Articles | Volume 14, issue 4
https://doi.org/10.5194/essd-14-1735-2022
© 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-14-1735-2022
© 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
| 
13 Apr 2022
Data description paper |
| 13 Apr 2022
| 13 Apr 2022
High-resolution land use and land cover dataset for regional climate modelling: a plant functional type map for Europe 2015
Vanessa Reinhart
CORRESPONDING AUTHOR
Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Fischertwiete 1, 20095 Hamburg, Germany
Institute of Geography, Section Physical Geography, Center for Earth System Research and Sustainability (CEN), Cluster of Excellence “Climate, Climatic Change, and Society” (CLICCS), Universität Hamburg, Bundesstraße 55, 20146 Hamburg, Germany
Peter Hoffmann
Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Fischertwiete 1, 20095 Hamburg, Germany
Institute of Geography, Section Physical Geography, Center for Earth System Research and Sustainability (CEN), Cluster of Excellence “Climate, Climatic Change, and Society” (CLICCS), Universität Hamburg, Bundesstraße 55, 20146 Hamburg, Germany
Diana Rechid
Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Fischertwiete 1, 20095 Hamburg, Germany
Jürgen Böhner
Institute of Geography, Section Physical Geography, Center for Earth System Research and Sustainability (CEN), Cluster of Excellence “Climate, Climatic Change, and Society” (CLICCS), Universität Hamburg, Bundesstraße 55, 20146 Hamburg, Germany
Benjamin Bechtel
Department of Geography, Ruhr-Universität Bochum, Universitätsstraße 150/Gebäude IA, 44801 Bochum, Germany
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Earth Syst. Sci. Data, 15, 3819–3852, https://doi.org/10.5194/essd-15-3819-2023, https://doi.org/10.5194/essd-15-3819-2023, 2023
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This paper introduces the new high-resolution land use and land cover change dataset LUCAS LUC for Europe (version 1.1), tailored for use in regional climate models. Historical and projected future land use change information from the Land-Use Harmonization 2 (LUH2) dataset is translated into annual plant functional type changes from 1950 to 2015 and 2016 to 2100, respectively, by employing a newly developed land use translator.
Peter Hoffmann, Vanessa Reinhart, Diana Rechid, Nathalie de Noblet-Ducoudré, Edouard L. Davin, Christina Asmus, Benjamin Bechtel, Jürgen Böhner, Eleni Katragkou, and Sebastiaan Luyssaert
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-252, https://doi.org/10.5194/essd-2021-252, 2021
Manuscript not accepted for further review
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This paper introduces the new high-resolution land-use land-cover change dataset LUCAS LUC historical and future land use and land cover change dataset (Version 1.0), tailored for use in regional climate models. Historical and projected future land use change information from the Land-Use Harmonization 2 (LUH2) dataset is translated into annual plant functional type changes from 1950 to 2015 and 2016 to 2100, respectively, by employing a newly developed land use translator.
Joni-Pekka Pietikäinen, Kevin Sieck, Lars Buntemeyer, Thomas Frisius, Christine Nam, Peter Hoffmann, Christina Pop, Diana Rechid, and Daniela Jacob
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Our research, involving 22 European scientists, investigated drought and heat impacts on forests in 2018–2022. Findings reveal that climate extremes are intensifying, with central Europe being most severely impacted. The southern region showed resilience due to historical drought exposure, while northern and Alpine areas experienced emerging or minimal impacts. The study highlights the need for region-specific strategies, improved data collection, and sustainable practices to safeguard forests.
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Earth Syst. Sci. Data, 15, 3819–3852, https://doi.org/10.5194/essd-15-3819-2023, https://doi.org/10.5194/essd-15-3819-2023, 2023
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Nat. Hazards Earth Syst. Sci., 22, 3015–3039, https://doi.org/10.5194/nhess-22-3015-2022, https://doi.org/10.5194/nhess-22-3015-2022, 2022
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Myocardial infarctions (MIs; heart attacks) are influenced by temperature extremes, air pollution, lack of green spaces and ageing population. Here, we apply machine learning (ML) models in order to estimate the influence of various environmental and demographic risk factors. The resulting ML models can accurately reproduce observed annual variability in MI and inter-annual trends. The models allow quantification of the importance of individual factors and can be used to project future risk.
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.
Swantje Preuschmann, Tanja Blome, Knut Görl, Fiona Köhnke, Bettina Steuri, Juliane El Zohbi, Diana Rechid, Martin Schultz, Jianing Sun, and Daniela Jacob
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Geosci. Model Dev., 11, 1641–1652, https://doi.org/10.5194/gmd-11-1641-2018, https://doi.org/10.5194/gmd-11-1641-2018, 2018
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Ramchandra Karki, Shabeh ul Hasson, Lars Gerlitz, Udo Schickhoff, Thomas Scholten, and Jürgen Böhner
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Shabeh Hasson, Jürgen Böhner, and Valerio Lucarini
Earth Syst. Dynam., 8, 337–355, https://doi.org/10.5194/esd-8-337-2017, https://doi.org/10.5194/esd-8-337-2017, 2017
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Karakoram Anomaly.
B. Bechtel, M. Pesaresi, L. See, G. Mills, J. Ching, P. J. Alexander, J. J. Feddema, A. J. Florczyk, and I. Stewart
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B. Bechtel
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 243–250, https://doi.org/10.5194/isprs-archives-XLI-B8-243-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-243-2016, 2016
O. Conrad, B. Bechtel, M. Bock, H. Dietrich, E. Fischer, L. Gerlitz, J. Wehberg, V. Wichmann, and J. Böhner
Geosci. Model Dev., 8, 1991–2007, https://doi.org/10.5194/gmd-8-1991-2015, https://doi.org/10.5194/gmd-8-1991-2015, 2015
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M. Klinge, J. Böhner, and S. Erasmi
Biogeosciences, 12, 2893–2905, https://doi.org/10.5194/bg-12-2893-2015, https://doi.org/10.5194/bg-12-2893-2015, 2015
U. Schickhoff, M. Bobrowski, J. Böhner, B. Bürzle, R. P. Chaudhary, L. Gerlitz, H. Heyken, J. Lange, M. Müller, T. Scholten, N. Schwab, and R. Wedegärtner
Earth Syst. Dynam., 6, 245–265, https://doi.org/10.5194/esd-6-245-2015, https://doi.org/10.5194/esd-6-245-2015, 2015
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Near-natural Himalayan treelines are usually krummholz treelines, which are relatively unresponsive to climate change. Intense recruitment of treeline trees suggests a great potential for future treeline advance. Competitive abilities of tree seedlings within krummholz thickets and dwarf scrub heaths will be a major source of variation in treeline dynamics. Tree growth-climate relationships show mature treeline trees to be responsive in particular to high pre-monsoon temperature trends.
L. Gerlitz, O. Conrad, and J. Böhner
Earth Syst. Dynam., 6, 61–81, https://doi.org/10.5194/esd-6-61-2015, https://doi.org/10.5194/esd-6-61-2015, 2015
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In order to assess high-resolution precipitation fields for the Tibetan Plateau and the Himalayan Arc, a novel downscaling approach is presented which integrates traditional statistical downscaling and GIS-based terrain parameterization techniques. The approach enables a detailed analysis of the precipitation heterogeinity over the complex target area.
S. Hasson, V. Lucarini, S. Pascale, and J. Böhner
Earth Syst. Dynam., 5, 67–87, https://doi.org/10.5194/esd-5-67-2014, https://doi.org/10.5194/esd-5-67-2014, 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
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Earth Syst. Sci. Data, 17, 2535–2551, https://doi.org/10.5194/essd-17-2535-2025, https://doi.org/10.5194/essd-17-2535-2025, 2025
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The currently available urban canopy parameter (UCP) datasets are limited to just a few cities for urban climate simulations by the Weather Research and Forecasting (WRF) model. To address this gap, we develop a global 1 km spatially continuous UCP dataset (GloUCP) which provides superior spatial coverage and higher accuracy in capturing urban morphology across diverse regions. It has great potential to support further advancements in urban climate modeling and related applications.
Ruoque Shen, Qiongyan Peng, Xiangqian Li, Xiuzhi Chen, and Wenping Yuan
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Rice is a vital staple crop that plays a crucial role in food security in China. However, long-term high-resolution rice distribution maps in China are lacking. This study developed a new rice-mapping method, mitigating the impact of cloud contamination and missing data in optical remote sensing observations on rice mapping. The resulting dataset, CCD-Rice (China Crop Dataset-Rice), achieved high accuracy and showed a strong correlation with statistical data.
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Earth Syst. Sci. Data, 17, 2147–2174, https://doi.org/10.5194/essd-17-2147-2025, https://doi.org/10.5194/essd-17-2147-2025, 2025
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Michael MacFerrin, Christopher Amante, Kelly Carignan, Matthew Love, and Elliot Lim
Earth Syst. Sci. Data, 17, 1835–1849, https://doi.org/10.5194/essd-17-1835-2025, https://doi.org/10.5194/essd-17-1835-2025, 2025
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Here we present Earth TOPOgraphy (ETOPO) 2022, the latest iteration of NOAA's global seamless topographic–bathymetric dataset. ETOPO 2022 is a significant upgrade regarding resolution and accuracy from previous ETOPO releases and is freely available in multiple data formats and resolutions for all uses (public or private), excepting navigation.
Jingling Jiang, Hong Zhang, Ji Ge, Lijun Zuo, Lu Xu, Mingyang Song, Yinhaibin Ding, Yazhe Xie, and Wenjiang Huang
Earth Syst. Sci. Data, 17, 1781–1805, https://doi.org/10.5194/essd-17-1781-2025, https://doi.org/10.5194/essd-17-1781-2025, 2025
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This study uses temporal synthetic aperture radar (SAR) data and optical imagery to conduct rice-mapping experiments in 34 African countries with rice-planting areas exceeding 5000 ha in 2022, achieving a 20 m resolution spatial distribution mapping for 2023. The average classification accuracy based on the validation set exceeded 85 %, and the R2; values for linear fitting with existing statistical data all surpassed 0.9, demonstrating the effectiveness of the proposed mapping method.
Zihang Lou, Dailiang Peng, Zhou Shi, Hongyan Wang, Yaqiong Zhang, Xue Yan, Zhongxing Chen, Su Ye, Le Yu, Jinkang Hu, Yulong Lv, Hao Peng, Yizhou Zhang, and Bing Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-133, https://doi.org/10.5194/essd-2025-133, 2025
Revised manuscript accepted for ESSD
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This study created the first detailed annual maps of Africa's cropland extent from 2000 to 2022 in 30 m resolution to support global efforts against hunger and sustainable farming. Our findings show Africa's cropland grew by 8.5 % over two decade, while 11.5 % of cropland was abandoned by 2018 – revealing hidden challenges in agricultural sustainability. These yearly, field-sized maps help governments track where farming grows or shrinks, plan food supplies, and protect vital cropland.
David A. Gibbs, Melissa Rose, Giacomo Grassi, Joana Melo, Simone Rossi, Viola Heinrich, and Nancy L. Harris
Earth Syst. Sci. Data, 17, 1217–1243, https://doi.org/10.5194/essd-17-1217-2025, https://doi.org/10.5194/essd-17-1217-2025, 2025
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Updated global maps of greenhouse gas (GHG) emissions and sequestration by forests from 2001 onwards using satellite-derived data show that forests are strong net carbon sinks, capturing about as much CO2 each year on average as the USA emitted from fossil fuels in 2019. After reclassifying fluxes to countries’ reporting categories for national GHG inventories, we found that roughly two-thirds of the net CO2 flux from forests is anthropogenic and one-third is non-anthropogenic.
Zhenghang Yuan, Zhitong Xiong, Lichao Mou, and Xiao Xiang Zhu
Earth Syst. Sci. Data, 17, 1245–1263, https://doi.org/10.5194/essd-17-1245-2025, https://doi.org/10.5194/essd-17-1245-2025, 2025
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ChatEarthNet is an image–text dataset that provides high-quality, detailed natural language descriptions for global-scale satellite data. It consists of 163 488 image-text pairs with captions generated by ChatGPT-3.5 and an additional 10 000 image-text pairs with captions generated by ChatGPT-4V(ision). This dataset has significant potential for training and evaluating vision–language geo-foundation models in remote sensing.
Xiao Zhang, Liangyun Liu, Tingting Zhao, Wenhan Zhang, Linlin Guan, Ming Bai, and Xidong Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-73, https://doi.org/10.5194/essd-2025-73, 2025
Revised manuscript accepted for ESSD
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This work describes a novel global 10 m land-cover dataset with fine classification system, which contains 30 land-cover subcategories and achieves the fulfilling performance over the globe.
Simon Boitard, Arnaud Mialon, Stéphane Mermoz, Nemesio J. Rodríguez-Fernández, Philippe Richaume, Julio César Salazar-Neira, Stéphane Tarot, and Yann H. Kerr
Earth Syst. Sci. Data, 17, 1101–1119, https://doi.org/10.5194/essd-17-1101-2025, https://doi.org/10.5194/essd-17-1101-2025, 2025
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Aboveground biomass (AGB) is a critical component of the Earth's carbon cycle. The presented dataset aims to help monitor this essential climate variable with AGB time series from 2011 onward, derived with a carefully calibrated spatial relationship between the measurements of the Soil Moisture and Ocean Salinity (SMOS) mission and pre-existing AGB maps. The produced dataset has been extensively compared with other available AGB time series and can be used in AGB studies.
Nicolas Lampach, Jon Olav Skoien, Helena Ramos, Julien Gaffuri, Renate Koeble, Linda See, and Marijn Van der Velde
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-59, https://doi.org/10.5194/essd-2025-59, 2025
Revised manuscript accepted for ESSD
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Eurostat and JRC developed a new methodology to make geospatial data from agricultural census available to users, while ensuring that no confidential information from individuals is disclosed. The geospatial data presented in the article correspond to the contextual indicators of the monitoring and evaluation framework of the Common Agricultural Policy. Our exploratory analysis reveals several interesting patterns which contribute to the broader debate on the future of European agriculture.
Fuyou Tian, Bingfang Wu, Hongwei Zeng, Miao Zhang, Weiwei Zhu, Nana Yan, Yuming Lu, and Yifan Li
Earth Syst. Sci. Data, 17, 855–880, https://doi.org/10.5194/essd-17-855-2025, https://doi.org/10.5194/essd-17-855-2025, 2025
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Our study introduces GMIE, a high-resolution global map of irrigated cropland at 100 m resolution, covering 403.17 Mha and utilizing irrigation performance under drought stress. We found that 23.4 % of global cropland is irrigated, with the most extensive areas in India, China, the United States, and Pakistan. We identified the distribution of central pivot systems commonly used in the United States and Saudi Arabia. This new map can better support water management and food security globally.
Guangsheng Zhou, Hongrui Ren, Lei Zhang, Xiaomin Lv, and Mengzi Zhou
Earth Syst. Sci. Data, 17, 773–797, https://doi.org/10.5194/essd-17-773-2025, https://doi.org/10.5194/essd-17-773-2025, 2025
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This study developed a new approach to long-time continuous annual vegetation mapping from remote sensing imagery, and mapped the vegetation of the Qinghai–Tibet Plateau (QTP) from 2000 to 2022 using the MOD09A1 product. The overall accuracy of continuous annual QTP vegetation mapping reached 83.3%, with the reference annual 2020 data reaching an accuracy of 83.3% and a kappa coefficient of 0.82. The study supports the use of remote sensing data to mapping long-time continuous annual vegetation.
Xuemeng Tian, Davide Consoli, Martijn Witjes, Florian Schneider, Leandro Parente, Murat Şahin, Yu-Feng Ho, Robert Minařík, and Tomislav Hengl
Earth Syst. Sci. Data, 17, 741–772, https://doi.org/10.5194/essd-17-741-2025, https://doi.org/10.5194/essd-17-741-2025, 2025
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Our study introduces a Landsat-based data cube simplifying access to detailed environmental data across Europe from 2000 to 2022, covering vegetation, water, soil, and crops. Our experiments demonstrate its effectiveness in developing environmental models and maps. Tailored feature selection is crucial for its effective use in environmental modeling. It aims to support comprehensive environmental monitoring and analysis, helping researchers and policy-makers in managing environmental resources.
Mingyang Song, Lu Xu, Ji Ge, Hong Zhang, Lijun Zuo, Jingling Jiang, Yinhaibin Ding, Yazhe Xie, and Fan Wu
Earth Syst. Sci. Data, 17, 661–683, https://doi.org/10.5194/essd-17-661-2025, https://doi.org/10.5194/essd-17-661-2025, 2025
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We created a 10 m resolution rice distribution map for East Asia in 2023 (EARice10), achieving an overall accuracy (OA) of 90.48 % on validation samples. EARice10 shows strong consistency with statistical data (coefficient of determination, R2: 0.94–0.98) and existing datasets (R2: 0.79–0.98). It is the most up-to-date map, covering the four major rice-producing countries in East Asia at 10 m resolution.
Maximilian Freudenberg, Sebastian Schnell, and Paul Magdon
Earth Syst. Sci. Data, 17, 351–367, https://doi.org/10.5194/essd-17-351-2025, https://doi.org/10.5194/essd-17-351-2025, 2025
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Classifying tree species in satellite images is an important task for environmental monitoring and forest management. Here we present a dataset containing Sentinel-2 satellite pixel time series of individual trees intended for training machine learning models. The dataset was created by merging information from the German National Forest Inventory in 2012 with satellite data. It sparsely covers the whole of Germany for the years 2015 to 2022 and comprises 48 species and 3 species groups.
Yangyang Fu, Xiuzhi Chen, Chaoqing Song, Xiaojuan Huang, Jie Dong, Qiongyan Peng, and Wenping Yuan
Earth Syst. Sci. Data, 17, 95–115, https://doi.org/10.5194/essd-17-95-2025, https://doi.org/10.5194/essd-17-95-2025, 2025
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This study proposed the Winter-Triticeae Crops Index (WTCI), which had great performance and stable spatiotemporal transferability in identifying winter-triticeae crops in 66 countries worldwide, with an overall accuracy of 87.7 %. The first global 30 m resolution distribution maps of winter-triticeae crops from 2017 to 2022 were further produced based on the WTCI method. The product can serve as an important basis for agricultural applications.
Jiahao Shi, Hua Yuan, Wanyi Lin, Wenzong Dong, Hongbin Liang, Zhuo Liu, Jianxin Zeng, Haolin Zhang, Nan Wei, Zhongwang Wei, Shupeng Zhang, Shaofeng Liu, Xingjie Lu, and Yongjiu Dai
Earth Syst. Sci. Data, 17, 117–134, https://doi.org/10.5194/essd-17-117-2025, https://doi.org/10.5194/essd-17-117-2025, 2025
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Flux tower data are widely recognized as benchmarking data for land surface models, but insufficient emphasis on and deficiency in site attribute data limits their true value. We collect site-observed vegetation, soil, and topography data from various sources. The final dataset encompasses 90 sites globally, with relatively complete site attribute data and high-quality flux validation data. This work has provided more reliable site attribute data, benefiting land surface model development.
Binghong Han, Jian Bi, Shengli Tao, Tong Yang, Yongli Tang, Mengshuai Ge, Hao Wang, Zhenong Jin, Jinwei Dong, Zhibiao Nan, and Jin-Sheng He
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-620, https://doi.org/10.5194/essd-2024-620, 2025
Revised manuscript accepted for ESSD
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The Tibetan Plateau is an important pastoral area where cultivated pastures play an increasingly important role. However, little is known about the spatial distribution of the cultivated pasture due to the difficulty in distinguishing them from natural grasslands with remote sensing. For the first time, we have mapped the cultivated pastures on the plateau at a resolution of 30 meters with decent accuracy. This data set is valuable to scientists, policy makers, conservationists and pastoralists.
Yanghai Yu, Yang Lei, Paul Siqueira, Xiaotong Liu, Denuo Gu, Anmin Fu, Yong Pang, Wenli Huang, and Jiancheng Shi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-596, https://doi.org/10.5194/essd-2024-596, 2025
Revised manuscript accepted for ESSD
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This paper presents a global-to-local method to improve forest height estimates by fusing InSAR and GEDI data. The large-scale ability was tested on open-access ALOS-1 data, where a two-fold solution is used to address temporal gap between GEDI and ALOS data. Produced products of 30 m gridded forest height mosaics for the northeastern U.S. and China show improved accuracy at 3–4 m/ha and 20 % enhancement over interpolated GEDI maps. The prototype is promising to fuse GEDI and future NISAR data.
Raphaël d'Andrimont, Momchil Yordanov, Fernando Sedano, Astrid Verhegghen, Peter Strobl, Savvas Zachariadis, Flavia Camilleri, Alessandra Palmieri, Beatrice Eiselt, Jose Miguel Rubio Iglesias, and Marijn van der Velde
Earth Syst. Sci. Data, 16, 5723–5735, https://doi.org/10.5194/essd-16-5723-2024, https://doi.org/10.5194/essd-16-5723-2024, 2024
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The Land Use/Cover Area frame Survey (LUCAS) Copernicus 2022 is a large and systematic in situ field survey of 137 966 polygons over the European Union in 2022. The data contain 82 land cover classes and 40 land use classes.
Shuang Chen, Jie Wang, Qiang Liu, Xiangan Liang, Rui Liu, Peng Qin, Jincheng Yuan, Junbo Wei, Shuai Yuan, Huabing Huang, and Peng Gong
Earth Syst. Sci. Data, 16, 5449–5475, https://doi.org/10.5194/essd-16-5449-2024, https://doi.org/10.5194/essd-16-5449-2024, 2024
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The inconsistent coverage of Landsat data due to its long revisit intervals and frequent cloud cover poses challenges to large-scale land monitoring. We developed a global 30 m 23-year (2000–2022) daily seamless data cube (SDC) of surface reflectance based on Landsat 5, 7, 8, and 9 and MODIS products. The SDC exhibits enhanced capabilities for monitoring land cover changes and robust consistency in both spatial and temporal dimensions, which are important for global environmental monitoring.
Gerardo E. Soto, Steven W. Wilcox, Patrick E. Clark, Francesco P. Fava, Nathaniel D. Jensen, Njoki Kahiu, Chuan Liao, Benjamin Porter, Ying Sun, and Christopher B. Barrett
Earth Syst. Sci. Data, 16, 5375–5404, https://doi.org/10.5194/essd-16-5375-2024, https://doi.org/10.5194/essd-16-5375-2024, 2024
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This paper uses machine learning and linear unmixing to produce rangeland health indicators: Landsat time series of land cover classes and vegetation fractional cover of photosynthetic vegetation, non-photosynthetic vegetation, and bare ground in arid and semi-arid Kenya, Ethiopia, and Somalia. This represents the first multi-decadal Landsat-resolution dataset specifically designed for mapping and monitoring rangeland health in the arid and semi-arid rangelands of this portion of eastern Africa.
Yangzi Che, Xuecao Li, Xiaoping Liu, Yuhao Wang, Weilin Liao, Xianwei Zheng, Xucai Zhang, Xiaocong Xu, Qian Shi, Jiajun Zhu, Honghui Zhang, Hua Yuan, and Yongjiu Dai
Earth Syst. Sci. Data, 16, 5357–5374, https://doi.org/10.5194/essd-16-5357-2024, https://doi.org/10.5194/essd-16-5357-2024, 2024
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Most existing building height products are limited with respect to either spatial resolution or coverage, not to mention the spatial heterogeneity introduced by global building forms. Using Earth Observation (EO) datasets for 2020, we developed a global height dataset at the individual building scale. The dataset provides spatially explicit information on 3D building morphology, supporting both macro- and microanalysis of urban areas.
Yuling Chen, Haitao Yang, Zekun Yang, Qiuli Yang, Weiyan Liu, Guoran Huang, Yu Ren, Kai Cheng, Tianyu Xiang, Mengxi Chen, Danyang Lin, Zhiyong Qi, Jiachen Xu, Yixuan Zhang, Guangcai Xu, and Qinghua Guo
Earth Syst. Sci. Data, 16, 5267–5285, https://doi.org/10.5194/essd-16-5267-2024, https://doi.org/10.5194/essd-16-5267-2024, 2024
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The national-scale continuous maps of arithmetic mean height and weighted mean height across China address the challenges of accurately estimating forest stand mean height using a tree-based approach. These maps produced in this study provide critical datasets for forest sustainable management in China, including climate change mitigation (e.g., terrestrial carbon estimation), forest ecosystem assessment, and forest inventory practices.
Jia Zhou, Jin Niu, Ning Wu, and Tao Lu
Earth Syst. Sci. Data, 16, 5171–5189, https://doi.org/10.5194/essd-16-5171-2024, https://doi.org/10.5194/essd-16-5171-2024, 2024
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The study provided an annual 100 m resolution glimpse into the grazing activities across the Qinghai–Tibet Plateau. The newly minted Gridded Dataset of Grazing Intensity (GDGI) not only boasts exceptional accuracy but also acts as a pivotal resource for further research and strategic planning, with the potential to shape sustainable grazing practices, guide informed environmental stewardship, and ensure the longevity of the region’s precious ecosystems.
Adrià Descals, David L. A. Gaveau, Serge Wich, Zoltan Szantoi, and Erik Meijaard
Earth Syst. Sci. Data, 16, 5111–5129, https://doi.org/10.5194/essd-16-5111-2024, https://doi.org/10.5194/essd-16-5111-2024, 2024
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This study provides a 10 m global oil palm extent layer for 2021 and a 30 m oil palm planting-year layer from 1990 to 2021. The oil palm extent layer was produced using a convolutional neural network that identified industrial and smallholder plantations using Sentinel-1 data. The oil palm planting year was developed using a methodology specifically designed to detect the early stages of oil palm development in the Landsat time series.
Ran Jia, Xiuqi Fang, Yundi Yang, Masayuki Yokozawa, and Yu Ye
Earth Syst. Sci. Data, 16, 4971–4994, https://doi.org/10.5194/essd-16-4971-2024, https://doi.org/10.5194/essd-16-4971-2024, 2024
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We reconstructed a cropland area change dataset in Northeast China over the past millennium by integrating multisource data with a unified standard using the historical and archaeological record, statistical yearbook, and national land survey. Cropland in Northeast China exhibited phases of expansion–reduction–expansion over the past millennium. This dataset can be used for improving the land use and land cover change (LUCC) dataset and assessing LUCC-induced carbon emission and climate change.
Stefania Di Tommaso, Sherrie Wang, Rob Strey, and David B. Lobell
Earth Syst. Sci. Data, 16, 4931–4947, https://doi.org/10.5194/essd-16-4931-2024, https://doi.org/10.5194/essd-16-4931-2024, 2024
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Sugarcane plays a vital role in food, biofuel, and farmer income globally, yet its cultivation faces numerous social and environmental challenges. Despite its significance, accurate mapping remains limited. Our study addresses this gap by introducing a novel 10 m global dataset of sugarcane maps spanning 2019–2022. Comparisons with field data, pre-existing maps, and official government statistics all indicate the high precision and high recall of our maps.
Juliette Bernard, Catherine Prigent, Carlos Jimenez, Etienne Fluet-Chouinard, Bernhard Lehner, Elodie Salmon, Philippe Ciais, Zhen Zhang, Shushi Peng, and Marielle Saunois
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-466, https://doi.org/10.5194/essd-2024-466, 2024
Revised manuscript accepted for ESSD
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Wetlands are responsible for about a third of global emissions of methane, a potent greenhouse gas. We have developed the GIEMS-MethaneCentric (GIEMS-MC) dataset to represent the dynamics of wetland extent on a global scale (0.25°x0.25° resolution, monthly time step). This updated resource combines satellite data and existing wetland databases, covering 1992 to 2020. Consistent maps of other methane-emitting surface waters (lakes, rivers, reservoirs, rice paddies) are also provided.
Jie Wang, Xiangming Xiao, Yuanwei Qin, Jinwei Dong, Geli Zhang, Xuebin Yang, Xiaocui Wu, Chandrashekhar Biradar, and Yang Hu
Earth Syst. Sci. Data, 16, 4619–4639, https://doi.org/10.5194/essd-16-4619-2024, https://doi.org/10.5194/essd-16-4619-2024, 2024
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Existing satellite-based forest maps have large uncertainties due to different forest definitions and mapping algorithms. To effectively manage forest resources, timely and accurate annual forest maps at a high spatial resolution are needed. This study improved forest maps by integrating PALSAR-2 and Landsat images. Annual evergreen and non-evergreen forest-type maps were also generated. This critical information supports the Global Forest Resources Assessment.
Xin Zhao, Kazuya Nishina, Haruka Izumisawa, Yuji Masutomi, Seima Osako, and Shuhei Yamamoto
Earth Syst. Sci. Data, 16, 3893–3911, https://doi.org/10.5194/essd-16-3893-2024, https://doi.org/10.5194/essd-16-3893-2024, 2024
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Mapping a rice calendar in a spatially explicit manner with a consistent framework remains challenging at a global or continental scale. We successfully developed a new gridded rice calendar for monsoon Asia based on Sentinel-1 and Sentinel-2 images, which characterize transplanting and harvesting dates and the number of rice croppings in a comprehensive framework. Our rice calendar will be beneficial for rice management, production prediction, and the estimation of greenhouse gas emissions.
Yuehong Chen, Congcong Xu, Yong Ge, Xiaoxiang Zhang, and Ya'nan Zhou
Earth Syst. Sci. Data, 16, 3705–3718, https://doi.org/10.5194/essd-16-3705-2024, https://doi.org/10.5194/essd-16-3705-2024, 2024
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Population data is crucial for human–nature interactions. Gridded population data can address limitations of census data in irregular units. In China, rapid urbanization necessitates timely and accurate population grids. However, existing datasets for China are either outdated or lack recent census data. Hence, a novel approach was developed to disaggregate China’s seventh census data into 100 m population grids. The resulting dataset outperformed the existing LandScan and WorldPop datasets.
Zia Mehrabi, Kaitai Tong, Julie Fortin, Radost Stanimirova, Mark Friedl, and Navin Ramankutty
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-279, https://doi.org/10.5194/essd-2024-279, 2024
Revised manuscript accepted for ESSD
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We present a global geospatial database of cropland and pastures representing the year 2015. We made it using machine learning models to merge satellite-based land cover data with agricultural census data that we compiled. This database is an update to an earlier version representing the year 2000. It can be used to study issues such as land use, food security, climate change and biodiversity loss. We provide a reproducible code base to easily update the product for future years.
Shuchao Ye, Peiyu Cao, and Chaoqun Lu
Earth Syst. Sci. Data, 16, 3453–3470, https://doi.org/10.5194/essd-16-3453-2024, https://doi.org/10.5194/essd-16-3453-2024, 2024
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We reconstructed annual cropland density and crop type maps, including nine major crop types (corn, soybean, winter wheat, spring wheat, durum wheat, cotton, sorghum, barley, and rice), from 1850 to 2021 at 1 km × 1 km resolution. We found that the US total crop acreage has increased by 118 × 106 ha (118 Mha), mainly driven by corn (30 Mha) and soybean (35 Mha). Additionally, the US cropping diversity experienced an increase in the 1850s–1960s, followed by a decline over the past 6 decades.
Fang Chen, Lei Wang, Yu Wang, Haiying Zhang, Ning Wang, Pengfei Ma, and Bo Yu
Earth Syst. Sci. Data, 16, 3369–3382, https://doi.org/10.5194/essd-16-3369-2024, https://doi.org/10.5194/essd-16-3369-2024, 2024
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Storage tanks are responsible for approximately 25 % of CH4 emissions in the atmosphere, exacerbating climate warming. Currently there is no publicly accessible storage tank inventory. We generated the first high-spatial-resolution (1–2 m) storage tank dataset (STD) over 92 typical cities in China in 2021, totaling 14 461 storage tanks with the construction year from 2000–2021. It shows significant agreement with CH4 emission spatially and temporally, promoting the CH4 control strategy proposal.
Xingyi Huang, Yuwei Yin, Luwei Feng, Xiaoye Tong, Xiaoxin Zhang, Jiangrong Li, and Feng Tian
Earth Syst. Sci. Data, 16, 3307–3332, https://doi.org/10.5194/essd-16-3307-2024, https://doi.org/10.5194/essd-16-3307-2024, 2024
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The Tibetan Plateau, with its diverse vegetation ranging from forests to alpine grasslands, plays a key role in understanding climate change impacts. Existing maps lack detail or miss unique ecosystems. Our research, using advanced satellite technology and machine learning, produced the map TP_LC10-2022. Comparisons with other maps revealed TP_LC10-2022's excellence in capturing local variations. Our map is significant for in-depth ecological studies.
Qinghang Mei, Zhao Zhang, Jichong Han, Jie Song, Jinwei Dong, Huaqing Wu, Jialu Xu, and Fulu Tao
Earth Syst. Sci. Data, 16, 3213–3231, https://doi.org/10.5194/essd-16-3213-2024, https://doi.org/10.5194/essd-16-3213-2024, 2024
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In order to make up for the lack of long-term soybean planting area maps in China, we firstly generated a dataset of soybean planting area with a spatial resolution of 10 m for major producing areas in China from 2017 to 2021 (ChinaSoyArea10m). Compared with existing datasets, ChinaSoyArea10m has higher consistency with census data and further improvement in spatial details. The dataset can provide reliable support for subsequent studies on yield monitoring and food security.
Yavar Pourmohamad, John T. Abatzoglou, Erin J. Belval, Erica Fleishman, Karen Short, Matthew C. Reeves, Nicholas Nauslar, Philip E. Higuera, Eric Henderson, Sawyer Ball, Amir AghaKouchak, Jeffrey P. Prestemon, Julia Olszewski, and Mojtaba Sadegh
Earth Syst. Sci. Data, 16, 3045–3060, https://doi.org/10.5194/essd-16-3045-2024, https://doi.org/10.5194/essd-16-3045-2024, 2024
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The FPA FOD-Attributes dataset provides > 300 biological, physical, social, and administrative attributes associated with > 2.3×106 wildfire incidents across the US from 1992 to 2020. The dataset can be used to (1) answer numerous questions about the covariates associated with human- and lightning-caused wildfires and (2) support descriptive, diagnostic, predictive, and prescriptive wildfire analytics, including the development of machine learning models.
Ewa Grabska-Szwagrzyk, Dirk Tiede, Martin Sudmanns, and Jacek Kozak
Earth Syst. Sci. Data, 16, 2877–2891, https://doi.org/10.5194/essd-16-2877-2024, https://doi.org/10.5194/essd-16-2877-2024, 2024
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We accurately mapped 16 dominant tree species and genera in Poland using Sentinel-2 observations from short periods in spring, summer, and autumn (2018–2021). The classification achieved more than 80% accuracy in country-wide forest species mapping, with variation based on species, region, and observation frequency. Freely accessible resources, including the forest tree species map and training and test data, can be found at https://doi.org/10.5281/zenodo.10180469.
Charles E. Miller, Peter C. Griffith, Elizabeth Hoy, Naiara S. Pinto, Yunling Lou, Scott Hensley, Bruce D. Chapman, Jennifer Baltzer, Kazem Bakian-Dogaheh, W. Robert Bolton, Laura Bourgeau-Chavez, Richard H. Chen, Byung-Hun Choe, Leah K. Clayton, Thomas A. Douglas, Nancy French, Jean E. Holloway, Gang Hong, Lingcao Huang, Go Iwahana, Liza Jenkins, John S. Kimball, Tatiana Loboda, Michelle Mack, Philip Marsh, Roger J. Michaelides, Mahta Moghaddam, Andrew Parsekian, Kevin Schaefer, Paul R. Siqueira, Debjani Singh, Alireza Tabatabaeenejad, Merritt Turetsky, Ridha Touzi, Elizabeth Wig, Cathy J. Wilson, Paul Wilson, Stan D. Wullschleger, Yonghong Yi, Howard A. Zebker, Yu Zhang, Yuhuan Zhao, and Scott J. Goetz
Earth Syst. Sci. Data, 16, 2605–2624, https://doi.org/10.5194/essd-16-2605-2024, https://doi.org/10.5194/essd-16-2605-2024, 2024
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NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) conducted airborne synthetic aperture radar (SAR) surveys of over 120 000 km2 in Alaska and northwestern Canada during 2017, 2018, 2019, and 2022. This paper summarizes those results and provides links to details on ~ 80 individual flight lines. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band SAR data.
Ying Tu, Shengbiao Wu, Bin Chen, Qihao Weng, Yuqi Bai, Jun Yang, Le Yu, and Bing Xu
Earth Syst. Sci. Data, 16, 2297–2316, https://doi.org/10.5194/essd-16-2297-2024, https://doi.org/10.5194/essd-16-2297-2024, 2024
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We developed the first 30 m annual cropland dataset of China (CACD) for 1986–2021. The overall accuracy of CACD reached up to 0.93±0.01 and was superior to other products. Our fine-resolution cropland maps offer valuable information for diverse applications and decision-making processes in the future.
Lingcheng Li, Gautam Bisht, Dalei Hao, and L. Ruby Leung
Earth Syst. Sci. Data, 16, 2007–2032, https://doi.org/10.5194/essd-16-2007-2024, https://doi.org/10.5194/essd-16-2007-2024, 2024
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This study fills a gap to meet the emerging needs of kilometer-scale Earth system modeling by developing global 1 km land surface parameters for land use, vegetation, soil, and topography. Our demonstration simulations highlight the substantial impacts of these parameters on spatial variability and information loss in water and energy simulations. Using advanced explainable machine learning methods, we identified influential factors driving spatial variability and information loss.
Hui Li, Xiaobo Wang, Shaoqiang Wang, Jinyuan Liu, Yuanyuan Liu, Zhenhai Liu, Shiliang Chen, Qinyi Wang, Tongtong Zhu, Lunche Wang, and Lizhe Wang
Earth Syst. Sci. Data, 16, 1689–1701, https://doi.org/10.5194/essd-16-1689-2024, https://doi.org/10.5194/essd-16-1689-2024, 2024
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Utilizing satellite remote sensing data, we established a multi-season rice calendar dataset named ChinaRiceCalendar. It exhibits strong alignment with field observations collected by agricultural meteorological stations across China. ChinaRiceCalendar stands as a reliable dataset for investigating and optimizing the spatiotemporal dynamics of rice phenology in China, particularly in the context of climate and land use changes.
Giulia Ronchetti, Luigi Nisini Scacchiafichi, Lorenzo Seguini, Iacopo Cerrani, and Marijn van der Velde
Earth Syst. Sci. Data, 16, 1623–1649, https://doi.org/10.5194/essd-16-1623-2024, https://doi.org/10.5194/essd-16-1623-2024, 2024
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We present a dataset of EU-wide harmonized subnational crop area, production, and yield statistics with information on data sources, processing steps, missing and derived data, and quality checks. Statistical records (344 282) collected from 1975 to 2020 for soft and durum wheat, winter and spring barley, grain maize, sunflower, and sugar beet were aligned with the EUROSTAT crop legend and the 2016 territorial classification for 961 regions. Time series have a median length of 21 years.
Xiao Zhang, Tingting Zhao, Hong Xu, Wendi Liu, Jinqing Wang, Xidong Chen, and Liangyun Liu
Earth Syst. Sci. Data, 16, 1353–1381, https://doi.org/10.5194/essd-16-1353-2024, https://doi.org/10.5194/essd-16-1353-2024, 2024
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This work describes GLC_FCS30D, the first global 30 m land-cover dynamics monitoring dataset, which contains 35 land-cover subcategories and covers the period of 1985–2022 in 26 time steps (its maps are updated every 5 years before 2000 and annually after 2000).
Qiangqiang Sun, Ping Zhang, Xin Jiao, Xin Lin, Wenkai Duan, Su Ma, Qidi Pan, Lu Chen, Yongxiang Zhang, Shucheng You, Shunxi Liu, Jinmin Hao, Hong Li, and Danfeng Sun
Earth Syst. Sci. Data, 16, 1333–1351, https://doi.org/10.5194/essd-16-1333-2024, https://doi.org/10.5194/essd-16-1333-2024, 2024
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To provide multifaceted changes under climate change and anthropogenic impacts, we estimated monthly vegetation and soil fractions in 2001–2022, providing an accurate estimate of surface heterogeneous composition, better than vegetation index and vegetation continuous-field products. We find a greening trend on Earth except for the tropics. A combination of interactive changes in vegetation and soil can be adopted as a valuable measurement of climate change and anthropogenic impacts.
Kai Cheng, Yuling Chen, Tianyu Xiang, Haitao Yang, Weiyan Liu, Yu Ren, Hongcan Guan, Tianyu Hu, Qin Ma, and Qinghua Guo
Earth Syst. Sci. Data, 16, 803–819, https://doi.org/10.5194/essd-16-803-2024, https://doi.org/10.5194/essd-16-803-2024, 2024
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To quantify forest carbon stock and its future potential accurately, we generated a 30 m resolution forest age map for China in 2020 using multisource remote sensing datasets based on machine learning and time series analysis approaches. Validation with independent field samples indicated that the mapped forest age had an R2 of 0.51--0.63. Nationally, the average forest age is 56.1 years (standard deviation of 32.7 years).
Wolfgang Alexander Obermeier, Clemens Schwingshackl, Ana Bastos, Giulia Conchedda, Thomas Gasser, Giacomo Grassi, Richard A. Houghton, Francesco Nicola Tubiello, Stephen Sitch, and Julia Pongratz
Earth Syst. Sci. Data, 16, 605–645, https://doi.org/10.5194/essd-16-605-2024, https://doi.org/10.5194/essd-16-605-2024, 2024
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We provide and compare country-level estimates of land-use CO2 fluxes from a variety and large number of models, bottom-up estimates, and country reports for the period 1950–2021. Although net fluxes are small in many countries, they are often composed of large compensating emissions and removals. In many countries, the estimates agree well once their individual characteristics are accounted for, but in other countries, including some of the largest emitters, substantial uncertainties exist.
Cameron I. Ludemann, Nathan Wanner, Pauline Chivenge, Achim Dobermann, Rasmus Einarsson, Patricio Grassini, Armelle Gruere, Kevin Jackson, Luis Lassaletta, Federico Maggi, Griffiths Obli-Laryea, Martin K. van Ittersum, Srishti Vishwakarma, Xin Zhang, and Francesco N. Tubiello
Earth Syst. Sci. Data, 16, 525–541, https://doi.org/10.5194/essd-16-525-2024, https://doi.org/10.5194/essd-16-525-2024, 2024
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Nutrient budgets help identify the excess or insufficient use of fertilizers and other nutrient sources in agriculture. They allow the calculation of indicators, such as the nutrient balance (surplus or deficit) and nutrient use efficiency, that help to monitor agricultural productivity and sustainability. This article describes a global cropland nutrient budget that provides data on 205 countries and territories from 1961 to 2020 (data available at https://www.fao.org/faostat/en/#data/ESB).
Cited articles
Alkama, R. and Cescatti, A.: Biophysical climate impacts of recent changes in
global forest cover, Science, 351, 600–604, 2016. a
Anderegg, L. D. L., Griffith, D. M., Cavender-Bares, J., Riley, W. J., Berry,
J. A., Dawson, T. E., and Still, C. J.: Representing plant diversity in land
models: An evolutionary approach to make “Functional Types” more
functional, Glob. Change Biol., 28, 2541–2554,
https://doi.org/10.1111/gcb.16040, 2021. a
Bégué, A., Arvor, D., Bellon, B., Betbeder, J., De Abelleyra, D.,
Ferraz, R. P. D., Lebourgeois, V., Lelong, C., Simões, M., and Verón,
S. R.: Remote sensing and cropping practices: A review, Remote Sensing, 10, 99, https://doi.org/10.3390/rs10010099,
2018. a
Belda, M., Halenka, T., Huszar, P., Karlicky, J., and Nováková, T.: Do
we need urban parameterization in high resolution regional climate
simulations?, in: AGU Fall Meeting Abstracts, 2018AGUFM.A21L2878B,
2018. a
Bojinski, S., Verstraete, M., Peterson, T. C., Richter, C., Simmons, A., and
Zemp, M.: The concept of essential climate variables in support of climate
research, applications, and policy, B. Am. Meteorol.
Soc., 95, 1431–1443, 2014. a
Bonan, G. B.: Forests and climate change: forcings, feedbacks, and the climate
benefits of forests, Science, 320, 1444–1449, 2008. a
Bonan, G. B., Levis, S., Kergoat, L., and Oleson, K. W.: Landscapes as patches
of plant functional types: An integrating concept for climate and ecosystem
models, Global Biogeochem. Cy., 16, 5-1–5-23, https://doi.org/10.1029/2000GB001360, 2002. a, b
Bontemps S., Defourny P., Radoux J., Van Bogaert E., Lamarche C., Achard F., Mayaux P., Boettcher M., Brockmann C., Kirches G., Zülkhe M., Kalogirou V., Seifert F.M., and Arino O.: Consistent
global land cover maps for climate modelling communities: current
achievements of the ESA’s land cover CCI, in: Proceedings of the ESA living
planet symposium, Edinburgh, 9–13 September 2013, pp. 9–13, 2013. a
Box, E. O.: Plant functional types and climate at the global scale, J.
Veg. Sci., 7, 309–320, 1996. a
Bright, R. M., Zhao, K., Jackson, R. B., and Cherubini, F.: Quantifying surface
albedo and other direct biogeophysical climate forcings of forestry
activities, Glob. Change Biol., 21, 3246–3266, 2015. a
Burke, M. and Emerick, K.: Adaptation to climate change: Evidence from US
agriculture, Am. Econ. J.-Econ. Pol., 8, 106–40, 2016. a
Chapin III, F. S., McGuire, A. D., Randerson, J., Pielke Sr., R., Baldocchi, D., Hobbie,
S. E., Roulet, N., Eugster, W., Kasischke, E., Rastetter, E. B., Zimov, S. A., and Running, S. W.: Arctic
and boreal ecosystems of western North America as components of the climate
system, Glob. Change Biol., 6, 211–223, 2000. a
Chen, X., Zhang, X.-S., and Li, B.-L.: The possible response of life zones in
China under global climate change, Global Planet. Change, 38, 327–337,
2003. a
Conrad, O., Bechtel, B., Bock, M., Dietrich, H., Fischer, E., Gerlitz, L., Wehberg, J., Wichmann, V., and Böhner, J.: System for Automated Geoscientific Analyses (SAGA) v. 2.1.4, Geosci. Model Dev., 8, 1991–2007, https://doi.org/10.5194/gmd-8-1991-2015, 2015. a
Cornes, R. C., van der Schrier, G., van den Besselaar, E. J., and Jones, P. D.:
An ensemble version of the E-OBS temperature and precipitation data sets,
J. Geophys. Res.-Atmos., 123, 9391–9409, 2018. a
Daly, C., Helmer, E. H., and Quiñones, M.: Mapping the climate of puerto
rico, vieques and culebra, Int. J. Climatol., 23, 1359–1381, 2003. a
Daniel, M., Lemonsu, A., Déqué, M., Somot, S., Alias, A., and Masson,
V.: Benefits of explicit urban parameterization in regional climate modeling
to study climate and city interactions, Clim. Dynam., 52, 2745–2764,
2019. a
Davin, E. L., Rechid, D., Breil, M., Cardoso, R. M., Coppola, E., Hoffmann, P., Jach, L. L., Katragkou, E., de Noblet-Ducoudré, N., Radtke, K., Raffa, M., Soares, P. M. M., Sofiadis, G., Strada, S., Strandberg, G., Tölle, M. H., Warrach-Sagi, K., and Wulfmeyer, V.: Biogeophysical impacts of forestation in Europe: first results from the LUCAS (Land Use and Climate Across Scales) regional climate model intercomparison, Earth Syst. Dynam., 11, 183–200, https://doi.org/10.5194/esd-11-183-2020, 2020. a, b
Di Gregorio, A.: Land cover classification system: classification concepts and
user manual: LCCS, vol. 2, Food and Agriculture Organization of the United Nations, Rome, ISBN 92-5-105327-8, 2005. a
Dierckx, W., Sterckx, S., Benhadj, I., Livens, S., Duhoux, G., Van Achteren,
T., Francois, M., Mellab, K., and Saint, G.: PROBA-V mission for global
vegetation monitoring: standard products and image quality, Int.
J. Remote Sens., 35, 2589–2614, 2014. a
Donlon, C., Berruti, B., Buongiorno, A., Ferreira, M.-H., Féménias, P.,
Frerick, J., Goryl, P., Klein, U., Laur, H., Mavrocordatos, C., Nieke, J., Rebhan, H., Seitz, B., Stroede, J., and Sciarrac, R.: The
global monitoring for environment and security (GMES) sentinel-3 mission,
Remote Sens. Environ., 120, 37–57, 2012. a
d’Andrimont, R., Yordanov, M., Martinez-Sanchez, L., Eiselt, B., Palmieri,
A., Dominici, P., Gallego, J., Reuter, H. I., Joebges, C., Lemoine, G., and
van der Velde, M.: Harmonised LUCAS in-situ land cover and use database for field
surveys from 2006 to 2018 in the European Union, Scientific Data, 7, 352, https://doi.org/10.1038/s41597-020-00675-z,
2020. a
ESA: MERIS Product Handbook, Issue: 2.1, https://earth.esa.int/eogateway/documents/20142/37627/MERIS-product-handbook.pdf, (last access: 4 April 2022), 2006. a
ESA: Land Cover CCI Product User Guide Version 2, Tech. Rep., http://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf (last access: 4 April 2022), 2017b. a
Foody, G. M.: Status of land cover classification accuracy assessment, Remote
Sens. Environ., 80, 185–201, 2002. a
Ge, J., Qi, J., Lofgren, B. M., Moore, N., Torbick, N., and Olson, J. M.:
Impacts of land use/cover classification accuracy on regional climate
simulations, J. Geophys. Res.-Atmos., 112, D05107, https://doi.org/10.1029/2006JD007404, 2007. a
Harris, I., Jones, P., Osborn, T., and Lister, D.: Updated high-resolution
grids of monthly climatic observations – the CRU TS3.10 Dataset,
Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711,
2014. a
Hartley, A., MacBean, N., Georgievski, G., and Bontemps, S.: Uncertainty in
plant functional type distributions and its impact on land surface models,
Remote Sens. Environ., 203, 71–89, 2017. a
Hastings, D. A. and Emery, W. J.: The advanced very high resolution radiometer
(AVHRR) – A brief reference guide, Photogramm. Eng. Rem.
S., 58, 1183–1188, 1992. a
Hoffmann, P., Katzfey, J., McGregor, J., and Thatcher, M.: Bias and variance
correction of sea surface temperatures used for dynamical downscaling,
J. Geophys. Res.-Atmos., 121, 12-877–12-890, 2016. a
Hua, T., Zhao, W., Liu, Y., Wang, S., and Yang, S.: Spatial consistency
assessments for global land-cover datasets: A comparison among GLC2000, CCI
LC, MCD12, GLOBCOVER and GLCNMO, Remote Sensing, 10, 1846, https://doi.org/10.3390/rs10111846, 2018. a, b
Hurtt, G. C., Chini, L. P., Frolking, S., Betts, R. A., Feddema, J., Fischer, G.,
Fisk, J. P., Hibbard, K., Houghton, R. A., Jones, C. D., Kindermann, G., Kinoshita, T., Klein Goldewijk, K., Riahi, K., Shevliakova, E., Smith, S., Stehfest, E., Thomson, A., Thornton, P., van Vuuren, D. P., and Wang, Y. P.:
Harmonization of
land-use scenarios for the period 1500–2100: 600 years of global gridded
annual land-use transitions, wood harvest, and resulting secondary lands,
Climatic Change, 109, 117–161, https://doi.org/10.1007/s10584-011-0153-2, 2011. a
Jung, M., Henkel, K., Herold, M., and Churkina, G.: Exploiting synergies of
global land cover products for carbon cycle modeling, Remote Sens.
Environ., 101, 534–553, 2006. a
Karthikeyan, L., Chawla, I., and Mishra, A. K.: A review of remote sensing
applications in agriculture for food security: Crop growth and yield,
irrigation, and crop losses, J. Hydrology, 586, 124905, https://doi.org/10.1016/j.jhydrol.2020.124905, 2020. a
Khatun, K., Imbach, P., and Zamora, J.: An assessment of climate change impacts
on the tropical forests of Central America using the Holdridge Life Zone
(HLZ) land classification system, iForest-Biogeosciences and Forestry, 6,
183–189, https://doi.org/10.3832/ifor0743-006, 2013. a
Kueppers, L. M., Snyder, M. A., and Sloan, L. C.: Irrigation cooling effect:
Regional climate forcing by land-use change, Geophys. Res. Lett.,
34, L03703, https://doi.org/10.1029/2006GL028679, 2007. a
Lattanzi, F. A.: C3/C4 grasslands and climate change, in: Proceedings of the 23rd General Meeting of the European Grassland Federation, Kiel, Germany, 29 August–2 September 2010, Mecke Druck und Verlag, 3–13, ISBN 978-3-86944-021-7, 2010. a
Lavorel, S., Díaz, S., Cornelissen, J. H. C., Garnier, E., Harrison,
S. P., McIntyre, S., Pausas, J. G., Pérez-Harguindeguy, N., Roumet, C.,
and Urcelay, C.: Plant functional types: are we getting any closer to the
Holy Grail?, in: Terrestrial ecosystems in a changing world, 1st edn., edited by: Canadell, J. G., Pataki, D. E., and Pitelka, L. F., pp. 149–164,
Springer, ISBN 978-3-540-32730-1, https://doi.org/10.1007/978-3-540-32730-1_13, 2007. a
Lawrence, D. and Vandecar, K.: Effects of tropical deforestation on climate and
agriculture, Nat. Clim. Change, 5, 27–36, 2015. a
Li, L., Yang, Z.-L., Matheny, A. M., Zheng, H., Swenson, S. C., Lawrence,
D. M., Barlage, M., Yan, B., McDowell, N. G., and Leung, L. R.:
Representation of Plant Hydraulics in the Noah-MP Land Surface Model: Model
Development and Multiscale Evaluation, J. Adv. Model. Earth
Sy., 13, e2020MS002214, https://doi.org/10.1029/2020MS002214, 2021. a
Li, W., MacBean, N., Ciais, P., Defourny, P., Lamarche, C., Bontemps, S., Houghton, R. A., and Peng, S.: Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015), Earth Syst. Sci. Data, 10, 219–234, https://doi.org/10.5194/essd-10-219-2018, 2018. a, b, c, d, e
Lobell, D., Bala, G., and Duffy, P.: Biogeophysical impacts of cropland
management changes on climate, Geophys. Res. Lett., 33, L06708, https://doi.org/10.1029/2005GL025492, 2006. a
Lu, Y. and Kueppers, L. M.: Surface energy partitioning over four dominant
vegetation types across the United States in a coupled regional climate model
(Weather Research and Forecasting Model 3–Community Land Model 3.5), J. Geophys. Res.-Atmos., 117, D06111, https://doi.org/10.1029/2011JD016991, 2012. a
Lugo, A. E., Brown, S. L., Dodson, R., Smith, T. S., and Shugart, H. H.: The
Holdridge life zones of the conterminous United States in relation to
ecosystem mapping, J. Biogeogr., 26, 1025–1038, 1999. a
Mahmood, R., Pielke Sr., R. A., Hubbard, K. G., Niyogi, D., Dirmeyer, P. A.,
McAlpine, C., Carleton, A. M., Hale, R., Gameda, S., Beltrán-Przekurat,
A., Baker, B., McNider, R., Legates, D. R., Shepherd, M., Du, J., Blanken, P. D., Frauenfeld, O. W., Nair U. S., and Fallt, S.: Land cover changes and their biogeophysical effects on climate,
Int. J. Climatol., 34, 929–953, 2014. a
Maisongrande, P., Duchemin, B., and Dedieu, G.: VEGETATION/SPOT: an operational
mission for the Earth monitoring; presentation of new standard products,
Int. J. Remote Sens., 25, 9–14, 2004. a
Olofsson, P., Foody, G. M., Herold, M., Stehman, S. V., Woodcock, C. E., and
Wulder, M. A.: Good practices for estimating area and assessing accuracy of
land change, Remote Sens. Environ., 148, 42–57, 2014. a
Ottlé, C., Lescure, J., Maignan, F., Poulter, B., Wang, T., and Delbart, N.: Use of various remote sensing land cover products for plant functional type mapping over Siberia, Earth Syst. Sci. Data, 5, 331–348, https://doi.org/10.5194/essd-5-331-2013, 2013. a
Ottosen, T.-B., Lommen, S. T., and Skjøth, C. A.: Remote sensing of cropping
practice in Northern Italy using time-series from Sentinel-2, Comput.
Electron. Agr., 157, 232–238, 2019. a
Pau, S., Edwards, E. J., and Still, C. J.: Improving our understanding of
environmental controls on the distribution of C3 and C4 grasses, Global
Change Biol., 19, 184–196, 2013. a
Perugini, L., Caporaso, L., Marconi, S., Cescatti, A., Quesada, B.,
de Noblet-Ducoudre, N., House, J. I., and Arneth, A.: Biophysical effects on
temperature and precipitation due to land cover change, Environ.
Res. Lett., 12, 053002, https://doi.org/10.1088/1748-9326/aa6b3f, 2017. a
Poulter, B., Ciais, P., Hodson, E., Lischke, H., Maignan, F., Plummer, S., and Zimmermann, N. E.: Plant functional type mapping for earth system models, Geosci. Model Dev., 4, 993–1010, https://doi.org/10.5194/gmd-4-993-2011, 2011. a, b
Poulter, B., MacBean, N., Hartley, A., Khlystova, I., Arino, O., Betts, R., Bontemps, S., Boettcher, M., Brockmann, C., Defourny, P., Hagemann, S., Herold, M., Kirches, G., Lamarche, C., Lederer, D., Ottlé, C., Peters, M., and Peylin, P.: Plant functional type classification for earth system models: results from the European Space Agency's Land Cover Climate Change Initiative, Geosci. Model Dev., 8, 2315–2328, https://doi.org/10.5194/gmd-8-2315-2015, 2015. a, b, c
Rechid, D., Davin, E., de Noblet-Ducoudré, N., and Katragkou, E.: CORDEX Flagship Pilot Study LUCAS – Land Use & Climate Across Scales – a new initiative on coordinated regional land use change and climate experiments for Europe, in: 19th EGU General Assembly, EGU2017, Vienna, Austria, 23–28 April 2017, 19, p. 13172, 2017. a
Reinhart, V., Fonte, C. C., Hoffmann, P., Bechtel, B., Rechid, D., and
Böhner, J.: Comparison of ESA climate change initiative land cover to
CORINE land cover over Eastern Europe and the Baltic States from a regional
climate modeling perspective, Int. J. Appl. Earth
Obs., 94, 102221, https://doi.org/10.1016/j.jag.2020.102221, 2021a. a, b, c
Richardson, A. D., Keenan, T. F., Migliavacca, M., Ryu, Y., Sonnentag, O., and
Toomey, M.: Climate change, phenology, and phenological control of vegetation
feedbacks to the climate system, Agr. Forest Meteorol., 169,
156–173, 2013. a
Rufin, P., Frantz, D., Ernst, S., Rabe, A., Griffiths, P., Özdoğan,
M., and Hostert, P.: Mapping cropping practices on a national scale using
intra-annual landsat time series binning, Remote Sensing, 11, 232, https://doi.org/10.3390/rs11030232, 2019. a
Saad, R., Koellner, T., and Margni, M.: Land use impacts on freshwater
regulation, erosion regulation, and water purification: a spatial approach
for a global scale level, Int. J. Life Cycle Ass.,
18, 1253–1264, 2013. a
Santos-Alamillos, F., Pozo-Vázquez, D., Ruiz-Arias, J., and Tovar-Pescador,
J.: Influence of land-use misrepresentation on the accuracy of WRF wind
estimates: Evaluation of GLCC and CORINE land-use maps in southern Spain,
Atmos. Res., 157, 17–28, 2015. a
Sertel, E., Robock, A., and Ormeci, C.: Impacts of land cover data quality on
regional climate simulations, Int. J. Climatol., 30,
1942–1953, 2010. a
Siebert, S., Döll, P., Hoogeveen, J., Faures, J.-M., Frenken, K., and Feick, S.: Development and validation of the global map of irrigation areas, Hydrol. Earth Syst. Sci., 9, 535–547, https://doi.org/10.5194/hess-9-535-2005, 2005. a
Skov, F. and Svenning, J.-C.: Potential impact of climatic change on the
distribution of forest herbs in Europe, Ecography, 27, 366–380, 2004. a
Stehman, S. V.: Sampling designs for accuracy assessment of land cover,
Int. J. Remote Sens., 30, 5243–5272, 2009. a
Still, C. J., Berry, J. A., Collatz, G. J., and DeFries, R. S.: Global
distribution of C3 and C4 vegetation: carbon cycle implications, Global
Biogeochem. Cy., 17, 6–14, https://doi.org/10.1029/2001GB001807, 2003. a
Szelepcsényi, Z., Breuer, H., and Sümegi, P.: The climate of Carpathian
Region in the 20th century based on the original and modified Holdridge life
zone system, Centr. Eur. J. Geosci., 6, 293–307, 2014. a
Szelepcsényi, Z., Breuer, H., Kis, A., Pongrácz, R., and Sümegi,
P.: Assessment of projected climate change in the Carpathian Region using the
Holdridge life zone system, Theor. Appl. Climatol., 131,
593–610, 2018. a
Tatli, H. and Dalfes, H. N.: Defining Holdridge's life zones over Turkey,
Int. J. Climatol., 36, 3864–3872, 2016. a
Tatli, H. and Dalfes, H. N.: Analysis of temporal diversity of precipitation
along with biodiversity of Holdridge life zones, Theor. Appl.
Climatol., 144, 391–400, 2021. a
Thompson, C., Beringer, J., Chapin III, F. S., and McGuire, A. D.: Structural
complexity and land-surface energy exchange along a gradient from arctic
tundra to boreal forest, J. Veg. Sci., 15, 397–406, 2004. a
van Bodegom, P. M., Douma, J. C., and Verheijen, L. M.: A fully traits-based
approach to modeling global vegetation distribution, P.
Natl. Acad. Sci. USA, 111, 13733–13738,
https://doi.org/10.1073/pnas.1304551110, 2014. a
Wei, Y., Liu, S., Huntzinger, D., Michalak, A., Viovy, N., Post, W., Schwalm,
C., Schaefer, K., Jacobson, A., LU, C., Tian, H., Ricciuto, D., Cook, R.,
Mao, J., and Shi, X.: NACP MsTMIP: Global and North American Driver Data for
Multi-Model Intercomparison, NASA [data set], https://doi.org/10.3334/ORNLDAAC/1220, 2014. a, b, c
Winter, J. M., Pal, J. S., and Eltahir, E. A.: Coupling of integrated biosphere
simulator to regional climate model version 3, J. Climate, 22,
2743–2757, 2009. a
Wullschleger, S. D., Epstein, H. E., Box, E. O., Euskirchen, E. S., Goswami,
S., Iversen, C. M., Kattge, J., Norby, R. J., van Bodegom, P. M., and Xu, X.:
Plant functional types in Earth system models: past experiences and future
directions for application of dynamic vegetation models in high-latitude
ecosystems, Annals of Botany, 114, 1–16, https://doi.org/10.1093/aob/mcu077, 2014. a
Yang, Y., Zhu, Q., Peng, C., Wang, H., and Chen, H.: From plant functional
types to plant functional traits: A new paradigm in modelling global
vegetation dynamics, Prog. Phys. Geog.,
39, 514–535, https://doi.org/10.1177/0309133315582018, 2015. a
Yang, Y., Xiao, P., Feng, X., and Li, H.: Accuracy assessment of seven global
land cover datasets over China, ISPRS J. Photogramm., 125, 156–173, 2017. a
Yue, T., Liu, J., Jørgensen, S. E., Gao, Z., Zhang, S., and Deng, X.:
Changes of Holdridge life zone diversity in all of China over half a century,
Ecol. Model., 144, 153–162, 2001. a
Yue, T. X., Fan, Z. M., Liu, J. Y., and Wei, B. X.: Scenarios of major
terrestrial ecosystems in China, Ecol. Model., 199, 363–376, 2006. a
Short summary
The LANDMATE plant functional type (PFT) land cover dataset for Europe 2015 (Version 1.0) is a gridded, high-resolution dataset for use in regional climate models. LANDMATE PFT is prepared using the expertise of regional climate modellers all over Europe and is easily adjustable to fit into different climate model families. We provide comprehensive spatial quality information for LANDMATE PFT, which can be used to reduce uncertainty in regional climate model simulations.
The LANDMATE plant functional type (PFT) land cover dataset for Europe 2015 (Version 1.0) is a...
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