Articles | Volume 15, issue 2
https://doi.org/10.5194/essd-15-1005-2023
© Author(s) 2023. 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-15-1005-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
03 Mar 2023
Data description paper |
| 03 Mar 2023
| 03 Mar 2023
Four-century history of land transformation by humans in the United States (1630–2020): annual and 1 km grid data for the HIStory of LAND changes (HISLAND-US)
Xiaoyong Li
State Key Laboratory of Urban and Regional Ecology, Research Center
for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 100085,
China
Schiller Institute for Integrated Science and Society, Department of
Earth and Environmental Sciences, Boston College, Chestnut Hill, MA 02467,
USA
International Center for Climate and Global Change Research, College
of Forestry, Wildlife and Environment, Auburn University, Auburn, AL 36849,
USA
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Hanqin Tian
CORRESPONDING AUTHOR
Schiller Institute for Integrated Science and Society, Department of
Earth and Environmental Sciences, Boston College, Chestnut Hill, MA 02467,
USA
Chaoqun Lu
Department of Ecology, Evolution, and Organismal Biology, Iowa State
University, Ames, IA 50011, USA
Shufen Pan
International Center for Climate and Global Change Research, College
of Forestry, Wildlife and Environment, Auburn University, Auburn, AL 36849,
USA
Schiller Institute for Integrated Science and Society, Department of
Earth and Environmental Sciences, Boston College, Chestnut Hill, MA 02467,
USA
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Rongting Xu, Hanqin Tian, Chaoqun Lu, Shufen Pan, Jian Chen, Jia Yang, and Bowen Zhang
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Based on a comprehensive analysis framework including 15 factors, a factorial analysis scheme was developed to quantify a relative contribution of individual factors to carbon dynamics induced by urbanization. A case study in the southern US showed that land conversion had larger impacts than other factors, causing C loss. Urban managements & the interactive effect among factors compensated for 42% of the C loss in LC. The altered disturbance regime after urbanization enhanced the urban C sink.
H. Tian, G. Chen, C. Lu, X. Xu, W. Ren, K. Banger, B. Zhang, B. Tao, S. Pan, M. Liu, and C. Zhang
Biogeosciences Discuss., https://doi.org/10.5194/bgd-10-19811-2013, https://doi.org/10.5194/bgd-10-19811-2013, 2013
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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.
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.
Ruoque Shen, Qiongyan Peng, Xiangqian Li, Xiuzhi Chen, and Wenping Yuan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-584, https://doi.org/10.5194/essd-2024-584, 2024
Revised manuscript accepted for ESSD
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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 using to address the challenges of cloud contamination and missing data in optical remote sensing observations. The resulting dataset, CCD-Rice (China Crop Dataset-Rice), achieved high accuracy and showed strong correlation with statistical data.
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.
Weilin Liao, Yanman Li, Xiaoping Liu, Yuhao Wang, Yangzi Che, Ledi Shao, Guangzhao Chen, Hua Yuan, Ning Zhang, and Fei Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-408, https://doi.org/10.5194/essd-2024-408, 2024
Revised manuscript accepted for ESSD
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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.
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.
Yifan Cheng, Lei Zhao, Tirthankar Chakraborty, Keith Oleson, Matthias Demuzere, Xiaoping Liu, Yangzi Che, Weilin Liao, Yuyu Zhou, and Xinchang Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-416, https://doi.org/10.5194/essd-2024-416, 2024
Revised manuscript accepted for ESSD
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Absence of globally consistent and spatially continuous urban surface properties have long prevented large-scale high-resolution urban climate modeling. We developed the U-Surf data, a 1km-resolution dataset that provides key urban surface properties worldwide. U-Surf enhances urban representation in models, enables city-to-city comparison, and supports kilometer-scale Earth system modeling. Its broader applications can be extended to machine learning and many other non-climatic practices.
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).
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
Short summary
Short summary
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
Short summary
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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
Short summary
Short summary
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.
Cited articles
Bartholome, E. and Belward, A. S.: GLC2000: a new approach to global land
cover mapping from Earth observation data, Int. J. Remote Sens., 26,
1959–1977, https://doi.org/10.1080/01431160412331291297, 2005.
Bigelow, D. P. and Borchers, A.: Major Uses of Land in the United States
2012, U.S. Department of Agriculture, Economic Research Service, https://www.ers.usda.gov/publications/pub-details/?pubid=84879 (last access: 13 February 2023), 2017.
Billington, R. A. and Ridge, M.: Westward expansion: a history of the
American frontier, University of New Mexico Press, ISBN 9780826319814, 2001.
Boryan, C., Yang, Z., Mueller, R., and Craig, M.: Monitoring US agriculture:
the US Department of Agriculture, National Agricultural Statistics Service,
Cropland Data Layer Program, Geocarto. Int., 26, 341–358, https://doi.org/10.1080/10106049.2011.562309, 2011.
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.
Chen, G., Pan, S., Hayes, D. J., and Tian, H.: Spatial and temporal patterns of plantation forests in the United States since the 1930s: an annual and gridded data set for regional Earth system modeling, Earth Syst. Sci. Data, 9, 545–556, https://doi.org/10.5194/essd-9-545-2017, 2017.
Chen, H., Tian, H., Liu, M., Melillo, J., Pan, S., and Zhang, C.: Effect of
Land-Cover Change on Terrestrial Carbon Dynamics in the Southern United
States, J. Environ. Qual., 35, 1533–1547, https://doi.org/10.2134/jeq2005.0198, 2006.
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. Remote Sens., 103, 7–27, https://doi.org/10.1016/j.isprsjprs.2014.09.002, 2015.
Clawson, M.: Forests in the long sweep of American history, Science, 204,
1168–1174, https://doi.org/10.1126/science.204.4398.1168, 1979.
Cole, K. L., Davis, M. B., Stearns, F., Guntenspergen, G., and Walker, K.:
Historical landcover changes in the Great Lakes region, U.S. Geological Survey, Biological Resources Division, https://hdl.handle.net/11299/165997 (last access: 13 February 2023), 1998.
Coulson, D. P. and Joyce, L.: United States state-level population estimates:
Colonization to 1999, U.S. Department of Agriculture, Forest Service, Rocky
Mountain Research Station, https://doi.org/10.2737/RMRS-GTR-111, 2003.
Crossley, M. S.: County-level crop area in the USA 1840–2017,
Inter-university Consortium for Political and Social Research, Ann Arbor, MI, https://doi.org/10.3886/E115795V3, 2020.
Crossley, M. S., Burke, K. D., Schoville, S. D., and Radeloff, V. C.: Recent
collapse of crop belts and declining diversity of US agriculture since 1840,
Glob. Change Biol., 27, 151–164, https://doi.org/10.1111/gcb.15396, 2021.
Dangal, S. R. S., Felzer, B. S., and Hurteau, M. D.: Effects of agriculture and
timber harvest on carbon sequestration in the eastern US forests, J.
Geophys. Res.-Biogeo., 119, 35–54, https://doi.org/10.1002/2013JG002409, 2014.
Domke, G. M., Oswalt, S. N., Walters, B. F., and Morin, R. S.: Tree planting
has the potential to increase carbon sequestration capacity of forests in
the United States, P. Natl. Acad. Sci. USA, 117, 24649–24651,
https://doi.org/10.1073/pnas.2010840117, 2020.
Drummond, M. A. and Loveland, T. R.: Land-use pressure and a transition to
forest-cover loss in the eastern United States, BioScience, 60, 286–298,
https://doi.org/10.1525/bio.2010.60.4.7, 2010.
Ellis, E. C., Gauthier, N., Klein Goldewijk, K., Bliege Bird, R., Boivin, N., Díaz, S., Fuller, D. Q., Grill J. L., Kaplan, J. O., Kingston, N., Locke, H., McMichael, C. N. H., Ranco, D., Rick, T. C., Shaw, R. M., Stephens, L., Svenning, J., 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.
Fang, Y. and Jawitz, J. W.: High-resolution reconstruction of the United
States human population distribution, 1790 to 2010, Sci. Data, 5, 180067, https://doi.org/10.1038/sdata.2018.67, 2018.
Foster, D. R.: Land-Use History (1730–1990) and Vegetation Dynamics in
Central New-England, USA, J. Ecol., 80, 753–772, https://doi.org/10.2307/2260864, 1992.
Foster, D. R., Motzkin, G., and Slater, B.: Land-use history as long-term
broad-scale disturbance: regional forest dynamics in central New England,
Ecosystems, 1, 96–119, https://doi.org/10.1007/s100219900008,
1998.
Fretwell, J. D., Williams, J. S., and Redman, P. J.: National water summary
on wetland resources, U.S. Government Printing Office, https://doi.org/10.3133/wsp2425, 1996.
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N.,
Sibley, A., and Huang, X.: MODIS Collection 5 global land cover: Algorithm
refinements and characterization of new datasets, Remote Sens. Environ.,
114, 168–182, https://doi.org/10.1016/j.rse.2009.08.016, 2010.
Fuchs, R., Herold, M., Verburg, P. H., and Clevers, J. G. P. W.: A high-resolution and harmonized model approach for reconstructing and analysing historic land changes in Europe, Biogeosciences, 10, 1543–1559, https://doi.org/10.5194/bg-10-1543-2013, 2013.
Garrison, C. E.: Forestry and Tree Planting in Virginia, Reforestation, Nurseries, and Genetic Resources (RNGR), https://rngr.net/publications/tpn/55-2/forestry-and-tree-planting-in-virginia (last access: 13 February 2023), 2012.
Grassi, G., House, J., Dentener, F., Federici, S., den Elzen, M., and
Penman, J.: The key role of forests in meeting climate targets requires
science for credible mitigation, Nature Clim. Change, 7, 220–226, https://doi.org/10.1038/nclimate3227, 2017.
Griscom, B. W., Adams, J., Ellis, P. W., Houghton, R. A., Lomax, G., Miteva,
D. A., Schlesinger, W. H., Shoch, D., Siikamaki, J. V., Smith, P., Woodbury,
P., Zganjar, C., Blackman, A., Campari, J., Conant, R. T., Delgado, C.,
Elias, P., Gopalakrishna, T., Hamsik, M. R., Herrero, M., Kiesecker, J.,
Landis, E., Laestadius, L., Leavitt, S. M., Minnemeyer, S., Polasky, S.,
Potapov, P., Putz, F. E., Sanderman, J., Silvius, M., Wollenberg, E., and
Fargione, J.: Natural climate solutions, P. Natl. Acad. Sci. USA,
114, 11645–11650, https://doi.org/10.1073/pnas.1710465114,
2017.
Hagenauer, J. and Helbich, M.: A geographically weighted artificial neural
network, Int. J. Geogr. Inform. Sci., 36,
215–235, https://doi.org/10.1080/13658816.2021.1871618, 2022.
Haines, M., Fishback, P., and Rhode, P.: United States Agriculture Data,
1840–2012, Inter-university Consortium for Political and Social Research,
https://doi.org/10.3886/ICPSR35206.v4, 2018.
Hall, B., Motzkin, G., Foster, D. R., Syfert, M., and Burk, J.: Three
hundred years of forest and land-use change in Massachusetts, USA, J.
Biogeogr., 29, 1319–1335, https://doi.org/10.1046/j.1365-2699.2002.00790.x, 2002.
Hanberry, B. B., Kabrick, J. M., He, H. S., and Palik, B. J.: Historical
trajectories and restoration strategies for the Mississippi River Alluvial
Valley, For. Eco. Manag., 280, 103–111, https://doi.org/10.1016/j.foreco.2012.05.033, 2012.
Heimlich, R. E. and Daugherty, A. B.: America's cropland: Where does it come from,
United States Department of Agriculture, 3–9, https://handle.nal.usda.gov/10113/IND20394000 (last access: 13 February 2023), 1991.
Hart, J. F.: Loss and abandonment of cleared farm land in the Eastern United
States, An. Assoc. Am. Geogr., 58, 417–440, 1968.
He, F., Li, S., and Zhang, X.: A spatially explicit reconstruction of forest
cover in China over 1700–2000, Glob. Planet. Change, 131, 73–81, https://doi.org/10.1016/j.gloplacha.2015.05.008, 2015.
Homer, C., Dewitz, J., Jin, S., Xian, G., Costello, C., Danielson, P., Gass,
L., Funk, M., Wickham, J., Stehman, S., Auch, R., and Riitters, K.:
Conterminous United States land cover change patterns 2001–2016 from the
2016 National Land Cover Database, ISPRS. J. Photogramm. Remote, 162,
184–199, https://doi.org/10.1016/j.isprsjprs.2020.02.019, 2020.
Houghton, R. A., Hackler, J. L., and Lawrence, K. T.: The US carbon budget:
Contributions from land-use change, Science, 285, 574–578, https://doi.org/10.1126/science.285.5427.574, 1999.
Hurt, R. D.: American agriculture: A brief history, Purdue University Press,
2002.
Hurtt, G. C., Frolking, S., Fearon, M. G., Moore, B., Shevliakova, E.,
Malyshev, S., Pacala, S. W., and Houghton, R. A.: The underpinnings of
land-use history: three centuries of global gridded land-use transitions,
wood-harvest activity, and resulting secondary lands, Glob. Change Biol.,
12, 1208–1229, https://doi.org/10.1111/j.1365-2486.2006.01150.x, 2006.
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.
Jeon, S. B., Olofsson, P., and Woodcock, C. E.: Land use change in New
England: a reversal of the forest transition, J. Land Use Sci., 9, 105–130,
https://doi.org/10.1080/1747423X.2012.754962, 2014.
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.
Lark, T. J., Mueller, R. M., Johnson, D. M., and Gibbs, H. K.: Measuring
land-use and land-cover change using the US department of agriculture's
cropland data layer: Cautions and recommendations, Int. J. Appl. Earth Obs.
Geoinf., 62, 224–235, https://doi.org/10.1016/j.jag.2017.06.007, 2017.
Lark, T. J., Spawn, S. A., Bougie, M., and Gibbs, H. K.: Cropland expansion
in the United States produces marginal yields at high costs to wildlife,
Nat. Commun., 11, 1–11, https://doi.org/10.1038/s41467-020-18045-z, 2020.
Lark, T. J., Schelly, I. H., and Gibbs, H. K.: Accuracy, Bias, and
Improvements in Mapping Crops and Cropland across the United States Using
the USDA Cropland Data Layer, Remote Sens., 13, 968, https://doi.org/10.3390/rs13050968, 2021.
Leyk, S. and Uhl, J. H.: HISDAC-US, historical settlement data compilation
for the conterminous United States over 200 years, Sci. Data, 5, 1–14,
https://doi.org/10.1038/sdata.2018.175, 2018.
Leyk, S., Uhl, J. H., Connor, D. S., Braswell, A. E., Mietkiewicz, N.,
Balch, J. K., and Gutmann, M.: Two centuries of settlement and urban
development in the United States, Sci. Adv., 6, eaba2937, https://doi.org/10.1126/sciadv.aba2937, 2020.
Li, S., He, F., and Zhang, X.: A spatially explicit reconstruction of
cropland cover in China from 1661 to 1996, Regional Environmental Change,
16, 417–428, https://doi.org/10.1007/s10113-014-0751-4, 2016.
Li, X., Yu, L., Sohl, T., Clinton, N., Li, W., Zhu, Z., Liu, X., and Gong,
P.: A cellular automata downscaling based 1 km global land use datasets
(2010–2100), Sci. Bull., 61, 1651–1661,
https://doi.org/10.1007/s11434-016-1148-1, 2016.
Li, X., Tian, H., Pan, S., and Lu, C.: Land use and land cover changes in
the contiguous United States from 1630 to 2020 (v2.0), Zenodo [data set], https://doi.org/10.5281/zenodo.7055086, 2022.
Liu, M. and Tian, H.: China's land cover and land use change from 1700 to
2005: Estimations from high-resolution satellite data and historical
archives, Global Biogeochem. Cy., 24, GB3003, https://doi.org/10.1029/2009gb003687, 2010.
Liu, X., Liang, X., Li, X., Xu, X., Ou, J., Chen, Y., Li, S., Wang, S., and
Pei, F.: A future land use simulation model (FLUS) for simulating multiple
land use scenarios by coupling human and natural effects, Landsc. Urban
Plan., 168, 94–116, https://doi.org/10.1016/j.landurbplan.2017.09.019, 2017.
MacCleery, D. W.: American forests: a history of resiliency and recovery,
U.S. Department of Agriculture, Forest History Society, ISBN 0890300488, 2011.
Meinig, D. W.: The Shaping of America: A Geographical Perspective on 500
Years of History, vol. 2: Continental America, 1800–1867, Yale University Press, https://www.jstor.org/stable/j.ctt5hk0p1 (last access: 13 February 2023), 1993.
Mergener, R., Botti, W., and Heyd, R.: Forestry and Tree Planting in
Michigan, Reforestation, Nurseries, and Genetic Resources (RNGR), https://rngr.net/publications/tpn/57-1/forestry-and-tree-planting-in-michigan (last access: 13 February 2023), 2014.
Olmstead, A. L. and Rhode, P. W.: A history of California agriculture, Giannini
Foundation of Agricultural Economics, University of California, https://giannini.ucop.edu/ (last access: 13 February 2023), 2017.
Oswalt, S. N., Smith, W. B., Miles, P. D. and Pugh, Scott, A.: Forest
Resources of the United States, 2012: a technical document supporting the
Forest Service 2010 update of the RPA Assessment, U.S. Department of
Agriculture, Forest Service, Washington Office, https://doi.org/10.2737/WO-GTR-91, 2014.
Oswalt, S. N., Miles, P. D., Pugh, S. A., and Smith, W. B.: Forest
Resources of the United States, 2017: a technical document supporting the
Forest Service 2020 RPA Assessment, U.S. Department of Agriculture, Forest
Service, Washington Office, https://doi.org/10.2737/WO-GTR-97, 2019.
Peng, S., Ciais, P., Maignan, F., Li, W., Chang, J., Wang, T., and Yue, C.:
Sensitivity of land use change emission estimates to historical land use and
land cover mapping, Global Biogeochem. Cy., 31, 626–643, https://doi.org/10.1002/2015gb005360, 2017.
Reuss, L. A., Wooten, H. H., and Marschner, F. J.: Inventory of Major Land Uses in the United States, U.S.
Department of Agriculture, https://ageconsearch.umn.edu/record/314797 (last access: 13 February 2023), 1948.
Rollins, M. G.: LANDFIRE: a nationally consistent vegetation, wildland fire,
and fuel assessment, Int. J. Wildland Fire, 18, 235–249, https://doi.org/10.1071/WF08088, 2009.
Schulman, S. A.: The Lumber Industry of the Upper Cumberland River Valley, Tennessee Historical Quarterly, 32, 255–264, https://www.jstor.org/stable/42623392 (last access: 3 February 2023), 1973.
Smith, W. B., Vissage, J. S., Darr, D. R., and Sheffield, R. M.: Forest
Resources of the United States, 1997, U.S. Department of Agriculture Forest
Service, https://doi.org/10.2737/NC-GTR-219, 2001.
Sohl, T., Reker, R., Bouchard, M., Sayler, K., Dornbierer, J., Wika, S.,
Quenzer, R., and Friesz, A.: Modeled historical land use and land cover for
the conterminous United States, J. Land Use Sci., 11, 476–499, https://doi.org/10.1080/1747423X.2016.1147619, 2016.
Sohl, T. L., Sayler, K. L., Bouchard, M. A., Reker, R. R., Friesz, A. M.,
Bennett, S. L., Sleeter, B. M., Sleeter, R. R., Wilson, T., and Soulard, C.:
Spatially explicit modeling of 1992–2100 land cover and forest stand age
for the conterminous United States, Ecol. Appl., 24, 1015–1036, https://doi.org/10.1890/13-1245.1, 2014.
Stanturf, J. A., Palik, B. J., and Dumroese, R. K.: Contemporary forest
restoration: A review emphasizing function, For. Ecol. Manag., 331, 292–323,
https://doi.org/10.1016/j.foreco.2014.07.029, 2014.
Steyaert, L. T. and Knox, R. G.: Reconstructed historical land cover and
biophysical parameters for studies of land-atmosphere interactions within
the eastern United States, J. Geophys. Res.-Atmos., 113, D02101, https://doi.org/10.1029/2006jd008277, 2008.
Thompson, J. R., Carpenter, D. N., Cogbill, C. V., and Foster, D. R.: Four
Centuries of Change in Northeastern United States Forests, Plos One, 8,
e72540, https://doi.org/10.1371/journal.pone.0072540, 2013.
Tian, H., Chen, G., Zhang, C., Liu, M., Sun, G., Chappelka, A., Ren, W., Xu,
X., Lu, C., and Pan, S.: Century-scale responses of ecosystem carbon storage
and flux to multiple environmental changes in the southern United States,
Ecosystems, 15, 674–694, https://doi.org/10.1007/s10021-012-9539-x, 2012.
Tian, H., Banger, K., Tao, B., and Dadhwal, V. K.: History of land use in India
during 1880–2010: Large-scale land transformation reconstructed from
satellite data and historical achieves, Glob. Planet. Change, 121, 76–88,
https://doi.org/10.1016/j.gloplacha.2014.07.005, 2014.
Tian, H., Xu, R., Pan, S., Yao, Y., Bian, Z., Cai, W., Hopkinson, C.,
Justic, D., Lohrenz, S., Lu, C., Ren, W., and Yang, J.: Long-term trajectory of
nitrogen loading and delivery from Mississippi River Basin to the Gulf of
Mexico, Global Biogeochem. Cy., 34, e2019GB006475, https://doi.org/10.1029/2019GB006475, 2020.
Uhl, J. H., Leyk, S., McShane, C. M., Braswell, A. E., Connor, D. S., and Balk, D.: Fine-grained, spatiotemporal datasets measuring 200 years of land development in the United States, Earth Syst. Sci. Data, 13, 119–153, https://doi.org/10.5194/essd-13-119-2021, 2021.
U.S. Department of Agriculture: Summary Report: 2017 National Resources
Inventory, Natural Resources Conservation Service Washington, D.C., and Center
for Survey Statistics and Methodology, Iowa State University, Ames, Iowa, https://www.nrcs.usda.gov/nri (last access: 13 February 2023),
2020.
U.S. Department of Agriculture and Economic Research Service: Our Land and Water Resources: Current and Prospective Supplies and Uses, U.S. Government Printing Office, https://www.govinfo.gov/app/details/CZIC-s21-a46-no-1290 (last access: 13 February 2023), 1974.
Verburg, P. H. and Overmars, K. P.: Combining top-down and bottom-up
dynamics in land use modeling: exploring the future of abandoned farmlands
in Europe with the Dyna-CLUE model, Landscape Ecol., 24, 1167–1181,
https://doi.org/10.1007/s10980-009-9355-7, 2009.
Verburg, P. H., Schulp, C. J. E., Witte, N., and Veldkamp, A.: Downscaling
of land use change scenarios to assess the dynamics of European landscapes,
Agr. Ecosyst. Environ., 114, 39–56, https://doi.org/10.1016/j.agee.2005.11.024, 2006.
Waisanen, P. J. and Bliss, N. B.: Changes in population and agricultural
land in conterminous United States counties, 1790 to 1997, Global
Biogeochem. Cy., 16, 84-81–84-19, https://doi.org/10.1029/2001gb001843, 2002.
West, T. O., Page, Y. L., Huang, M., Wolf, J., and Thomson, A. M.:
Downscaling global land cover projections from an integrated assessment
model for use in regional analyses: results and evaluation for the US from
2005 to 2095, Environ. Res. Lett., 9, 064004, https://doi.org/10.1088/1748-9326/9/6/064004, 2014.
Winkler, K., Fuchs, R., Rounsevell, M., and Herold, M.: Global land use
changes are four times greater than previously estimated, Nat. Commun., 12,
1–10, https://doi.org/10.1038/s41467-021-22702-2, 2021.
Williams, M.: Americans and Their Forests: A Historical Geography, Cambridge University Press, ISBN 9780521428378, 1992.
Yang, J., Tao, B., Shi, H., Ouyang, Y., Pan, S., Ren, W., and Lu, C.:
Integration of remote sensing, county-level census, and machine learning for
century-long regional cropland distribution data reconstruction, Int. J.
Appl. Earth Obs. Geoinf., 91, 102151, https://doi.org/10.1016/j.jag.2020.102151, 2020.
Yang, L., Jin, S., Danielson, P., Homer, C., Gass, L., Bender, S. M., Case,
A., Costello, C., Dewitz, J., Fry, J., Funk, M., Granneman, B., Liknes, G.
C., Rigge, M., and Xian, G.: A new generation of the United States National
Land Cover Database: Requirements, research priorities, design, and
implementation strategies, ISPRS. J. Photogramm. Remote, 146, 108–123,
https://doi.org/10.1016/j.isprsjprs.2018.09.006, 2018.
Yu, Z. and Lu, C.: Historical cropland of the continental U.S. from 1850 to
2016, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.881801, 2017.
Yu, Z. and Lu, C.: Historical cropland expansion and abandonment in the
continental U.S. during 1850 to 2016, Glob. 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, https://doi.org/10.1111/gcb.14768, 2019.
Zumkehr, A. and Campbell, J. E.: Historical U.S. Cropland areas and the
potential for bioenergy production on abandoned croplands, Environ. Sci.
Technol., 47, 3840–3847, https://doi.org/10.1021/es3033132,
2013.
Short summary
We reconstructed land use and land cover (LULC) history for the conterminous United States during 1630–2020 by integrating multi-source data. The results show the widespread expansion of cropland and urban land and the shrinking of natural vegetation in the past four centuries. Forest planting and regeneration accelerated forest recovery since the 1920s. The datasets can be used to assess the LULC impacts on the ecosystem's carbon, nitrogen, and water cycles.
We reconstructed land use and land cover (LULC) history for the conterminous United States...
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