mainly coupled to climate change. We conclude that the joint influence of Westerlies and Indian Monsoon during the early Holocene caused comparatively moist conditions, while dominating Westerlies yielded dry conditions since 6.7 cal kyr BP.
M. Fritz, T. Opel, G. Tanski, U. Herzschuh, H. Meyer, A. Eulenburg, and H. Lantuit
The Cryosphere, 9, 737–752, https://doi.org/10.5194/tc-9-737-2015, https://doi.org/10.5194/tc-9-737-2015, 2015
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Ground ice in permafrost has not, until now, been considered to be a source of dissolved organic carbon (DOC), dissolved inorganic carbon (DIC) and other elements that are important for ecosystems and carbon cycling.
Ice wedges in the Arctic Yedoma region hold 45.2 Tg DOC (Tg = 10^12g), 33.6 Tg DIC and a freshwater reservoir of 4200 km³.
Leaching of terrestrial organic matter is the most relevant process of DOC sequestration into ground ice.
J. Strauss, L. Schirrmeister, K. Mangelsdorf, L. Eichhorn, S. Wetterich, and U. Herzschuh
Biogeosciences, 12, 2227–2245, https://doi.org/10.5194/bg-12-2227-2015, https://doi.org/10.5194/bg-12-2227-2015, 2015
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Climatic warming is affecting permafrost, including decomposition of organic matter (OM). However, quantitative data for the quality of OM and its availability for decomposition is limited. We analyzed the quality of OM in late Pleistocene (Yedoma) and Holocene (thermokarst) deposits. A lack of depth trends reveals a constant quality of OM showing that permafrost acts like a freezer, preserving OM quality. This OM will be susceptible to decomposition under climatic warming.
B. Aichner, S. J. Feakins, J. E. Lee, U. Herzschuh, and X. Liu
Clim. Past, 11, 619–633, https://doi.org/10.5194/cp-11-619-2015, https://doi.org/10.5194/cp-11-619-2015, 2015
A. Dallmeyer, M. Claussen, N. Fischer, K. Haberkorn, S. Wagner, M. Pfeiffer, L. Jin, V. Khon, Y. Wang, and U. Herzschuh
Clim. Past, 11, 305–326, https://doi.org/10.5194/cp-11-305-2015, https://doi.org/10.5194/cp-11-305-2015, 2015
I. Fedorova, A. Chetverova, D. Bolshiyanov, A. Makarov, J. Boike, B. Heim, A. Morgenstern, P. P. Overduin, C. Wegner, V. Kashina, A. Eulenburg, E. Dobrotina, and I. Sidorina
Biogeosciences, 12, 345–363, https://doi.org/10.5194/bg-12-345-2015, https://doi.org/10.5194/bg-12-345-2015, 2015
B. Heim, E. Abramova, R. Doerffer, F. Günther, J. Hölemann, A. Kraberg, H. Lantuit, A. Loginova, F. Martynov, P. P. Overduin, and C. Wegner
Biogeosciences, 11, 4191–4210, https://doi.org/10.5194/bg-11-4191-2014, https://doi.org/10.5194/bg-11-4191-2014, 2014
A. A. Andreev, P. E. Tarasov, V. Wennrich, E. Raschke, U. Herzschuh, N. R. Nowaczyk, J. Brigham-Grette, and M. Melles
Clim. Past, 10, 1017–1039, https://doi.org/10.5194/cp-10-1017-2014, https://doi.org/10.5194/cp-10-1017-2014, 2014
Y. Wang, U. Herzschuh, L. S. Shumilovskikh, S. Mischke, H. J. B. Birks, J. Wischnewski, J. Böhner, F. Schlütz, F. Lehmkuhl, B. Diekmann, B. Wünnemann, and C. Zhang
Clim. Past, 10, 21–39, https://doi.org/10.5194/cp-10-21-2014, https://doi.org/10.5194/cp-10-21-2014, 2014
A. C. Kraberg, E. Druzhkova, B. Heim, M. J. G. Loeder, and K. H. Wiltshire
Biogeosciences, 10, 7263–7277, https://doi.org/10.5194/bg-10-7263-2013, https://doi.org/10.5194/bg-10-7263-2013, 2013
R. Zibulski, U. Herzschuh, L. A. Pestryakova, J. Wolter, S. Müller, N. Schilling, S. Wetterich, L. Schirrmeister, and F. Tian
Biogeosciences, 10, 5703–5728, https://doi.org/10.5194/bg-10-5703-2013, https://doi.org/10.5194/bg-10-5703-2013, 2013
Related subject area
Domain: ESSD – Land | Subject: Land Cover and Land Use
Harmonising the land-use flux estimates of global models and national inventories for 2000–2020
Four-century history of land transformation by humans in the United States (1630–2020): annual and 1 km grid data for the HIStory of LAND changes (HISLAND-US)
A 250 m annual alpine grassland AGB dataset over the Qinghai–Tibet Plateau (2000–2019) in China based on in situ measurements, UAV photos, and MODIS data
AsiaRiceYield4km: seasonal rice yield in Asia from 1995 to 2015
TreeSatAI Benchmark Archive: a multi-sensor, multi-label dataset for tree species classification in remote sensing
UGS-1m: fine-grained urban green space mapping of 31 major cities in China based on the deep learning framework
AI4Boundaries: an open AI-ready dataset to map field boundaries with Sentinel-2 and aerial photography
GWL_FCS30: a global 30 m wetland map with a fine classification system using multi-sourced and time-series remote sensing imagery in 2020
CALC-2020: a new baseline land cover map at 10 m resolution for the circumpolar Arctic
MDAS: a new multimodal benchmark dataset for remote sensing
Gridded pollen-based Holocene regional plant cover in temperate and northern subtropical China suitable for climate modelling
Location, biophysical and agronomic parameters for croplands in northern Ghana
20 m Annual Paddy Rice Map for Mainland Southeast Asia Using Sentinel-1 SAR Data
Historical nitrogen fertilizer use in China from 1952 to 2018
Estimating Local Agricultural GDP across the World
History of anthropogenic Nitrogen inputs (HaNi) to the terrestrial biosphere: a 5 arcmin resolution annual dataset from 1860 to 2019
LUCAS cover photos 2006–2018 over the EU: 874 646 spatially distributed geo-tagged close-up photos with land cover and plant species label
Gridded 5 arcmin datasets for simultaneously farm-size-specific and crop-specific harvested areas in 56 countries
A 29-year time series of annual 300-metre resolution plant functional type maps for climate models
Vectorized dataset of roadside noise barriers in China using street view imagery
A global map of local climate zones to support earth system modelling and urban-scale environmental science
Mapping 10 m global impervious surface area (GISA-10m) using multi-source geospatial data
An Open-Source Automatic Survey of Green Roofs in London using Segmentation of Aerial Imagery
Classification and mapping of European fuels using a hierarchical-multipurpose fuel classification system
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
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Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
Xiaoyong Li, Hanqin Tian, Chaoqun Lu, and Shufen Pan
Earth Syst. Sci. Data, 15, 1005–1035, https://doi.org/10.5194/essd-15-1005-2023, https://doi.org/10.5194/essd-15-1005-2023, 2023
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We reconstructed land use and land cover (LULC) history for the conterminous United States during 1630–2020 by integrating multi-source data. The results show the widespread expansion of cropland and urban land and the shrinking of natural vegetation in the past four centuries. Forest planting and regeneration accelerated forest recovery since the 1920s. The datasets can be used to assess the LULC impacts on the ecosystem's carbon, nitrogen, and water cycles.
Huifang Zhang, Zhonggang Tang, Binyao Wang, Hongcheng Kan, Yi Sun, Yu Qin, Baoping Meng, Meng Li, Jianjun Chen, Yanyan Lv, Jianguo Zhang, Shuli Niu, and Shuhua Yi
Earth Syst. Sci. Data, 15, 821–846, https://doi.org/10.5194/essd-15-821-2023, https://doi.org/10.5194/essd-15-821-2023, 2023
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The accuracy of regional grassland aboveground biomass (AGB) is always limited by insufficient ground measurements and large spatial gaps with satellite pixels. This paper used more than 37 000 UAV images as bridges to successfully obtain AGB values matching MODIS pixels. The new AGB estimation model had good robustness, with an average R2 of 0.83 and RMSE of 34.13 g m2. Our new dataset provides important input parameters for understanding the Qinghai–Tibet Plateau during global climate change.
Huaqing Wu, Jing Zhang, Zhao Zhang, Jichong Han, Juan Cao, Liangliang Zhang, Yuchuan Luo, Qinghang Mei, Jialu Xu, and Fulu Tao
Earth Syst. Sci. Data, 15, 791–808, https://doi.org/10.5194/essd-15-791-2023, https://doi.org/10.5194/essd-15-791-2023, 2023
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High-spatiotemporal-resolution rice yield datasets are limited over a large region. We proposed an explicit method to predict rice yield based on machine learning methods and generated a seasonal 4 km resolution rice yield dataset across Asia (AsiaRiceYield4km) for 1995–2015. The seasonal rice yield accuracy of AsiaRiceYield4km is high and much improved compared with previous datasets. AsiaRiceYield4km will fill the current data gap and better support agricultural monitoring systems.
Steve Ahlswede, Christian Schulz, Christiano Gava, Patrick Helber, Benjamin Bischke, Michael Förster, Florencia Arias, Jörn Hees, Begüm Demir, and Birgit Kleinschmit
Earth Syst. Sci. Data, 15, 681–695, https://doi.org/10.5194/essd-15-681-2023, https://doi.org/10.5194/essd-15-681-2023, 2023
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Imagery from air and space is the primary source of large-scale forest mapping. Our study introduces a new dataset with over 50000 image patches prepared for deep learning tasks. We show how the information for 20 European tree species can be extracted from different remote sensing sensors. Our algorithms can detect single species with precision scores up to 88 %. With a pixel size of 20×20 cm, forestry administration can now derive large-scale tree species maps at a very high resolution.
Qian Shi, Mengxi Liu, Andrea Marinoni, and Xiaoping Liu
Earth Syst. Sci. Data, 15, 555–577, https://doi.org/10.5194/essd-15-555-2023, https://doi.org/10.5194/essd-15-555-2023, 2023
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A large-scale and high-resolution urban green space (UGS) product with 1 m of 31 major cities in China (UGS-1m) is generated based on a deep learning framework to provide basic UGS information for relevant UGS research, such as distribution, area, and UGS rate. Moreover, an urban green space dataset (UGSet) with a total of 4454 samples of 512 × 512 in size are also supplied as the benchmark to support model training and algorithm comparison.
Raphaël d'Andrimont, Martin Claverie, Pieter Kempeneers, Davide Muraro, Momchil Yordanov, Devis Peressutti, Matej Batič, and François Waldner
Earth Syst. Sci. Data, 15, 317–329, https://doi.org/10.5194/essd-15-317-2023, https://doi.org/10.5194/essd-15-317-2023, 2023
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AI4boundaries is an open AI-ready data set to map field boundaries with Sentinel-2 and aerial photography provided with harmonised labels covering seven countries and 2.5 M parcels in Europe.
Xiao Zhang, Liangyun Liu, Tingting Zhao, Xidong Chen, Shangrong Lin, Jinqing Wang, Jun Mi, and Wendi Liu
Earth Syst. Sci. Data, 15, 265–293, https://doi.org/10.5194/essd-15-265-2023, https://doi.org/10.5194/essd-15-265-2023, 2023
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An accurate global 30 m wetland dataset that can simultaneously cover inland and coastal zones is lacking. This study proposes a novel method for wetland mapping and generates the first global 30 m wetland map with a fine classification system (GWL_FCS30), including five inland wetland sub-categories (permanent water, swamp, marsh, flooded flat and saline) and three coastal wetland sub-categories (mangrove, salt marsh and tidal flats).
Chong Liu, Xiaoqing Xu, Xuejie Feng, Xiao Cheng, Caixia Liu, and Huabing Huang
Earth Syst. Sci. Data, 15, 133–153, https://doi.org/10.5194/essd-15-133-2023, https://doi.org/10.5194/essd-15-133-2023, 2023
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Rapid Arctic changes are increasingly influencing human society, both locally and globally. Land cover offers a basis for characterizing the terrestrial world, yet spatially detailed information on Arctic land cover is lacking. We employ multi-source data to develop a new land cover map for the circumpolar Arctic. Our product reveals regionally contrasting biome distributions not fully documented in existing studies and thus enhances our understanding of the Arctic’s terrestrial system.
Jingliang Hu, Rong Liu, Danfeng Hong, Andrés Camero, Jing Yao, Mathias Schneider, Franz Kurz, Karl Segl, and Xiao Xiang Zhu
Earth Syst. Sci. Data, 15, 113–131, https://doi.org/10.5194/essd-15-113-2023, https://doi.org/10.5194/essd-15-113-2023, 2023
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Multimodal data fusion is an intuitive strategy to break the limitation of individual data in Earth observation. Here, we present a multimodal data set, named MDAS, consisting of synthetic aperture radar (SAR), multispectral, hyperspectral, digital surface model (DSM), and geographic information system (GIS) data for the city of Augsburg, Germany, along with baseline models for resolution enhancement, spectral unmixing, and land cover classification, three typical remote sensing applications.
Furong Li, Marie-José Gaillard, Xianyong Cao, Ulrike Herzschuh, Shinya Sugita, Jian Ni, Yan Zhao, Chengbang An, Xiaozhong Huang, Yu Li, Hongyan Liu, Aizhi Sun, and Yifeng Yao
Earth Syst. Sci. Data, 15, 95–112, https://doi.org/10.5194/essd-15-95-2023, https://doi.org/10.5194/essd-15-95-2023, 2023
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The objective of this study is present the first gridded and temporally continuous quantitative plant-cover reconstruction for temperate and northern subtropical China over the last 12 millennia. The reconstructions are based on 94 pollen records and include estimates for 27 plant taxa, 10 plant functional types, and 3 land-cover types. The dataset is suitable for palaeoclimate modelling and the evaluation of simulated past vegetation cover and anthropogenic land-cover change from models.
Jose Luis Gómez-Dans, Philip Edward Lewis, Feng Yin, Kofi Asare, Patrick Lamptey, Kenneth Kobina Yedu Aidoo, Dilys Sefakor MacCarthy, Hongyuan Ma, Qingling Wu, Martin Addi, Stephen Aboagye-Ntow, Caroline Edinam Doe, Rahaman Alhassan, Isaac Kankam-Boadu, Jianxi Huang, and Xuecao Li
Earth Syst. Sci. Data, 14, 5387–5410, https://doi.org/10.5194/essd-14-5387-2022, https://doi.org/10.5194/essd-14-5387-2022, 2022
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We provide a data set to support mapping croplands in smallholder landscapes in Ghana. The data set contains information on crop location on three agroecological zones for 2 years, temporal series of measurements of leaf area index and leaf chlorophyll concentration for maize canopies and yield. We demonstrate the use of these data to validate cropland masks, create a maize mask using satellite data and explore the relationship between satellite measurements and yield.
Chunling Sun, Hong Zhang, Lu Xu, Ji Ge, Jingling Jiang, Lijun Zuo, and Chao Wang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-392, https://doi.org/10.5194/essd-2022-392, 2022
Revised manuscript accepted for ESSD
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Over 90 % of the world’s rice is produced in the Asia-Pacific Region. In this study, a rice mapping method based on Sentinel-1 synthetic aperture radar data for mainland Southeast Asia is proposed. A combination of spatio-temporal features with strong generalization is selected and input into the U-Net model to obtain a 20-meter resolution rice map of mainland Southeast Asia in 2019. The accuracy of the proposed method is 92.20 %. The rice map is concordant with statistics and other rice maps.
Zhen Yu, Jing Liu, and Giri Kattel
Earth Syst. Sci. Data, 14, 5179–5194, https://doi.org/10.5194/essd-14-5179-2022, https://doi.org/10.5194/essd-14-5179-2022, 2022
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We developed a 5 km annual nitrogen (N) fertilizer use dataset in China, covering the period from 1952 to 2018. We found that previous FAO-data-based N fertilizer products overestimated the N use in low, but underestimated in high, cropland coverage areas in China. The new dataset has improved the spatial distribution and corrected the existing biases, which is beneficial for biogeochemical cycle simulations in China, such as the assessment of greenhouse gas emissions and food production.
Yating Ru, Brian Blankespoor, Ulrike Wood-Sichra, Timothy S. Thomas, Liangzhi You, and Erwin Kalvelagen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-336, https://doi.org/10.5194/essd-2022-336, 2022
Revised manuscript accepted for ESSD
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Economic statistics are frequently produced at an administrative level that lacks detail to examine development patterns and the exposure to natural hazards. This paper disaggregates national and subnational administrative statistics of Agricultural GDP into a global dataset at the local level using satellite-derived indicators. The paper estimates the exposure of areas with at least one extreme drought to agricultural GDP is US$432 billion, where nearly 1.2 billion people live.
Hanqin Tian, Zihao Bian, Hao Shi, Xiaoyu Qin, Naiqing Pan, Chaoqun Lu, Shufen Pan, Francesco N. Tubiello, Jinfeng Chang, Giulia Conchedda, Junguo Liu, Nathaniel Mueller, Kazuya Nishina, Rongting Xu, Jia Yang, Liangzhi You, and Bowen Zhang
Earth Syst. Sci. Data, 14, 4551–4568, https://doi.org/10.5194/essd-14-4551-2022, https://doi.org/10.5194/essd-14-4551-2022, 2022
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Nitrogen is one of the critical nutrients for growth. Evaluating the change in nitrogen inputs due to human activity is necessary for nutrient management and pollution control. In this study, we generated a historical dataset of nitrogen input to land at the global scale. This dataset consists of nitrogen fertilizer, manure, and atmospheric deposition inputs to cropland, pasture, and rangeland at high resolution from 1860 to 2019.
Raphaël d'Andrimont, Momchil Yordanov, Laura Martinez-Sanchez, Peter Haub, Oliver Buck, Carsten Haub, Beatrice Eiselt, and Marijn van der Velde
Earth Syst. Sci. Data, 14, 4463–4472, https://doi.org/10.5194/essd-14-4463-2022, https://doi.org/10.5194/essd-14-4463-2022, 2022
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Between 2006 and 2018, 875 661 LUCAS cover (i.e. close-up) photos were taken over a systematic sample of the European Union. This geo-located photo dataset has been curated and is being made available along with the surveyed label data, including land cover and plant species.
Han Su, Bárbara Willaarts, Diana Luna-Gonzalez, Maarten S. Krol, and Rick J. Hogeboom
Earth Syst. Sci. Data, 14, 4397–4418, https://doi.org/10.5194/essd-14-4397-2022, https://doi.org/10.5194/essd-14-4397-2022, 2022
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There are over 608 million farms around the world but they are not the same. We developed high spatial resolution maps showing where small and large farms were located and which crops were planted for 56 countries. We checked the reliability and have the confidence to use them for the country level and global studies. Our maps will help more studies to easily measure how agriculture policies, water availability, and climate change affect small and large farms.
Kandice L. Harper, Celine Lamarche, Andrew Hartley, Philippe Peylin, Catherine Ottlé, Vladislav Bastrikov, Rodrigo San Martín, Sylvia I. Bohnenstengel, Grit Kirches, Martin Boettcher, Roman Shevchuk, Carsten Brockmann, and Pierre Defourny
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-296, https://doi.org/10.5194/essd-2022-296, 2022
Revised manuscript accepted for ESSD
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We built a spatially explicit annual PFT dataset for 1992–2020 exhibiting intraclass spatial variability in PFT fractional cover at 300 m. For each year, 14 maps of PFTs percentage cover are produced: bare soil, water, permanent snow/ice, built, managed grasses, natural grasses, and trees and shrubs each split into leaf type and seasonality. ORCHIDEE and JULES model simulations indicate significant differences in simulated carbon, water, and energy fluxes in some regions using this new PFT set.
Zhen Qian, Min Chen, Yue Yang, Teng Zhong, Fan Zhang, Rui Zhu, Kai Zhang, Zhixin Zhang, Zhuo Sun, Peilong Ma, Guonian Lü, Yu Ye, and Jinyue Yan
Earth Syst. Sci. Data, 14, 4057–4076, https://doi.org/10.5194/essd-14-4057-2022, https://doi.org/10.5194/essd-14-4057-2022, 2022
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Roadside noise barriers (RNBs) are important urban infrastructures to ensure a city is liveable. This study provides the first reliable and nationwide vectorized RNB dataset with street view imagery in China. The generated RNB dataset is evaluated in terms of two aspects, i.e., the detection accuracy and the completeness and positional accuracy. The method is based on a developed geospatial artificial intelligence framework.
Matthias Demuzere, Jonas Kittner, Alberto Martilli, Gerald Mills, Christian Moede, Iain D. Stewart, Jasper van Vliet, and Benjamin Bechtel
Earth Syst. Sci. Data, 14, 3835–3873, https://doi.org/10.5194/essd-14-3835-2022, https://doi.org/10.5194/essd-14-3835-2022, 2022
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Because urban areas are key contributors to climate change but are also susceptible to multiple hazards, one needs spatially detailed information on urban landscapes to support environmental services. This global local climate zone map describes this much-needed intra-urban heterogeneity across the whole surface of the earth in a universal language and can serve as a basic infrastructure to study e.g. environmental hazards, energy demand, and climate adaptation and mitigation solutions.
Xin Huang, Jie Yang, Wenrui Wang, and Zhengrong Liu
Earth Syst. Sci. Data, 14, 3649–3672, https://doi.org/10.5194/essd-14-3649-2022, https://doi.org/10.5194/essd-14-3649-2022, 2022
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Using more than 2.7 million Sentinel images, we proposed a global ISA mapping method and produced the 10-m global ISA dataset (GISA-10m), with overall accuracy exceeding 86 %. The inter-comparison between different global ISA datasets showed the superiority of our results. The ISA distribution at urban and rural was discussed and compared. For the first time, courtesy of the high spatial resolution, the global road ISA was further identified, and its distribution was discussed.
Charles H. Simpson, Oscar Brousse, Nahid Mohajeri, Michael Davies, and Clare Heaviside
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-259, https://doi.org/10.5194/essd-2022-259, 2022
Revised manuscript accepted for ESSD
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Adding plants to the roofs of buildings can reduce both indoor and outdoor temperatures, so can reduce urban overheating which is expected to increase due to climate change and urban growth. To better understand the effect this has on the urban environment, we need data on how many buildings have green roofs already. We used a computer vision model to find green roofs in aerial imagery in London, producing a dataset identifying what buildings have green roofs and improving on previous methods.
Elena Aragoneses, Mariano García, Michele Salis, Luís M. Ribeiro, and Emilio Chuvieco
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-184, https://doi.org/10.5194/essd-2022-184, 2022
Revised manuscript accepted for ESSD
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The authors present a new fuel classification system with a total of 85 fuels, useful for different spatial scales and purposes. Based on it, the authors developed a European fuel map (1 km resolution) using land cover datasets, biogeographic datasets, and bioclimatic modelling. The authors validated the map by comparing it to high-resolution data, obtaining high overall accuracy. Finally, the authors developed a crosswalk to standard fuel models as a first assignment of fuel parameters.
Cited articles
Abdi, A. M.:
Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data, GISci Remote Sens., 57, 1–20, https://doi.org/10.1080/15481603.2019.1650447, 2020.
ABoVE Science Definition Team:
A Concise Experiment Plan for the Arctic-Boreal Vulnerability Experiment, ORNL DAAC, Oak Ridge, Tennessee, USA, [data set], https://doi.org/10.3334/ORNLDAAC/1617, 2014.
Agisoft LLC: Agisoft PhotoScan Professional, Version 1.4.3; Agisoft LLC: St. Petersburg, Russia, 2018.
Alexander, H., Paulson, A., DeMarco, J., Hewitt, R., Lichstein, J., Loranty, M., Mack, M., McEwan, R., Borth, E., Frankenberg, S., and Robinson, S.:
Fire influences on forest recovery and associated climate feedbacks in Siberian Larch Forests, Russia, 2018–2019, Arctic Data Center, https://doi.org/10.18739/A2XG9FB90, 2020.
Astola, H., Seitsonen, L., Halme, E., Molinier, M., and Lönnqvist, A.:
Deep Neural Networks with Transfer Learning for Forest Variable Estimation Using Sentinel-2 Imagery in Boreal Forest, Remote Sens.-Basel, 13, 2392, https://doi.org/10.3390/rs13122392, 2021.
Beamish, A., Raynolds, M. K., Epstein, H., Frost, G. V., Macander, M. J., Bergstedt, H., Bartsch, A., Kruse, S., Miles, V., Tanis, C. M, Heim, B., Fuchs, M., Chabrillat, S., Shevtsova, I., Verdonen, M., and Wagner, J.:
Recent trends and remaining challenges for optical remote sensing of Arctic tundra vegetation: A review and outlook, Remote Sens. Environ., 246, 111872, https://doi.org/10.1016/j.rse.2020.111872, 2020.
Bonan, G. B.:
Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests, Science, 320, 1444–1449, https://doi.org/10.1126/science.1155121, 2008.
Braga, J. R. G., Peripato, V., Dalagnol, R. P., Ferreira, M., Tarabalka, Y. O. C., Aragão L. E. F., de Campos Velho, H., Shiguemori, E. H., and Wagner, F. H.:
Tree Crown Delineation Algorithm Based on a Convolutional Neural Network, Remote Sens.-Basel, 12, 1288, https://doi.org/10.3390/rs12081288, 2020.
Brieger, F., Herzschuh, U., Pestryakova, L. A., Bookhagen, B., Zakharov, E. S., and Kruse, S.:
Advances in the derivation of Northeast Siberian forest metrics using high-resolution UAV-based photogrammetric point cloud, Remote Sens.-Basel, 11, 1447, https://doi.org/10.3390/rs11121447, 2019.
CAVM Team: Circumpolar arctic vegetation map (
Chave, J., Davies, S. J., Phillips, O. L., Lewis, S. L., Sist, P., Schepaschenko, D., Armston, J., Baker, T. R., Coomes, D., Disney, M., Duncanson, L., Hérault, B., Labrière, N., Meyer, V., Réjou-Méchain, M., Scipal, K., and Saatchi, S.:
Ground Data are Essential for Biomass Remote Sensing Missions, Surv. Geophys., 40, 863–880, https://doi.org/10.1007/s10712-019-09528-w, 2019.
CloudCompare:
CloudCompare, version 2.10, GPL software, [software], http://www.cloudcompare.org/ (last access: 7 July 2021), 2022.
Copernicus:
Copernicus Digital Elevation Model Product Handbook: https://spacedata.copernicus.eu/documents/20126/0/GEO1988-CopernicusDEM-SPE-002_ProductHandbook_I4.0.pdf/849f4329-873d-50f4-652c-57490de7b9aa?t=1656003026551 (last access: 21 January 2021), 2021.
ESA (European Space Agency):
Sentinel-2 User Handbook, Issue 1.2, 64 pp, 2015.
ESA (European Space Agency):
Sentinel-2 S2MPC, Sen2Cor Software Release Note, S2-PDGS-MPC-L2A-SRN-V2.9.0, 30 November 2020, Sen2Cor v2.9 – STEP, https://www.esa.int (last access 6 May 2021), 2021.
Fraser, R. H., Olthof, I., Lantz, T. C., and Schmitt, C.:
UAV photogrammetry for mapping vegetation in the low-Arctic, Arctic Science, 2, 79–102, https://doi.org/10.1139/as-2016-0008, 2016.
Hao, Z., Lin, L., Post, C. J., Mikhailova, E. A., Li, M., Chen, Y., and Liu, J.:
Automated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN), ISPRS J Photogramm., 178, 112–123, https://doi.org/10.1016/j.isprsjprs.2021.06.003, 2021.
He, K., Gkioxari, G., Dollár, P., and Girshick, R.:
Mask R-CNN, 2017 IEEE International Conference on Computer Vision (ICCV), 2980–2988, Venice, Italy, 22–29 October 2017, https://doi.org/10.1109/ICCV.2017.322, 2017.
Herzschuh, U.:
Legacy of the Last Glacial on the present-day distribution of deciduous versus evergreen boreal forest, Global Ecol. Biogeogr., 29, 198–206, https://doi.org/10.1111/geb.13018, 2020.
Jensen, J. L. R. and Mathews, A. J.:
Assessment of image-based point cloud products to generate a bare earth surface and estimate canopy heights in a woodland ecosystem, Remote Sens.-Basel, 8, 50, https://doi.org/10.3390/rs8010050, 2016.
Kelley, A.:
Complete Guide to Creating COCO Datasets, GitHub repository [code], https://github.com/akTwelve/cocosynth (last access: 30 July 2019), 2019.
Kruse, S., Bolshiyanov, D., Grigoriev, M. N., Morgenstern, A., Pestryakova, L., Tsibizov, L., and Udke, A.:
Russian-German Cooperation: Expeditions to Siberia in 2018, Reports on Polar and Marine Research, Alfred Wegener Institute for Polar and Marine Research, 734, 257 p., https://doi.org/10.2312/BzPM_0734_2019, 2019a.
Kruse, S., Herzschuh, U., Stünzi, S., Vyse, S., and Zakharov, E.:
Sampling mixed species boreal forests affected by disturbances and mountain lake mountain lake and alas lake coring in Central Yakutia, in: Russian–German Cooperation: Expeditions to Siberia in 2018, Reports on polar and marine research (148–153), edited by: Kruse, S., Bolshiyanov, D., Grigoriev, M. N., Morgenstern, A., Pestryakova, L., Tsibizov, L., and Udke, A., Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, https://doi.org/10.2312/BzPM_0734_2019, 2019b.
Kruse, S., Herzschuh, U., Schulte, L., Stuenzi, S. M., Brieger, F., Zakharov, E. S., and Pestryakova, L. A.:
Forest inventories on circular plots on the expedition Chukotka 2018, NE Russia, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.923638, 2020a.
Kruse, S., Farkas, L., Brieger, F., Geng, R., Heim, B., Pestryakova, L. A., Herzschuh, U., and van Geffen, F.:
SiDroForest: Orthomosaics, SfM point clouds and products from aerial image data of expedition vegetation plots in 2018 in Central Yakutia and Chukotka, Siberia, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.933263, 2021.
Lin, T. Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., and Zitnick, C. L.:
Microsoft COCO: Common objects in context, in: European Conference on Computer Vision, 6–12 September 2014, 740–755, Springer, Cham, 2014.
Long, Y., Xia, G. S., Li, S., Yang, W., Yang, M., Y., Zhu, X. X., Zhang, L., and Li, D.:
DiRS: On Creating Benchmark Datasets for Remote Sensing Image Interpretation, CoRR, arXiv [preprint], https://doi.org/10.48550/arXiv.2006.12485, 2020.
Loranty, M. M., Abbott, B. W., Blok, D., Douglas, T. A., Epstein, H. E., Forbes, B. C., Jones, B. M., Kholodov, A. L., Kropp, H., Malhotra, A., Mamet, S. D., Myers-Smith, I. H., Natali, S. M., O'Donnell, J. A., Phoenix, G. K., Rocha, A. V., Sonnentag, O., Tape, K. D., and Walker, D. A.: Reviews and syntheses: Changing ecosystem influences on soil thermal regimes in northern high-latitude permafrost regions, Biogeosciences, 15, 5287–5313, https://doi.org/10.5194/bg-15-5287-2018, 2018.
MacDonald, G. M., Kremenetski, K. V., and Beilman, D. W.:
Climate change and the northern Russian treeline zone, Philos. T. R. Soc. B, 363, 2283–2299, https://doi.org/10.1098/rstb.2007.2200, 2007.
Maguire, A. J., Eitel, J., Vierling, L., Boelman, N., Griffin, K., Jennewein, J. S., and Jensen, J. E.:
ABoVE: Terrestrial Lidar Scanning Forest-Tundra Ecotone, Brooks Range, Alaska, 2016, ORNL DAAC, Oak Ridge, Tennessee, USA, [data set], https://doi.org/10.3334/ORNLDAAC/1782, 2020.
Mamet, S. D., Brown, C. D., Trant, A. J., and Laroque, C. P.:
Shifting global Larix distributions: Northern expansion and southern retraction as species respond to changing climate, J. Biogeogr., 46, 30–44, https://doi.org/10.1111/jbi.13465, 2019.
Miesner, T., Herzschuh, U., Pestryakova, L. A.,; Wieczorek, M., Kolmogorov, A., Heim, B., Zakharov, E. S., Shevtsova, I., Epp, L. S., Niemeyer, B., Jacobsen, I., Schröder, J., Trense, D., Schnabel, E., Schreiber, X., Bernhardt, N., Stuenzi, S. M., Brieger, F., Schulte, L., Smirnikov, V., Gloy, J., von Hippel, B., Jackisch, R., and Kruse, S.:
Tree data set from forest inventories in north-eastern Siberia, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.943547, 2022.
Montesano, P. M., Nelson, R. F., Dubayah, R. O., Sun, G., Cook, B. D., Ranson, K. J. R., and Kharuk, V.:
The uncertainty of biomass estimates from LiDAR and SAR across a boreal forest structure gradient, Remote Sens. Environ., 154, 398–407, https://doi.org/10.1016/j.rse.2014.01.027, 2014.
Montesano, P. M., Neigh, C. S., Sexton, J., Feng, M., Channan, S., Ranson, K. J., and Townshend, J. R.:
Calibration and validation of Landsat tree cover in the taiga–tundra ecotone. Remote Sens.-Basel, 8, 551, https://doi.org/10.3390/rs8070551, 2016.
Panagiotidis, D., Abdollahnejad, A., Surový, P., and Chiteculo, V.:
Determining tree height and crown diameter from high-resolution UAV imagery, Int J. Remote Sens., 38, 2392–2410, https://doi.org/10.1080/01431161.2016.1264028, 2017.
Plowright, A.: ForestTools: Analyzing Remotely Sensed Forest Data, R Package Version 0.2.0., https://github.com/andrew-plowright/ForestTools (last access: 17 May 2019), 2018.
R Core Team: R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, [software], https://www.R-project.org/ (last access: 6 April 2020), 2020.
Rees, W. G., Hofgaard, A., Boudreau, S., Cairns, D. M., Harper, K., Mamet, S., and Tutubalina, O.:
Is subarctic forest advance able to keep pace with climate change?, Glob. Change Biol., 26, 3965–3977, https://doi.org/10.1111/gcb.15113, 2020.
Schepaschenko, D., Shvidenko, A., Usoltsev, V., Lakyda, P., Luo, Y., Vasylyshyn, R., Lakyda, I., Myklush, Y., See, L., McCallum, I., Fritz, S., Kraxner, F., and Obersteiner, M.:
A dataset of forest biomass structure for Eurasia, Scientific Data, 4, 170070, https://doi.org/10.1038/sdata.2017.70, 2017.
Schepaschenko D., Chave J., Phillips O. L., Lewis S. L., Davies S. J., Réjou-Méchain M., Sist P., and Scipal K.:
The Forest Observation System, building a global reference dataset for remote sensing of forest biomass, Scientific Data, 6, 198, https://doi.org/10.1038/s41597-019-0196-1, 2019.
Schepaschenko, D., Moltchanova, E., Fedorov, S., Karminov, V., Ontikov, P., Santoro, M., See, L., Kositsyn, V., Shvidenko, A., Romanovskaya, A., Korotkov, V., Lesiv, M., Bartalev, S., Fritz, S., Shchepashchenko, M., and Kraxner, F.:
Russian forest sequesters substantially more carbon than previously reported, Sci. Rep.-UK, 11, 12825, https://doi.org/10.1038/s41598-021-92152-9, 2021.
Shevtsova, I., Herzschuh, U., Heim, B., Kruse, S., Schröder, J., Troeva, E., Pestryakova, L. A., and Zakharov, E. S.:
Foliage projective cover of 57 vegetation sites of central Chukotka from 2016, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.908570, 2019.
Shevtsova, I., Heim, B., Kruse, S., Schröder, J., Troeva, E., Pestryakova, L. A., Zakharov, E. S., and Herzschuh, U.:
Strong shrub expansion in tundra-taiga, tree infilling in taiga and stable tundra in central Chukotka (north-eastern Siberia) between 2000 and 2017, Environ. Res. Lett., 15, https://doi.org/10.1088/1748-9326/ab9059, 2020a.
Shevtsova, I., Kruse, S., Herzschuh, U., Schulte, L., Brieger, F., Stuenzi, S. M., Heim, B., Troeva, E. I., Pestryakova, L. A., and Zakharov, E. S.:
Foliage projective cover of 40 vegetation sites of central Chukotka from 2018, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.923664, 2020b.
Shevtsova, I., Kruse, S., Herzschuh, U., Schulte, L., Brieger, F., Stuenzi, S. M., Heim, B., Troeva, E. I., Pestryakova, L. A., and Zakharov, E. S.:
Total above-ground biomass of 39 vegetation sites of central Chukotka from 2018, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.923719, 2020c.
Shevtsova, I., Herzschuh, U., Heim, B., Schulte, L., Stünzi, S., Pestryakova, L. A., Zakharov, E. S., and Kruse, S.:
Recent above-ground biomass changes in central Chukotka (Russian Far East) using field sampling and Landsat satellite data, Biogeosciences, 18, 3343–3366, https://doi.org/10.5194/bg-18-3343-2021, 2021.
Simard, M., Pinto, N., Fisher, J. B., and Baccini, A.:
Mapping Forest canopy height globally with spaceborne lidar, J. Geophys. Res, 116, G04021, https://doi.org/10.1029/2011JG001708, 2011.
Sumbul. G., Charfuelan, M., Demir, B., and Markl, V.:
BigEarthNet: A Large-Scale Benchmark Archive for Remote Sensing Image Understanding, IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2 July–2 August 2019, 5901–5904, 2019.
Thanh Noi, P. and Kappas, M.:
Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery, Sensors, 18, https://doi.org/10.3390/s18010018, 2018.
The GIMP Development Team:
GIMP, retrieved from https://www.gimp.org (last access: 20 January 2020), 2019.
Troeva, E. I., Isaev, A. P., Cherosov, M. M., and Karpov, N. S. (Eds.):
The Far North: Plant Biodiversity and Ecology of Yakutia, Vol. 3. Springer Science & Business Media, ISBN 9789400731936, 2010.
van Geffen, F., Brieger, F., Pestryakova, L. A., Herzschuh, U., and Kruse, S.:
SiDroForest: Synthetic Siberian Larch Tree Crown Dataset of 10 000 instances in the Microsoft's Common Objects in Context dataset (coco) format, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.932795, 2021a.
van Geffen, F., Geng, R., Pflug, B., Kruse, S., Pestryakova, L. A, Herzschuh, U., and Heim, B.:
SiDroForest: Sentinel-2 Level-2 Bottom of Atmosphere labelled image patches with seasonal information for Central Yakutia and Chukotka vegetation plots (Siberia, Russia), PANGAEA [data set], https://doi.org/10.1594/PANGAEA.933268, 2021b.
van Geffen, F., Schulte, L., Geng, R., Heim, B., Pestryakova, L. A., Herzschuh, U., and Kruse, S.:
SiDroForest: Individual-labelled trees acquired during the fieldwork expeditions that took place in 2018 in Central Yakutia and Chukotka, Siberia, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.932821, 2021c.
Walker, D. A., Raynolds, M. K., Daniëls, F. J., Einarsson, E., Elvebakk, A., Gould, W. A., Katenin, A. E., Kholod, S. S., Markon, C. J., Melnikov, E. S., Moskalenko, N. G., Talbot, S. S., Yurtsev, B. A., and The other members of the CAVM Team: The Circumpolar Arctic vegetation map, J. Veg. Sci., 16, 267–282, https://doi.org/10.1111/j.1654-1103.2005.tb02365.x, 2005.
Wang, D., Wan, B., Liu, J., Su, Y., Guo, Q., Qiu, P., and Wu, X.:
Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery, Int. J. Appl. Earth Obs., 85, 101986, https://doi.org/10.1016/j.jag.2019.101986, 2020.
Weinstein, B. G., Marconi, S, Bohlman, S., Zare, A., and White, E.:
Individual Tree-Crown Detection in RGB Imagery Using Semi-Supervised Deep Learning Neural Networks, Remote Sens.-Basel, 11, 1309, https://doi.org/10.3390/rs11111309, 2019.
Weinstein, B. G., Marconi, S, Bohlman, S., Zare, A., Singh, A., Graves, S. J., and White, E.:
A remote sensing derived data set of 100 million individual tree crowns for the National Ecological Observatory Network, eLife, 10:e62922, https://doi.org/10.7554/eLife.62922, 2021.
Xiao, K., Engstrom, L., Ilyas, A., and Madry, A.:
Noise or signal: The role of image backgrounds in object recognition, arXiv [preprint], https://doi.org/10.48550/arXiv.2006.09994, 2020.
Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X., and Yan, G.:
An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sens.-Basel, 8, 501, https://doi.org/10.3390/rs8060501, 2016.
Short summary
SiDroForest is an attempt to remedy data scarcity regarding vegetation data in the circumpolar region, whilst providing adjusted and labeled data for machine learning and upscaling practices. SiDroForest contains four datasets that include SfM point clouds, individually labeled trees, synthetic tree crowns and labeled Sentinel-2 patches that provide insights into the vegetation composition and forest structure of two important vegetation transition zones in Siberia, Russia.
SiDroForest is an attempt to remedy data scarcity regarding vegetation data in the circumpolar...
