Articles | Volume 16, issue 10
https://doi.org/10.5194/essd-16-4971-2024
© Author(s) 2024. 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-16-4971-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
29 Oct 2024
Data description paper |
| 29 Oct 2024
| 29 Oct 2024
A 28-time-point cropland area change dataset in Northeast China from 1000 to 2020
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Faculty of Human Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa 359-1192, Japan
Xiuqi Fang
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Key Laboratory of Environmental Change and Natural Disaster of Chinese Ministry of Education, Beijing Normal University, Beijing 100875, China
Yundi Yang
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Masayuki Yokozawa
Faculty of Human Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa 359-1192, Japan
Yu Ye
CORRESPONDING AUTHOR
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Key Laboratory of Environmental Change and Natural Disaster of Chinese Ministry of Education, Beijing Normal University, Beijing 100875, China
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Xueqiong Wei, Mats Widgren, Beibei Li, Yu Ye, Xiuqi Fang, Chengpeng Zhang, and Tiexi Chen
Earth Syst. Sci. Data, 13, 3035–3056, https://doi.org/10.5194/essd-13-3035-2021, https://doi.org/10.5194/essd-13-3035-2021, 2021
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The cropland area of each administrative unit based on statistics in Scandinavia from 1690 to 1999 is allocated into 1 km grid cells. The cropland area increased from 1690 to 1950 and then decreasd in the following years, especially in southeastern Scandinavia. Comparing global datasets with this study, the spatial patterns show considerable differences. Our dataset is validated using satellite-based cropland cover data and results in previous studies.
Yachen Liu, Xiuqi Fang, Junhu Dai, Huanjiong Wang, and Zexing Tao
Clim. Past, 17, 929–950, https://doi.org/10.5194/cp-17-929-2021, https://doi.org/10.5194/cp-17-929-2021, 2021
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There are controversies about whether poetry can be used as one of the evidence sources for past climate changes. We tried to discuss the reliability and validity of phenological records from poems of the Tang and Song dynasties (618–1279 CE) by analyzing their certainties and uncertainties. A standardized processing method for phenological records from poems is introduced. We hope that this study can provide a reference for the extraction and application of phenological records from poems.
Siying Chen, Yun Su, Xiuqi Fang, and Jia He
Clim. Past, 16, 1873–1887, https://doi.org/10.5194/cp-16-1873-2020, https://doi.org/10.5194/cp-16-1873-2020, 2020
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Private diaries are important sources of historical data for research on climate change. Through a case study of Yunshan Diary, authored by Bi Guo of the Yuan dynasty of China, this article demonstrates how to delve into climate information in ancient diaries, mainly including species distribution records, phenological records and daily weather descriptions. This article considers how to use these records to reconstruct climate change and extreme climatic events on various timescales.
Related subject area
Domain: ESSD – Land | Subject: Land Cover and Land Use
Mapping sugarcane globally at 10 m resolution using Global Ecosystem Dynamics Investigation (GEDI) and Sentinel-2
Annual maps of forest and evergreen forest in the contiguous United States during 2015–2017 from analyses of PALSAR-2 and Landsat images
Monsoon Asia Rice Calendar (MARC): a gridded rice calendar in monsoon Asia based on Sentinel-1 and Sentinel-2 images
A 100 m gridded population dataset of China's seventh census using ensemble learning and big geospatial data
Annual time-series 1 km maps of crop area and types in the conterminous US (CropAT-US): cropping diversity changes during 1850–2021
Enhancing High-Resolution Forest Stand Mean Height Mapping in China through an Individual Tree-Based Approach with Close-Range LiDAR Data
Retrieval of dominant methane (CH4) emission sources, the first high-resolution (1–2 m) dataset of storage tanks of China in 2000–2021
A 10 m resolution land cover map of the Tibetan Plateau with detailed vegetation types
ChinaSoyArea10m: a dataset of soybean-planting areas with a spatial resolution of 10 m across China from 2017 to 2021
Physical, social, and biological attributes for improved understanding and prediction of wildfires: FPA FOD-Attributes dataset
3D-GloBFP: the first global three-dimensional building footprint dataset
Map of forest tree species for Poland based on Sentinel-2 data
Global 30-m seamless data cube (2000–2022) of land surface reflectance generated from Landsat-5,7,8,9 and MODIS Terra constellations
The ABoVE L-band and P-band airborne synthetic aperture radar surveys
Global mapping of oil palm planting year from 1990 to 2021
A 30 m annual cropland dataset of China from 1986 to 2021
Global 1 km land surface parameters for kilometer-scale Earth system modeling
ChinaRiceCalendar – seasonal crop calendars for early-, middle-, and late-season rice in China
Harmonized European Union subnational crop statistics can reveal climate impacts and crop cultivation shifts
GLC_FCS30D: the first global 30 m land-cover dynamics monitoring product with a fine classification system for the period from 1985 to 2022 generated using dense-time-series Landsat imagery and the continuous change-detection method
A global estimate of monthly vegetation and soil fractions from spatiotemporally adaptive spectral mixture analysis during 2001–2022
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Mapping Rangeland Health Indicators in East Africa from 2000 to 2022
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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.
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.
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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.
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.
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-274, https://doi.org/10.5194/essd-2024-274, 2024
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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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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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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.
Yangzi Che, Xuecao Li, Xiaoping Liu, Yuhao Wang, Weilin Liao, Xianwei Zheng, Xucai Zhang, Xiaocong Xu, Qian Shi, Jiajun Zhu, Hua Yuan, and Yongjiu Dai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-217, https://doi.org/10.5194/essd-2024-217, 2024
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Given the limited coverage or spatial resolution of existing datasets, we develop the first global building height map (3D-GloBFP) at the building footprint scale using Earth observation datasets and advanced machine learning techniques. Our map reveals the complex 3-D morphology of the world's building heights at a finer scale and provides reliable results (i.e., R2: 0.66–0.96, RMSEs: 1.9 m–14.6 m) over global regions 3D-GloBFP has great potential to support both macro- and micro-urban analysis
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.
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 Discuss., https://doi.org/10.5194/essd-2024-178, https://doi.org/10.5194/essd-2024-178, 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), and daily Seamless Data Cube (SDC) of surface reflectance based on Landsat 5,7,8,9 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.
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.
Adrià Descals, David L. A. Gaveau, Serge Wich, Zoltan Szantoi, and Erik Meijaard
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-157, https://doi.org/10.5194/essd-2024-157, 2024
Revised manuscript accepted for ESSD
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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.
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).
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 Discuss., https://doi.org/10.5194/essd-2023-494, https://doi.org/10.5194/essd-2023-494, 2024
Revised manuscript accepted for ESSD
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LUCAS 2022 Copernicus is a large an systematic in-situ field survey of 137,966 polygons over the EU in 2022. The data holds 82 land cover classes and 40 land use classes.
Yuanwei Qin, Xiangming Xiao, Hao Tang, Ralph Dubayah, Russell Doughty, Diyou Liu, Fang Liu, Yosio Shimabukuro, Egidio Arai, Xinxin Wang, and Berrien Moore III
Earth Syst. Sci. Data, 16, 321–336, https://doi.org/10.5194/essd-16-321-2024, https://doi.org/10.5194/essd-16-321-2024, 2024
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Forest definition has two major biophysical parameters, i.e., canopy height and canopy coverage. However, few studies have assessed forest cover maps in terms of these two parameters at a large scale. Here, we assessed the annual forest cover maps in the Brazilian Amazon using 1.1 million footprints of canopy height and canopy coverage. Over 93 % of our forest cover maps are consistent with the FAO forest definition, showing the high accuracy of these forest cover maps in the Brazilian Amazon.
Xiangan Liang, Qiang Liu, Jie Wang, Shuang Chen, and Peng Gong
Earth Syst. Sci. Data, 16, 177–200, https://doi.org/10.5194/essd-16-177-2024, https://doi.org/10.5194/essd-16-177-2024, 2024
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The state-of-the-art MODIS surface reflectance products suffer from temporal and spatial gaps, which make it difficult to characterize the continuous variation of the terrestrial surface. We proposed a framework for generating the first global 500 m daily seamless data cubes (SDC500), covering the period from 2000 to 2022. We believe that the SDC500 dataset can interest other researchers who study land cover mapping, quantitative remote sensing, and ecological science.
Rémy Ballot, Nicolas Guilpart, and Marie-Hélène Jeuffroy
Earth Syst. Sci. Data, 15, 5651–5666, https://doi.org/10.5194/essd-15-5651-2023, https://doi.org/10.5194/essd-15-5651-2023, 2023
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Assessing the benefits of crop diversification – a key element of agroecological transition – on a large scale requires a description of current crop sequences as a baseline, which is lacking at the scale of Europe. To fill this gap, we used a dataset that provides temporally and spatially incomplete land cover information to create a map of dominant crop sequence types for Europe over 2012–2018. This map is a useful baseline for assessing the benefits of future crop diversification.
Kristof Van Tricht, Jeroen Degerickx, Sven Gilliams, Daniele Zanaga, Marjorie Battude, Alex Grosu, Joost Brombacher, Myroslava Lesiv, Juan Carlos Laso Bayas, Santosh Karanam, Steffen Fritz, Inbal Becker-Reshef, Belén Franch, Bertran Mollà-Bononad, Hendrik Boogaard, Arun Kumar Pratihast, Benjamin Koetz, and Zoltan Szantoi
Earth Syst. Sci. Data, 15, 5491–5515, https://doi.org/10.5194/essd-15-5491-2023, https://doi.org/10.5194/essd-15-5491-2023, 2023
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WorldCereal is a global mapping system that addresses food security challenges. It provides seasonal updates on crop areas and irrigation practices, enabling informed decision-making for sustainable agriculture. Our global products offer insights into temporary crop extent, seasonal crop type maps, and seasonal irrigation patterns. WorldCereal is an open-source tool that utilizes space-based technologies, revolutionizing global agricultural mapping.
Jia Zhou, Jin Niu, Ning Wu, and Tao Lu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-403, https://doi.org/10.5194/essd-2023-403, 2023
Revised manuscript accepted for ESSD
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The study provided an annual 100-meter 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.
Gerardo E. Soto, Steven Wilcox, Patrick E. Clark, Francesco P. Fava, Nathan M. Jensen, Njoki Kahiu, Chuan Liao, Benjamin Porter, Ying Sun, and Christopher Barrett
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-217, https://doi.org/10.5194/essd-2023-217, 2023
Revised manuscript accepted for ESSD
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Using machine learning classification and linear unmixing, this paper produced Landsat-based time series of land cover classes and vegetation fractional cover of photosynthetic vegetation, non-photosynthetic vegetation, and bare ground. This dataset represents a first multi-decadal high-resolution dataset specifically designed for mapping and monitoring rangelands health in East Africa including Kenya, Ethiopia, and Somalia, which are dominated by arid and semi-arid extensive rangeland systems.
Francesco N. Tubiello, Giulia Conchedda, Leon Casse, Pengyu Hao, Giorgia De Santis, and Zhongxin Chen
Earth Syst. Sci. Data, 15, 4997–5015, https://doi.org/10.5194/essd-15-4997-2023, https://doi.org/10.5194/essd-15-4997-2023, 2023
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We describe a new dataset of cropland area circa the year 2020, with global coverage and country detail. Data are generated from geospatial information on the agreement characteristics of six high-resolution cropland maps. By helping to highlight features of cropland characteristics and underlying causes for agreement across land cover products, the dataset can be used as a tool to help guide future mapping efforts towards improved agricultural monitoring.
Martin Schwartz, Philippe Ciais, Aurélien De Truchis, Jérôme Chave, Catherine Ottlé, Cedric Vega, Jean-Pierre Wigneron, Manuel Nicolas, Sami Jouaber, Siyu Liu, Martin Brandt, and Ibrahim Fayad
Earth Syst. Sci. Data, 15, 4927–4945, https://doi.org/10.5194/essd-15-4927-2023, https://doi.org/10.5194/essd-15-4927-2023, 2023
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As forests play a key role in climate-related issues, their accurate monitoring is critical to reduce global carbon emissions effectively. Based on open-access remote-sensing sensors, and artificial intelligence methods, we created high-resolution tree height, wood volume, and biomass maps of metropolitan France that outperform previous products. This study, based on freely available data, provides essential information to support climate-efficient forest management policies at a low cost.
Zhuohong Li, Wei He, Mofan Cheng, Jingxin Hu, Guangyi Yang, and Hongyan Zhang
Earth Syst. Sci. Data, 15, 4749–4780, https://doi.org/10.5194/essd-15-4749-2023, https://doi.org/10.5194/essd-15-4749-2023, 2023
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Nowadays, a very-high-resolution land-cover (LC) map with national coverage is still unavailable in China, hindering efficient resource allocation. To fill this gap, the first 1 m resolution LC map of China, SinoLC-1, was built. The results showed that SinoLC-1 had an overall accuracy of 73.61 % and conformed to the official survey reports. Comparison with other datasets suggests that SinoLC-1 can be a better support for downstream applications and provide more accurate LC information to users.
Johannes H. Uhl, Dominic Royé, Keith Burghardt, José A. Aldrey Vázquez, Manuel Borobio Sanchiz, and Stefan Leyk
Earth Syst. Sci. Data, 15, 4713–4747, https://doi.org/10.5194/essd-15-4713-2023, https://doi.org/10.5194/essd-15-4713-2023, 2023
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Historical, fine-grained geospatial datasets on built-up areas are rarely available, constraining studies of urbanization, settlement evolution, or the dynamics of human–environment interactions to recent decades. In order to provide such historical data, we used publicly available cadastral building data for Spain and created a series of gridded surfaces, measuring age, physical, and land-use-related features of the built environment in Spain and the evolution of settlements from 1900 to 2020.
Christopher G. Marston, Aneurin W. O'Neil, R. Daniel Morton, Claire M. Wood, and Clare S. Rowland
Earth Syst. Sci. Data, 15, 4631–4649, https://doi.org/10.5194/essd-15-4631-2023, https://doi.org/10.5194/essd-15-4631-2023, 2023
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The UK Land Cover Map 2021 (LCM2021) is a UK-wide land cover data set, with 21- and 10-class versions. It is intended to support a broad range of UK environmental research, including ecological and hydrological research. LCM2021 was produced by classifying Sentinel-2 satellite imagery. LCM2021 is distributed as a suite of products to facilitate easy use for a range of applications. To support research at different spatial scales it includes 10 m, 25 m and 1 km resolution products.
Yu Zhao, Shaoyu Han, Jie Zheng, Hanyu Xue, Zhenhai Li, Yang Meng, Xuguang Li, Xiaodong Yang, Zhenhong Li, Shuhong Cai, and Guijun Yang
Earth Syst. Sci. Data, 15, 4047–4063, https://doi.org/10.5194/essd-15-4047-2023, https://doi.org/10.5194/essd-15-4047-2023, 2023
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In the present study, we generated a 30 m Chinese winter wheat yield dataset from 2016 to 2021, called ChinaWheatYield30m. The dataset has high spatial resolution and great accuracy. It is the highest-resolution yield dataset known. Such a dataset will provide basic knowledge of detailed wheat yield distribution, which can be applied for many purposes including crop production modeling or regional climate evaluation.
Feng Yang and Zhenzhong Zeng
Earth Syst. Sci. Data, 15, 4011–4021, https://doi.org/10.5194/essd-15-4011-2023, https://doi.org/10.5194/essd-15-4011-2023, 2023
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We generated a 4.77 m resolution annual tree cover map product for Southeast Asia (SEA) for 2016–2021 using Planet-NICFI and Sentinel-1 imagery. Maps were created with good accuracy and high consistency during 2016–2021. The baseline maps at 4.77 m can be converted to forest cover maps for SEA at various resolutions to meet different users’ needs. Our products can help resolve rounding errors in forest cover mapping by counting isolated trees and monitoring long, narrow forest cover removal.
Adrià Descals, Serge Wich, Zoltan Szantoi, Matthew J. Struebig, Rona Dennis, Zoe Hatton, Thina Ariffin, Nabillah Unus, David L. A. Gaveau, and Erik Meijaard
Earth Syst. Sci. Data, 15, 3991–4010, https://doi.org/10.5194/essd-15-3991-2023, https://doi.org/10.5194/essd-15-3991-2023, 2023
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The spatial extent of coconut palm is understudied despite its increasing demand and associated impacts. We present the first global coconut palm layer at 20 m resolution. The layer was produced using deep learning and remotely sensed data. The global coconut area estimate is 12.31 Mha for dense coconut palm, but the estimate is 3 times larger when sparse coconut palm is considered. This means that coconut production can likely increase on the lands currently allocated to coconut palm.
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, 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.
Wanru He, Xuecao Li, Yuyu Zhou, Zitong Shi, Guojiang Yu, Tengyun Hu, Yixuan Wang, Jianxi Huang, Tiecheng Bai, Zhongchang Sun, Xiaoping Liu, and Peng Gong
Earth Syst. Sci. Data, 15, 3623–3639, https://doi.org/10.5194/essd-15-3623-2023, https://doi.org/10.5194/essd-15-3623-2023, 2023
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Most existing global urban products with future projections were developed in urban and non-urban categories, which ignores the gradual change of urban development at the local scale. Using annual global urban extent data from 1985 to 2015, we forecasted global urban fractional changes under eight scenarios throughout 2100. The developed dataset can provide spatially explicit information on urban fractions at 1 km resolution, which helps support various urban studies (e.g., urban heat island).
Zeping Liu, Hong Tang, Lin Feng, and Siqing Lyu
Earth Syst. Sci. Data, 15, 3547–3572, https://doi.org/10.5194/essd-15-3547-2023, https://doi.org/10.5194/essd-15-3547-2023, 2023
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Large-scale maps of building rooftop area (BRA) are crucial for addressing policy decisions and sustainable development. In this paper, we propose a deep-learning method for high-resolution BRA mapping (2.5 m) from Sentinel-2 imagery (10 m). The resulting China building rooftop area dataset (CBRA) is the first multi-annual (2016–2021) and high-resolution (2.5 m) BRA dataset in China. Cross-comparisons show that the CBRA achieves the best performance in capturing the spatiotemporal information.
Ruoque Shen, Baihong Pan, Qiongyan Peng, Jie Dong, Xuebing Chen, Xi Zhang, Tao Ye, Jianxi Huang, and Wenping Yuan
Earth Syst. Sci. Data, 15, 3203–3222, https://doi.org/10.5194/essd-15-3203-2023, https://doi.org/10.5194/essd-15-3203-2023, 2023
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Paddy rice is the second-largest grain crop in China and plays an important role in ensuring global food security. This study developed a new rice-mapping method and produced distribution maps of single-season rice in 21 provincial administrative regions of China from 2017 to 2022 at a 10 or 20 m resolution. The accuracy was examined using 108 195 survey samples and county-level statistical data, and we found that the distribution maps have good accuracy.
Charles R. Lane, Ellen D'Amico, Jay R. Christensen, Heather E. Golden, Qiusheng Wu, and Adnan Rajib
Earth Syst. Sci. Data, 15, 2927–2955, https://doi.org/10.5194/essd-15-2927-2023, https://doi.org/10.5194/essd-15-2927-2023, 2023
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Non-floodplain wetlands (NFWs) – wetlands located outside floodplains – confer watershed-scale resilience to hydrological, biogeochemical, and biotic disturbances. Although they are frequently unmapped, we identified ~ 33 million NFWs covering > 16 × 10 km2 across the globe. NFWs constitute the majority of the world's wetlands (53 %). Despite their small size (median 0.039 km2), these imperiled systems have an outsized impact on watershed functions and sustainability and require protection.
Bingjie Li, Xiaocong Xu, Xiaoping Liu, Qian Shi, Haoming Zhuang, Yaotong Cai, and Da He
Earth Syst. Sci. Data, 15, 2347–2373, https://doi.org/10.5194/essd-15-2347-2023, https://doi.org/10.5194/essd-15-2347-2023, 2023
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A global land cover map with fine spatial resolution is important for climate and environmental studies, food security, or biodiversity conservation. In this study, we developed an improved global land cover map in 2015 with 30 m resolution (GLC-2015) by fusing the existing land cover products based on the Dempster–Shafer theory of evidence on the Google Earth Engine platform. The GLC-2015 performed well, with an OA of 79.5 % (83.6 %) assessed with the global point-based (patch-based) samples.
Richard A. Houghton and Andrea Castanho
Earth Syst. Sci. Data, 15, 2025–2054, https://doi.org/10.5194/essd-15-2025-2023, https://doi.org/10.5194/essd-15-2025-2023, 2023
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We update a previous analysis of carbon emissions (annual and national) from land use, land-use change, and forestry from 1850 to 2020. We use data from the latest (2020) Global Forest Resources Assessment, incorporate shifting cultivation, and include improvements to the bookkeeping model and recent estimates of emissions from peatlands. Net global emissions declined steadily over the decade from 2011 to 2020 (mean of 0.96 Pg C yr−1), falling below 1.0 Pg C yr−1 for the first time in 30 years.
Charles H. Simpson, Oscar Brousse, Nahid Mohajeri, Michael Davies, and Clare Heaviside
Earth Syst. Sci. Data, 15, 1521–1541, https://doi.org/10.5194/essd-15-1521-2023, https://doi.org/10.5194/essd-15-1521-2023, 2023
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Adding plants to roofs of buildings can reduce indoor and outdoor temperatures and 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.
Chunling Sun, Hong Zhang, Lu Xu, Ji Ge, Jingling Jiang, Lijun Zuo, and Chao Wang
Earth Syst. Sci. Data, 15, 1501–1520, https://doi.org/10.5194/essd-15-1501-2023, https://doi.org/10.5194/essd-15-1501-2023, 2023
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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 data for mainland Southeast Asia is proposed. A combination of spatiotemporal features with strong generalization is selected and input into the U-Net model to obtain a 20 m resolution rice area map of mainland Southeast Asia in 2019. The accuracy of the proposed method is 92.20 %. The rice area map is concordant with statistics and other rice area maps.
Kandice L. Harper, Céline 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, 15, 1465–1499, https://doi.org/10.5194/essd-15-1465-2023, https://doi.org/10.5194/essd-15-1465-2023, 2023
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We built a spatially explicit annual plant-functional-type (PFT) dataset for 1992–2020 exhibiting intra-class spatial variability in PFT fractional cover at 300 m. For each year, 14 maps of 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. Model simulations indicate significant differences in simulated carbon, water, and energy fluxes in some regions using this new set.
Yating Ru, Brian Blankespoor, Ulrike Wood-Sichra, Timothy S. Thomas, Liangzhi You, and Erwin Kalvelagen
Earth Syst. Sci. Data, 15, 1357–1387, https://doi.org/10.5194/essd-15-1357-2023, https://doi.org/10.5194/essd-15-1357-2023, 2023
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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. As an illustration, the paper estimates that the exposure of areas with extreme drought to agricultural GDP is USD 432 billion, where nearly 1.2 billion people live.
Cited articles
Arneth, A., Sitch, S., Pongratz, J., Stocker, B. D., Ciais, P., Poulter, B., Bayer, A. D., Bondeau, A., Calle, L., Chini, L. P., Gasser, T., Fader, M., Friedlingstein, P., Kato, E., Li, W., Lindeskog, M., Nabel, J. E. M. S., Pugh, T. A. M., Robertson, E., Viovy, N., Yue, C., and Zaehle, S.: Historical carbon dioxide emissions caused by land-use changes are possibly larger than assumed, Nat. Geosci., 10, 79–84, https://doi.org/10.1038/ngeo2882, 2017.
Bai, S., Shuwen, Z., and Yangzhen, Z.: Digital rebuilding of lucc spatial-temporal distribution of the last 100 years: taking dorbod mongolian autonomous county in daqing city as an example, Acta Geographica Sinica, 62, 427–436, 2007.
Cao, B., Yu, L., Li, X., Chen, M., Li, X., Hao, P., and Gong, P.: A 1 km global cropland dataset from 10 000 BCE to 2100 CE, Earth Syst. Sci. Data, 13, 5403–5421, https://doi.org/10.5194/essd-13-5403-2021, 2021.
Cao, S. and Ge, J.: The History of Chinese Population, Vol. 4, Fudan University Press, Shanghai, China, ISBN: 7-309-04302-2, 2005 (in Chinese).
Cao, S. and Ge, J.: The History of Chinese Migration, Vol. 5, Fudan University Press, Shanghai, China, ISBN: 978-7-309-15225-8, 2022 (in Chinese).
Chen, J., Chen, J., Liao, A., Cao, X., Chen, L., Chen, X., He, C., Han, G., Peng, S., Lu, M., Zhang, W., Tong, X., and Mills, J.: Global land cover mapping at 30 m resolution: a pok-based operational approach, ISPRS J. Photogramm., 103, 7–27, https://doi.org/10.1016/j.isprsjprs.2014.09.002, 2015.
Committee Of Integrative Survey Of Natural Resources and Committee Of National Planning Of Chinese Academy Of Sciences: Data Compilation of National Land Resources, Vol. 1, Committee of National Planning of Chinese Academy of Sciences, https://www.las.ac.cn/front/book/detail?id=f232342377990406593ffef3e4d3ba6a (last access: 22 October 2024), 1989 (in Chinese).
Committee Of Integrative Survey Of Natural Resources and Committee Of National Planning Of Chinese Academy Of Sciences: Data Compilation of National Land Resources, Vol. 3, Committee of National Planning of Chinese Academy of Sciences, Beijing, China, https://www.las.ac.cn/front/book/detail?id=61ef76fe786355cc289697bdea084964 (last access: 22 October 2024), 1990 (in Chinese).
Cong, P.: Garrison Reclamation in Liaodong in the Ming Dynasty, Journal of Chinese Historical Studies, 93–107, 1985 (in Chinese).
Cong, P.: Agriculture in Liaoyang Province in the Yuan Dynasty, Northern Cultural Relics, 1, 78–88, https://doi.org/10.16422/j.cnki.1001-0483.1993.01.019, 1993a (in Chinese).
Cong, P.: Khitan, Goryeo, Semu and Mongolian in Liaoyang Province in the Yuan Dynasty, Collected Papers of History Studies, 1, 7–14, 1993b (in Chinese).
Cropland Research Group: Quantitative Economic Analysis of Cropland Decline in China, Economic Science Press, Beijing, China, ISBN: 7-5058-0489-8, 1992 (in Chinese).
East Branch Railway Administration Of Russia and South Manchuria Railways Co.: North manchuria and east branch railway, Vol. 1, South Manchuria Railways Co., Dalian, China, https://ndlsearch.ndl.go.jp/books/R100000002-I000000602624 (last access: 22 October 2024), 1923a (in Japanese).
East Branch Railway Administration Of Russia and South Manchuria Railways Co.: North manchuria and east branch railway, Vol. 2, South Manchuria Railways Co., Dalian, China, https://ndlsearch.ndl.go.jp/books/R100000002-I000000600370 (last access: 22 October 2024), 1923b (in Japanese).
Ellis, E. C., Gauthier, N., Klein Goldewijk, K., Bird, R. B., Boivin, N., Díaz, S., Fuller, D. Q., Gill, J. L., Kaplan, J. O., Kingston, N., Locke, H., Mcmichael, C. N. H., Ranco, D., Rick, T. C., Rebecca Shaw, M., Stephens, L., Svenning, J. C., and Watson, J. E. M.: People have shaped most of terrestrial nature for at least 12,000 years, P. Natl. Acad. Sci. USA, 118, e2023483118, https://doi.org/10.1073/pnas.2023483118, 2021.
Fan, X.: Research on the Mechanism of the Layout of Ming Great Wall Military Defense System, PhD thesis, Tianjin University, 324 pp., 2015 (in Chinese).
Fang, X., Ye, Y., Ge, Q., and Zheng, J.: Land Exploitation in the Northeast China during the Qing Dynasty Inferred from the Development of Town System, Scientia Geographica Sinica, 25, 129–134, https://doi.org/10.3969/j.issn.1000-0690.2005.02.001, 2005 (in Chinese).
Fang, X., Ye, Y., and Zeng, Z.: Interaction of extreme climate event–cultivation–policy management, Science China Earth Sciences, 36, 680–688, https://doi.org/10.3969/j.issn.1674-7240.2006.07.009, 2006 (in Chinese).
Fang, X., Zhao, W., Zhang, C., Zhang, D., Wei, X., Qiu, W., and Ye, Y.: Methodology for credibility assessment of historical global lucc datasets, Sci. China Earth Sci., 63, 1013–1025, https://doi.org/10.1007/s11430-019-9555-3, 2020.
Fang, X., He, F., Wu, Z., and Zheng, J.: General characteristics of the agricultural area and fractional cropland cover changes in China for the past 2000 years, Acta Geographica Sinica, 76, 1732–1746, https://doi.org/10.11821/dlxb202107012, 2021 (in Chinese).
Foley, J. A., Defries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., Chapin, F. S., Coe, M. T., Daily, G. C., Gibbs, H. K., Helkowski, J. H., Holloway, T., Howard, E. A., Kucharik, C. J., Monfreda, C., Patz, J. A., Prentice, I. C., Ramankutty, N., and Snyder, P. K.: Global consequences of land use, Science, 309, 570–574, https://doi.org/10.1126/science.1111772, 2005.
Gaillard, M., Morrison, K. D., Madella, M., and Whitehouse, N.: Past land-use and land-cover change: the challenge of quantification at the subcontinental to global scales, Past Global Changes Magazine, 26, 3, https://doi.org/10.22498/pages.26.1.3, 2018.
Ge, J.: The History of Chinese Population, Vol. 1, Fudan University Press, Shanghai, China, ISBN: 7-309-03520-8, 2002 (in Chinese).
Godfray, H. C. J., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D., Muir, J. F., Pretty, J., Robinson, S., Thomas, S. M., and Toulmin, C.: Food security: the challenge of feeding 9 billion people, Science, 327, 812–818, https://doi.org/10.1126/science.1185383, 2010.
Gong, P., Wang, J., Le Yu, Zhao, Y., Zhao, Y., Liang, L., Niu, Z., Huang, X., Fu, H., Liu, S., Li, C., Li, X., Fu, W., Liu, C., Xu, Y., Wang, X., Cheng, Q., Hu, L., Yao, W., Zhang, H., Zhu, P., Zhao, Z., Zhang, H., Zheng, Y., Ji, L., Zhang, Y., Chen, H., Yan, A., Guo, J., Yu, L., Wang, L., Liu, X., Shi, T., Zhu, M., Chen, Y., Yang, G., Tang, P., Xu, B., Giri, C., Clinton, N., Zhu, Z., Chen, J., and Chen, J.: Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data, Int. J. Remote Sens., 34, 2607–2654, https://doi.org/10.1080/01431161.2012.748992, 2013.
Gortan, M., Testa, L., Fagiolo, G., and Lamperti, F.: A unified dataset for pre-processed climate indicators weighted by gridded economic activity, Sci. Data, 11, 533, https://doi.org/10.1038/s41597-024-03304-1, 2024.
Han, M.: Agricultural Geography of Liao and Jin Dynasties, Social Sciences Academic Press, Beijing, China, ISBN: 7-80149-186-6, 1999 (in Chinese).
Han, M.: Historical agricultural geography of China, Peking University Press, Beijing, China, ISBN: 978-7-301-19667-0, 2012 (in Chinese).
He, F., Li, M., and Li, S.: Reconstruction of Lu-level cropland areas in the Northern Song Dynasty (AD976–1078), J. Geogr. Sci., 27, 606–618, https://doi.org/10.1007/s11442-017-1395-3, 2017.
He, F., Yang, F., Zhao, C., Li, S., and Li, M.: Spatially explicit reconstruction of cropland cover for china over the past millennium, Sci. China Earth Sci., 66, 111–128, https://doi.org/10.1007/s11430-021-9988-5, 2023.
Huang, X., Ibrahim, M. M., Luo, Y., Jiang, L., Chen, J., and Hou, E.: Land Use Change Alters Soil Organic Carbon: Constrained Global Patterns and Predictors, Earth's Future, 12, e2023EF004254, https://doi.org/10.1029/2023EF004254, 2024.
Hurtt, G. C., Chini, L., Sahajpal, R., Frolking, S., Bodirsky, B. L., Calvin, K., Doelman, J. C., Fisk, J., Fujimori, S., Klein Goldewijk, K., Hasegawa, T., Havlik, P., Heinimann, A., Humpenöder, F., Jungclaus, J., Kaplan, J. O., Kennedy, J., Krisztin, T., Lawrence, D., Lawrence, P., Ma, L., Mertz, O., Pongratz, J., Popp, A., Poulter, B., Riahi, K., Shevliakova, E., Stehfest, E., Thornton, P., Tubiello, F. N., van Vuuren, D. P., and Zhang, X.: Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6, Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020, 2020.
Inner Mongolia Provincial Bureau Of Statistics: Agricultural and animal husbandry production statistics, Inner Mongolia Provincial Bureau of Statistics, Hohhot, China, 1983 (in Chinese).
Ito, A. and Hajima, T.: Biogeophysical and biogeochemical impacts of land-use change simulated by miroc-es2l, Prog. Earth Planet. Sci., 7, 1–15, https://doi.org/10.1186/s40645-020-00372-w, 2020.
Jia, D., Li, Y., and Fang, X.: Complexity of factors influencing the spatiotemporal distribution of archaeological settlements in northeast China over the past millennium, Quaternary Res., 89, 413–424, https://doi.org/10.1017/qua.2017.112, 2018.
Jia, R., Fang, X., and Ye, Y.: Gridded reconstruction of cropland cover changes in northeast china from ad 1000 to 1200, Reg. Environ. Change, 23, 128, https://doi.org/10.1007/s10113-023-02118-y, 2023.
Jia, R., Fang, X., Yang, Y., Yokozawa, M., and Ye, Yu.: A 28 time-points cropland area change dataset in Northeast China from 1000 to 2020, figshare [data set], https://doi.org/10.6084/m9.figshare.25450468.v2, 2024.
Jin, Q. and Mikami, T.: Research on Jurchen in Jin Dynasty, Heilongjiang People's Publishing House, Harbin, China, UBSN: 11093·111, 1984 (in Chinese).
Jin, X., Cao, X., Du, X., Yang, X., Bai, Q., and Zhou, Y.: Farmland dataset reconstruction and farmland change analysis in China during 1661–1985, J. Geogr. Sci., 25, 1058–1074, 2015.
Kalnay, E. and Cai, M.: Impact of urbanization and land-use change on climate, Nature, 423, 528–531, https://doi.org/10.1038/nature01675, 2003.
Kaplan, J. O., Krumhardt, K. M., Ellis, E. C., Ruddiman, W. F., Lemmen, C., and Klein Goldewijk, K.: Holocene carbon emissions as a result of anthropogenic land cover change, The Holocene, 21, 775–791, https://doi.org/10.1177/0959683610386983, 2011.
Karra, K., Kontgis, C., Statman-Weil, Z., Mazzariello, J. C., Mathis, M., and Brumby, S. P.: Global land use/land cover with Sentinel 2 and deep learning, in: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 11–16 July 2021, IEEE, 4704–4707, https://doi.org/10.1109/IGARSS47720.2021.9553499, 2021.
Klein Goldewijk, K., Beusen, A., Doelman, J., and Stehfest, E.: Anthropogenic land use estimates for the Holocene – HYDE 3.2, Earth Syst. Sci. Data, 9, 927–953, https://doi.org/10.5194/essd-9-927-2017, 2017.
Kong, J. and Feng, Y.: Historical Geography of Northeast China, Heilongjiang People's Publishing House, Harbin, China, ISBN: 9787207012036, 1989 (in Chinese).
Li, M.: Reconstruction of cropland change data for eastern Asia and its spatial-temporal characteristics analysis in the last millennium, PhD thesis, University of Chinese Academy of Sciences, China, 176 pp., 2019 (in Chinese).
Li, M., He, F., Li, S., and Yang, F.: Reconstruction of the cropland cover changes in eastern china between the 10th century and 13th century using historical documents, Sci. Rep., 8, 13552, https://doi.org/10.1038/s41598-018-31807-6, 2018.
Li, S., He, F., and Zhang, X.: Spatially explicit reconstruction of cropland cover in china from 1661 to 1996, Reg. Environ. Change, 16, 417–428, https://doi.org/10.1007/s10113-014-0751-4, 2016.
Li, Y.: Land Resources of China, China Land Press, Beijing, China, ISBN: 7-80097-371-9, 2000 (in Chinese).
Liu, J., Liu, B., Liu, H., and Zhang, F.: Long-term cultivation drives soil carbon, nitrogen, and bacterial community changes in the black soil region of northeastern China, Land Degrad. Dev., 35, 428–441, https://doi.org/10.1002/ldr.4925, 2024.
Liu, P.: A Study of registered residence in Jin Dynasty, Study of Chinese History, 2, 86–96, 1994a (in Chinese).
Liu, P.: A Study on the population status of Mengan Mouke in Jin Dynasty, Ethno-National Studies, 2, 81–89, 1994b (in Chinese).
Liu, Z., Han, G., and Liu, H.: Quan Liao Zhi (edited in 1566), Science Press, Beijing, China, ISBN: 978-7-03-049928-8, 2016 (in Chinese).
National Bureau Of Statistics: The Summary of Rural Social Economic Statistics on County Level in China, Chinese Statistical Press, Beijing, China, ISBN: 7-5037-0198-6, 1989 (in Chinese).
National Bureau Of Statistics: China Statistical Yearbook, China Statistics Press, Beijing, China, ISBN: 978-7-5230-0190-5, 2023 (in Chinese).
Office Of The Governor-General Of Kwantung: Economic Statistics of Manchuria and Mongolia, Office of the Governor-General of Kwantung, Dalian, China, https://ndlsearch.ndl.go.jp/books/R100000136-I1130000796084786944 (last access: 22 October 2024), 1918 (in Japanese).
Pongratz, J., Reick, C., Raddatz, T., and Claussen, M.: A reconstruction of global agricultural areas and land cover for the last millennium, Global Biogeochem. Cy., 22, GB3018, https://doi.org/10.1029/2007GB003153, 2008.
Poschlod, P., Bakker, J. P., and Kahmen, S.: Changing land use and its impact on biodiversity, Basic Appl. Ecol., 6, 93–98, https://doi.org/10.1016/j.baae.2004.12.001, 2005.
Potapov, P., Turubanova, S., Hansen, M. C., Tyukavina, A., Zalles, V., Khan, A., Song, X. P., Pickens, A., Shen, Q., and Cortez, J.: Global maps of cropland extent and change show accelerated cropland expansion in the twenty-first century, Nature Food, 3, 19–28, https://doi.org/10.1038/s43016-021-00429-z, 2022.
Ramankutty, N. and Foley, J. A.: Estimating historical changes in global land cover: croplands from 1700 to 1992, Global Biogeochem. Cy., 13, 997–1027, https://doi.org/10.1029/1999GB900046, 1999.
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000, Global Biogeochem. Cy., 22, GB1003, https://doi.org/10.1029/2007GB002952, 2008.
Roberts, N.: How humans changed the face of Earth, Science, 365, 865–866, https://doi.org/10.1126/science.aay4627, 2019.
Sáez-Sandino, T., Maestre, F. T., Berdugo, M., Gallardo, A., Plaza, C., Garcia-Palacios, P., Guirado, E., Zhou, G., Mueller, C. W., Tedersoo, L., Crowther, T. W., and Delgado-Baquerizo, M.: Increasing numbers of global change stressors reduce soil carbon worldwide, Nat. Clim. Change, 14, 740–745, https://doi.org/10.1038/s41558-024-02019-w, 2024.
Sebastiaan, L., Mathilde, J., Paul, C. S., Stephan, E., Julia, P., Eric, C., Galina, C., Axel, D., Karlheinz, E., Morgan, F., Bert, G., Thomas, G., Richard, A. H., Katja, K., Alexander, K., Thomas, K., Tobias, K., Tuomas, L., Annalea, L., Denis, L., Matthew, J. M., Patrick, M., Eddy, J. M., Kim, N., Kim, N., Juliane, O., Kim, P., Casimiro, A. P., Serge, R., Corinna, R., James, R., Andrew, E. S., Andrej, V., Martin, W., and Dolman, A. J.: Land management and land-cover change have impacts of similar magnitude on surface temperature, Nat. Clim. Change, 4, 389–393, https://doi.org/10.1038/nclimate2196, 2014.
Shi, F.: History Draft of Chinese Population Migration, Heilongjiang People's Publishing House, Harbin, China, ISBN: 7-207-01409-0, 1990 (in Chinese).
Shi, Z.: An Estimate of Agricultural Economic Indicators in the Qing Dynasty, Researches in Chinese Economic History, 5, 5–30, 2015 (in Chinese).
Shukla, P. R., Skea, J., Calvo Buendia, E., Masson-Delmotte, V., Pörtner, H. O., Roberts, D. C., Zhai, P., Slade, R., Connors, S., Van Diemen, R., Ferrat, M., Haughey, E., Luz, S., Neogi, S., Pathak, M., Petzold, J., Portugal Pereira, J., Vyas, P., Huntley, E., Kissick, K., Belkacemi, M., and Malley, J.: IPCC: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, Intergovernmental Panel on Climate Change (IPCC), https://www.ipcc.ch/srccl/ (last access: 22 October 2024), 2019.
Song, L.: Dynastic History of Yuan Dynasty, Zhonghua Publishing House, Beijing, China, UBSN: 11018.638, 1976 (in Chinese).
South Manchuria Railways Co.: Weights and Measures in Northeast China, South Manchuria Railways Co., Dalian, China, https://ndlsearch.ndl.go.jp/books/R100000002-I000000780185 (last access: 22 October 2024), 1927 (in Japanese).
Tan, Q.: The Historical Atlas of China, Vol. 6: Song , Liao and Jin Dynasties, SinoMaps Press, Beijing, China, ISBN: 7-5031-0385-X/K⋅195, 1982a (in Chinese).
Tan, Q.: The Historical Atlas of China, Vol. 7: Yuan and Ming Dynasties, SinoMaps Press, Beijing, China, ISBN: 7-5031-1843-1/K⋅646, 1982b (in Chinese).
Thenkabail, P. S., Teluguntla, P. G., Xiong, J., Oliphant, A., Congalton, R. G., Ozdogan, M., Gumma, M. K., Tilton, J. C., Giri, C., Milesi, C., Phalke, A., Massey, R., Yadav, K., Sankey, T., Zhong, Y., Aneece, I., and Foley, D.: Global cropland-extent product at 30-m resolution (GCEP30) derived from landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on Google Earth Engine Cloud, U.S. Geological Survey Professional Paper 1868, 63 pp., https://doi.org/10.3133/pp1868, 2021.
Tian, Y.: The land use and land cover change in Re-Cha-Sui area in recent 300 years, Master thesis, Graduate School of Chinese Academy of Sciences, 166 pp., 2005 (in Chinese).
Toqto'A: Dynastic History of Liao Dynasty, Zhonghua Publishing House, Beijing, China, ISBN: 7-101-00324-9, 1974 (in Chinese).
Toqto'A: Dynastic History of Jin Dynasty, Zhonghua Publishing House, Beijing, China, ISBN: 7-101-00325-7, 1975 (in Chinese).
Wang, S., Fang, C., Chen, X., Liang, J., Liu, K., Feng, K., Hubacek, K., and Wang, J.: China's ecological footprint via biomass import and consumption is increasing, Commun. Earth Environ., 5, 244, https://doi.org/10.1038/s43247-024-01399-3, 2024.
Wang, Y.: Garrison Reclamation of the Ming Dynasty, Zhonghua Publishing House, Beijing, China, ISBN: 978-7-101-06858-0, 2009 (in Chinese).
Wang, Y., Yu, H., Wang, S., Li, H., and Wang, Y.: Unveiling trends and environmental impacts of global black soil crop production: a comprehensive assessment, Resour. Conserv. Recy., 16, 208, 107717, https://doi.org/10.1016/j.resconrec.2024.107717, 2024.
Wei, X., Ye, Y., Zhang, Q., and Fang, X.: Reconstruction of cropland change over the past 300 years in the Jing-Jin-Ji area, China, Reg. Environ. Change, 2097-2109, 2016.
Wei, X., Widgren, M., Li, B., Ye, Y., Fang, X., Zhang, C., and Chen, T.: Dataset of 1 km cropland cover from 1690 to 1999 in Scandinavia, Earth Syst. Sci. Data, 13, 3035–3056, https://doi.org/10.5194/essd-13-3035-2021, 2021.
Winkler, K., Fuchs, R., Rounsevell, M., and Herold, M.: Global land use changes are four times greater than previously estimated, Nat. Commun., 12, 2501, https://doi.org/10.1038/s41467-021-22702-2, 2021.
Wu, S. and Ge, J.: The History of Chinese Population, Vol. 3, Fudan University Press, Shanghai, China, ISBN: 7-309-04302-2, 2005 (in Chinese).
Wu, S. and Ge, J.: The History of Chinese Migration, Volume 4, Fudan University Press, Shanghai, China, ISBN: 978-7-309-15224-1, 2022 (in Chinese).
Wu, Z.: Development of Gridded Allocation Method for Historical Cropland Based on Settlement Information and Its Application, PhD thesis, Beijing Normal University, China, 184 pp., 2021 (in Chinese).
Wu, Z., Fang, X., Jia, D., and Zhao, W.: Reconstruction of cropland cover using historical literature and settlement relics in farming areas of Shangjing Dao during the Liao Dynasty, China, around 1100 AD, The Holocene, 30, 1516–1527, https://doi.org/10.1177/0959683620941293, 2020.
Wu, Z., Fang, X., and Ye, Y.: A settlement density based allocation method for historical cropland cover: a case study of Jilin province, China, Land, 11, 1374, https://doi.org/10.3390/land11081374, 2022.
Xiong, Z.: Summary of county governance in Northeast China, Lida Publishing House, ISBN: 9787537152136, 1933 (in Chinese).
Xu, M., Zhang, Z., Yue, C., Zhao, J., Zhang, P., Wang, M., Wang, J., Zhao, H., Liu, J., Tang, X., and He, J.: Contributions of China's terrestrial ecosystem carbon uptakes to offsetting CO2 emissions under different scenarios over 2001–2060, Global Planet. Change, 238, 104485, https://doi.org/10.1016/j.gloplacha.2024.104485, 2024.
Xu, X., Li, B., Liu, X., Li, X., and Shi, Q.: Mapping annual global land cover changes at a 30 m resolution from 2000 to 2015, National Remote Sensing Bulletin, 25, 1896–1916, https://doi.org/10.11834/jrs.20211261, 2021 (in Chinese).
Xuan, X., Zhang, F., Deng, X., and Bai, Y.: Measurement and spatio-temporal transfer of greenhouse gas emissions from agricultural sources in China: a food trade perspective, Resour. Conserv. Recy., 197, 107100, https://doi.org/10.1016/j.resconrec.2023.107100, 2023.
Xue, L.: Research on the Liaoyang Province and Governance over the Northeast China of the Yuan Dynasty, PhD thesis, Nankai University, 261 pp., https://doi.org/10.7666/d.J0095355, 2006 (in Chinese).
Xue, L.: Research of the Governance Over the Northeast Region in the Yuan Dynasty, Social Sciences Academic Press, Beijing, China, ISBN: 978-7-5097-3697-5, 2012 (in Chinese).
Yang, F., Dong, G., Wu, P., and He, F.: Stylized facts of past 1000-year of China's cropland changes, Land Use Policy, 144, 107258, https://doi.org/10.1016/j.landusepol.2024.107258, 2024.
Yang, J. and Huang, X.: The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019, Earth Syst. Sci. Data, 13, 3907–3925, https://doi.org/10.5194/essd-13-3907-2021, 2021.
Yang, Y., Zhang, S., Liu, Y., Xing, X., and De Sherbinin, A.: Analyzing historical land use changes using a historical land use reconstruction model: a case study in zhenlai county, northeastern china, Sci. Rep., 7, 41275, https://doi.org/10.1038/srep41275, 2017.
Ye, X., Garber, P. A., Li, M., and Zhao, X.: Climate and anthropogenic activities threaten two langur species irrespective of their range size, Divers. Distrib., 30, e13841, https://doi.org/10.1111/ddi.13841, 2024.
Ye, Y. and Fang, X.: Expansion of cropland area and formation of the eastern farming-pastoral ecotone in northern china during the twentieth century, Reg. Environ. Change, 12, 923–934, https://doi.org/10.1007/s10113-012-0306-5, 2012.
Ye, Y., Fang, X., Dai, Y., Zeng, Z., and Zhang, X.: Calibration of cropland data and reconstruction of rate of reclamation in Northeast China during the period of Republic of China, Prog. Nat. Sci., 16, 1419–1427, 2006 (in Chinese).
Ye, Y., Fang, X., Ren, Y., Zhang, X., and Chen, L.: Cropland cover change in northeast china during the past 300 years, Sci. China Earth Sci., 52, 1172–1182, https://doi.org/10.1007/s11430-009-0118-8, 2009.
Ye, Y., Wei, X., Li, F., and Fang, X.: Reconstruction of cropland cover changes in the Shandong Province over the past 300 years, Sci. Rep., 5, 13642, https://doi.org/10.1038/srep13642, 2015.
Yu, Z. and Lu, C.: Historical cropland expansion and abandonment in the continental U.S. During 1850 to 2016, Global Ecol. Biogeogr., 27, 322–333, https://doi.org/10.1111/geb.12697, 2018.
Yu, Z., Lu, C., Tian, H., and Canadell, J. G.: Largely underestimated carbon emission from land use and land cover change in the conterminous United States, Glob. Change Biol., 25, 3741–3752, 2019.
Yu, Z., Jin, X., Miao, L., and Yang, X.: A historical reconstruction of cropland in China from 1900 to 2016, Earth Syst. Sci. Data, 13, 3203–3218, https://doi.org/10.5194/essd-13-3203-2021, 2021.
Zanaga, D., Van De Kerchove, R., De Keersmaecker, W., Souverijns, N., Brockmann, C., Quast, R., Wevers, J., Grosu, A., Paccini, A., Vergnaud, S., Cartus, O., Santoro, M., Fritz, S., Georgieva, I., Lesiv, M., Carter, S., Herold, M., Li, L., Tsendbazar, N.-E., Ramoino, F., and Arino, O.: ESA WorldCover 10 m 2020 v100, Version v100, Zenodo [data set], https://doi.org/10.5281/zenodo.5571936, 2021.
Zeng, Z., Fang, X., and Ye, Y.: The Process of Land Cultivation Based on Settlement Names in Jilin Province in the Past 300 Years, Acta Geographica Sinica, 66, 985–993, 2011 (in Chinese).
Zhan, J.: Heilongjiang History of Land Reclamation in border Areas, Vol. 1, Social Sciences Academic Press, Beijing, China, ISBN: 978-7-5201-1397-7, 2017 (in Chinese).
Zhang, C., Fang, X., Ye, Y., Tang, C., Wu, Z., Zheng, X., Zhang, D., Jiang, C., Li, J., Li, Y., and Zhao, Z.: A spatially explicit reconstruction of cropland cover in china around 1850 C.E. employing new land suitability based gridded allocation algorithm, Quatern. Int., 641, 62–73, https://doi.org/10.1016/j.quaint.2022.06.001, 2022.
Zhang, L., Fang, X., Ren, G., and Suo, X.: Environmental Changes in the North China Farming Grazing Transitional Zone, Earth Science Frontiers, 4, 127–136, https://www.earthsciencefrontiers.net.cn/CN/abstract/abstract1556.shtml (last access: 22 October 2024), 1997 (in Chinese).
Zhang, L., Jiang, L., Zhang, X., Zhang, A., and Jiang, C.: Reconstruction of cropland over heilongjiang province in the late 19th century, Acta Geographica Sinica, 69, 448–458, https://doi.org/10.11821/dlxb201404002, 2014.
Zhang, T.: Dynastic History of Ming Dynasty, Zhonghua Publishing House, Beijing, China, ISBN: 7-101-00327-3, 1974 (in Chinese).
Zhang, X., Zhao, T., Xu, H., Liu, W., Wang, J., Chen, X., and Liu, L.: GLC_FCS30D: the first global 30 m land-cover dynamics monitoring product with a fine classification system for the period from 1985 to 2022 generated using dense-time-series Landsat imagery and the continuous change-detection method, Earth Syst. Sci. Data, 16, 1353–1381, https://doi.org/10.5194/essd-16-1353-2024, 2024.
Zhang, Y.: Re-estimation on China's population and cropland in modern times, Researches in Chinese Economic History, 1, 20–30, 1991 (in Chinese).
Zhao, Y., Wang, K., Zhao, B., and Wang, F.: Spatio-temporal process and pattern of the establishment of county-level administrative divisions in China in the past 2200 years, Acta Geographica Sinica, 79, 890–908, https://doi.org/10.11821/dlxb202404005, 2024.
Zhou, S.: Study of Jurchen in Liaoyang Province in the Yuan Dynasty, Shanghai Jiaotong University Press, Shanghai, China, ISBN: 978-7-313-24340-9, 2021 (in Chinese).
Zhou, R.: A General Inspection and Re-appraise on Area Under Cultivation in the Early Period of the Qing, Journal of Chinese Social and Economic History, 3, 39–49, https://doi.org/10.3969/j.issn.1000-422X.2001.03.004, 2001 (in Chinese).
Short summary
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.
We reconstructed a cropland area change dataset in Northeast China over the past millennium by...
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