Articles | Volume 13, issue 1
https://doi.org/10.5194/essd-13-119-2021
© Author(s) 2021. 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-13-119-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
27 Jan 2021
Data description paper |
| 27 Jan 2021
| 27 Jan 2021
Fine-grained, spatiotemporal datasets measuring 200 years of land development in the United States
Johannes H. Uhl
CORRESPONDING AUTHOR
Department of Geography, University of Colorado Boulder, Boulder, CO 80309, USA
Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO 80309, USA
Stefan Leyk
Department of Geography, University of Colorado Boulder, Boulder, CO 80309, USA
Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO 80309, USA
Caitlin M. McShane
Department of Geography, University of Colorado Boulder, Boulder, CO 80309, USA
Anna E. Braswell
Earth Lab, Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO 80303, USA
Dylan S. Connor
School of Geographical Sciences & Urban Planning, Arizona State University, Tempe, AZ 85281, USA
Deborah Balk
CUNY Institute for Demographic Research and Marxe School of Public and International Affairs, Baruch College, City University of New York, New York City, NY 10017, USA
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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.
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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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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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Adrià Descals, Serge Wich, Zoltan Szantoi, Matthew J. Struebig, Rona Dennis, Zoe Hatton, Thina Ariffin, Nabillah Unus, David L. A. Gaveau, and Erik Meijaard
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Xiao Zhang, Tingting Zhao, Hong Xu, Wendi Liu, Jinqing Wang, Xidong Chen, and Liangyun Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-320, https://doi.org/10.5194/essd-2023-320, 2023
Revised manuscript accepted for ESSD
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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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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
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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.
Hui Li, Xiaobo Wang, Shaoqiang Wang, Yuanyuan Liu, Zhenhai Liu, Shiliang Chen, Qinyi Wang, Tongtong Zhu, Lunche Wang, and Lizhe Wang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-125, https://doi.org/10.5194/essd-2023-125, 2023
Revised manuscript accepted for ESSD
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As one of the major rice producing countries, China has obvious regional differences in rice types and planting patternsIn this study, the 2003–2020 Chinese seasonal rice calendar extracted from remote sensing data and other data is used to prove that the planting period of rice in China is significantly delayed and the maturity period is advanced. The results will provide data support for rice management and related industry development under future climate scenarios in China.
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.
Elena Aragoneses, Mariano García, Michele Salis, Luís M. Ribeiro, and Emilio Chuvieco
Earth Syst. Sci. Data, 15, 1287–1315, https://doi.org/10.5194/essd-15-1287-2023, https://doi.org/10.5194/essd-15-1287-2023, 2023
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We present a new hierarchical fuel classification system with a total of 85 fuels that is useful for preventing fire risk at different spatial scales. Based on this, we developed a European fuel map (1 km resolution) using land cover datasets, biogeographic datasets, and bioclimatic modelling. We validated the map by comparing it to high-resolution data, obtaining high overall accuracy. Finally, we developed a crosswalk for standard fuel models as a first assignment of fuel parameters.
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
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Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
Xiaoyong Li, Hanqin Tian, Chaoqun Lu, and Shufen Pan
Earth Syst. Sci. Data, 15, 1005–1035, https://doi.org/10.5194/essd-15-1005-2023, https://doi.org/10.5194/essd-15-1005-2023, 2023
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We reconstructed land use and land cover (LULC) history for the conterminous United States during 1630–2020 by integrating multi-source data. The results show the widespread expansion of cropland and urban land and the shrinking of natural vegetation in the past four centuries. Forest planting and regeneration accelerated forest recovery since the 1920s. The datasets can be used to assess the LULC impacts on the ecosystem's carbon, nitrogen, and water cycles.
Huifang Zhang, Zhonggang Tang, Binyao Wang, Hongcheng Kan, Yi Sun, Yu Qin, Baoping Meng, Meng Li, Jianjun Chen, Yanyan Lv, Jianguo Zhang, Shuli Niu, and Shuhua Yi
Earth Syst. Sci. Data, 15, 821–846, https://doi.org/10.5194/essd-15-821-2023, https://doi.org/10.5194/essd-15-821-2023, 2023
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The accuracy of regional grassland aboveground biomass (AGB) is always limited by insufficient ground measurements and large spatial gaps with satellite pixels. This paper used more than 37 000 UAV images as bridges to successfully obtain AGB values matching MODIS pixels. The new AGB estimation model had good robustness, with an average R2 of 0.83 and RMSE of 34.13 g m2. Our new dataset provides important input parameters for understanding the Qinghai–Tibet Plateau during global climate change.
Huaqing Wu, Jing Zhang, Zhao Zhang, Jichong Han, Juan Cao, Liangliang Zhang, Yuchuan Luo, Qinghang Mei, Jialu Xu, and Fulu Tao
Earth Syst. Sci. Data, 15, 791–808, https://doi.org/10.5194/essd-15-791-2023, https://doi.org/10.5194/essd-15-791-2023, 2023
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High-spatiotemporal-resolution rice yield datasets are limited over a large region. We proposed an explicit method to predict rice yield based on machine learning methods and generated a seasonal 4 km resolution rice yield dataset across Asia (AsiaRiceYield4km) for 1995–2015. The seasonal rice yield accuracy of AsiaRiceYield4km is high and much improved compared with previous datasets. AsiaRiceYield4km will fill the current data gap and better support agricultural monitoring systems.
Steve Ahlswede, Christian Schulz, Christiano Gava, Patrick Helber, Benjamin Bischke, Michael Förster, Florencia Arias, Jörn Hees, Begüm Demir, and Birgit Kleinschmit
Earth Syst. Sci. Data, 15, 681–695, https://doi.org/10.5194/essd-15-681-2023, https://doi.org/10.5194/essd-15-681-2023, 2023
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Imagery from air and space is the primary source of large-scale forest mapping. Our study introduces a new dataset with over 50000 image patches prepared for deep learning tasks. We show how the information for 20 European tree species can be extracted from different remote sensing sensors. Our algorithms can detect single species with precision scores up to 88 %. With a pixel size of 20×20 cm, forestry administration can now derive large-scale tree species maps at a very high resolution.
Qian Shi, Mengxi Liu, Andrea Marinoni, and Xiaoping Liu
Earth Syst. Sci. Data, 15, 555–577, https://doi.org/10.5194/essd-15-555-2023, https://doi.org/10.5194/essd-15-555-2023, 2023
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A large-scale and high-resolution urban green space (UGS) product with 1 m of 31 major cities in China (UGS-1m) is generated based on a deep learning framework to provide basic UGS information for relevant UGS research, such as distribution, area, and UGS rate. Moreover, an urban green space dataset (UGSet) with a total of 4454 samples of 512 × 512 in size are also supplied as the benchmark to support model training and algorithm comparison.
Raphaël d'Andrimont, Martin Claverie, Pieter Kempeneers, Davide Muraro, Momchil Yordanov, Devis Peressutti, Matej Batič, and François Waldner
Earth Syst. Sci. Data, 15, 317–329, https://doi.org/10.5194/essd-15-317-2023, https://doi.org/10.5194/essd-15-317-2023, 2023
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AI4boundaries is an open AI-ready data set to map field boundaries with Sentinel-2 and aerial photography provided with harmonised labels covering seven countries and 2.5 M parcels in Europe.
Xiao Zhang, Liangyun Liu, Tingting Zhao, Xidong Chen, Shangrong Lin, Jinqing Wang, Jun Mi, and Wendi Liu
Earth Syst. Sci. Data, 15, 265–293, https://doi.org/10.5194/essd-15-265-2023, https://doi.org/10.5194/essd-15-265-2023, 2023
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An accurate global 30 m wetland dataset that can simultaneously cover inland and coastal zones is lacking. This study proposes a novel method for wetland mapping and generates the first global 30 m wetland map with a fine classification system (GWL_FCS30), including five inland wetland sub-categories (permanent water, swamp, marsh, flooded flat and saline) and three coastal wetland sub-categories (mangrove, salt marsh and tidal flats).
Chong Liu, Xiaoqing Xu, Xuejie Feng, Xiao Cheng, Caixia Liu, and Huabing Huang
Earth Syst. Sci. Data, 15, 133–153, https://doi.org/10.5194/essd-15-133-2023, https://doi.org/10.5194/essd-15-133-2023, 2023
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Rapid Arctic changes are increasingly influencing human society, both locally and globally. Land cover offers a basis for characterizing the terrestrial world, yet spatially detailed information on Arctic land cover is lacking. We employ multi-source data to develop a new land cover map for the circumpolar Arctic. Our product reveals regionally contrasting biome distributions not fully documented in existing studies and thus enhances our understanding of the Arctic’s terrestrial system.
Jingliang Hu, Rong Liu, Danfeng Hong, Andrés Camero, Jing Yao, Mathias Schneider, Franz Kurz, Karl Segl, and Xiao Xiang Zhu
Earth Syst. Sci. Data, 15, 113–131, https://doi.org/10.5194/essd-15-113-2023, https://doi.org/10.5194/essd-15-113-2023, 2023
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Multimodal data fusion is an intuitive strategy to break the limitation of individual data in Earth observation. Here, we present a multimodal data set, named MDAS, consisting of synthetic aperture radar (SAR), multispectral, hyperspectral, digital surface model (DSM), and geographic information system (GIS) data for the city of Augsburg, Germany, along with baseline models for resolution enhancement, spectral unmixing, and land cover classification, three typical remote sensing applications.
Furong Li, Marie-José Gaillard, Xianyong Cao, Ulrike Herzschuh, Shinya Sugita, Jian Ni, Yan Zhao, Chengbang An, Xiaozhong Huang, Yu Li, Hongyan Liu, Aizhi Sun, and Yifeng Yao
Earth Syst. Sci. Data, 15, 95–112, https://doi.org/10.5194/essd-15-95-2023, https://doi.org/10.5194/essd-15-95-2023, 2023
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The objective of this study is present the first gridded and temporally continuous quantitative plant-cover reconstruction for temperate and northern subtropical China over the last 12 millennia. The reconstructions are based on 94 pollen records and include estimates for 27 plant taxa, 10 plant functional types, and 3 land-cover types. The dataset is suitable for palaeoclimate modelling and the evaluation of simulated past vegetation cover and anthropogenic land-cover change from models.
Jose Luis Gómez-Dans, Philip Edward Lewis, Feng Yin, Kofi Asare, Patrick Lamptey, Kenneth Kobina Yedu Aidoo, Dilys Sefakor MacCarthy, Hongyuan Ma, Qingling Wu, Martin Addi, Stephen Aboagye-Ntow, Caroline Edinam Doe, Rahaman Alhassan, Isaac Kankam-Boadu, Jianxi Huang, and Xuecao Li
Earth Syst. Sci. Data, 14, 5387–5410, https://doi.org/10.5194/essd-14-5387-2022, https://doi.org/10.5194/essd-14-5387-2022, 2022
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We provide a data set to support mapping croplands in smallholder landscapes in Ghana. The data set contains information on crop location on three agroecological zones for 2 years, temporal series of measurements of leaf area index and leaf chlorophyll concentration for maize canopies and yield. We demonstrate the use of these data to validate cropland masks, create a maize mask using satellite data and explore the relationship between satellite measurements and yield.
Zhen Yu, Jing Liu, and Giri Kattel
Earth Syst. Sci. Data, 14, 5179–5194, https://doi.org/10.5194/essd-14-5179-2022, https://doi.org/10.5194/essd-14-5179-2022, 2022
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We developed a 5 km annual nitrogen (N) fertilizer use dataset in China, covering the period from 1952 to 2018. We found that previous FAO-data-based N fertilizer products overestimated the N use in low, but underestimated in high, cropland coverage areas in China. The new dataset has improved the spatial distribution and corrected the existing biases, which is beneficial for biogeochemical cycle simulations in China, such as the assessment of greenhouse gas emissions and food production.
Femke van Geffen, Birgit Heim, Frederic Brieger, Rongwei Geng, Iuliia A. Shevtsova, Luise Schulte, Simone M. Stuenzi, Nadine Bernhardt, Elena I. Troeva, Luidmila A. Pestryakova, Evgenii S. Zakharov, Bringfried Pflug, Ulrike Herzschuh, and Stefan Kruse
Earth Syst. Sci. Data, 14, 4967–4994, https://doi.org/10.5194/essd-14-4967-2022, https://doi.org/10.5194/essd-14-4967-2022, 2022
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SiDroForest is an attempt to remedy data scarcity regarding vegetation data in the circumpolar region, whilst providing adjusted and labeled data for machine learning and upscaling practices. SiDroForest contains four datasets that include SfM point clouds, individually labeled trees, synthetic tree crowns and labeled Sentinel-2 patches that provide insights into the vegetation composition and forest structure of two important vegetation transition zones in Siberia, Russia.
Hanqin Tian, Zihao Bian, Hao Shi, Xiaoyu Qin, Naiqing Pan, Chaoqun Lu, Shufen Pan, Francesco N. Tubiello, Jinfeng Chang, Giulia Conchedda, Junguo Liu, Nathaniel Mueller, Kazuya Nishina, Rongting Xu, Jia Yang, Liangzhi You, and Bowen Zhang
Earth Syst. Sci. Data, 14, 4551–4568, https://doi.org/10.5194/essd-14-4551-2022, https://doi.org/10.5194/essd-14-4551-2022, 2022
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Nitrogen is one of the critical nutrients for growth. Evaluating the change in nitrogen inputs due to human activity is necessary for nutrient management and pollution control. In this study, we generated a historical dataset of nitrogen input to land at the global scale. This dataset consists of nitrogen fertilizer, manure, and atmospheric deposition inputs to cropland, pasture, and rangeland at high resolution from 1860 to 2019.
Raphaël d'Andrimont, Momchil Yordanov, Laura Martinez-Sanchez, Peter Haub, Oliver Buck, Carsten Haub, Beatrice Eiselt, and Marijn van der Velde
Earth Syst. Sci. Data, 14, 4463–4472, https://doi.org/10.5194/essd-14-4463-2022, https://doi.org/10.5194/essd-14-4463-2022, 2022
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Between 2006 and 2018, 875 661 LUCAS cover (i.e. close-up) photos were taken over a systematic sample of the European Union. This geo-located photo dataset has been curated and is being made available along with the surveyed label data, including land cover and plant species.
Han Su, Bárbara Willaarts, Diana Luna-Gonzalez, Maarten S. Krol, and Rick J. Hogeboom
Earth Syst. Sci. Data, 14, 4397–4418, https://doi.org/10.5194/essd-14-4397-2022, https://doi.org/10.5194/essd-14-4397-2022, 2022
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There are over 608 million farms around the world but they are not the same. We developed high spatial resolution maps showing where small and large farms were located and which crops were planted for 56 countries. We checked the reliability and have the confidence to use them for the country level and global studies. Our maps will help more studies to easily measure how agriculture policies, water availability, and climate change affect small and large farms.
Zhen Qian, Min Chen, Yue Yang, Teng Zhong, Fan Zhang, Rui Zhu, Kai Zhang, Zhixin Zhang, Zhuo Sun, Peilong Ma, Guonian Lü, Yu Ye, and Jinyue Yan
Earth Syst. Sci. Data, 14, 4057–4076, https://doi.org/10.5194/essd-14-4057-2022, https://doi.org/10.5194/essd-14-4057-2022, 2022
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Roadside noise barriers (RNBs) are important urban infrastructures to ensure a city is liveable. This study provides the first reliable and nationwide vectorized RNB dataset with street view imagery in China. The generated RNB dataset is evaluated in terms of two aspects, i.e., the detection accuracy and the completeness and positional accuracy. The method is based on a developed geospatial artificial intelligence framework.
Cited articles
Balch, J. K., Iglesias, V., Braswell, A. E., Rossi, M. W., Joseph, M. B., Mahood, A. L., Shrum, T. R., White, C. T., Scholl, V. M., McGuire, B., and Karban, C.: Social-Environmental Extremes: Rethinking Extraordinary Events as
Outcomes of Interacting Biophysical and Social Systems, Earth's Future, 8,
e2019EF001319, https://doi.org/10.1029/2019EF001319, 2020. a
Baldauf, M., Garlappi, L., and Yannelis, C.: Does climate change affect real
estate prices? Only if you believe in it, The Review of Financial Studies,
33, 1256–1295, 2020. a
Balk, D. and Yetman, G.: The global distribution of population: evaluating the
gains in resolution refinement, Center for International Earth Science
Information Network (CIESIN), Columbia University, New York, 2004. a
Bechard, A.: Gone with the Wind: Declines in Property Values as Harmful Algal
Blooms Are Blown Towards the Shore, J. Real Estate Financ., 1–16, https://doi.org/10.1007/s11146-020-09749-6, 2020. a
Bernstein, A., Gustafson, M. T., and Lewis, R.: Disaster on the horizon: The
price effect of sea level rise, J. Financ. Econ., 134,
253–272, 2019. a
Boeing, G.: Off the Grid… and Back Again? The Recent Evolution of American
Street Network Planning and Design, J. Am. Plann.
Assoc., 87,
123–137,
https://doi.org/10.1080/01944363.2020.1819382, 2020. a
Boslett, A. and Hill, E.: Shale gas transmission and housing prices, Resour. Energy Econ., 57, 36–50, 2019. a
Buchanan, M. K., Kulp, S., Cushing, L., Morello-Frosch, R., Nedwick, T., and
Strauss, B.: Sea level rise and coastal flooding threaten affordable housing,
Environ. Res. Lett., 15, 124020, https://doi.org/10.1088/1748-9326/abb266, 2020. a
Butler, M. A.: Rural-urban continuum codes for metro and nonmetro counties,
9028, US Department of Agriculture, Economic Research Service, Agriculture
and …, Washington D.C., USA, 1990. a
CIESIN: Global Rural-Urban Mapping Project.(GRUMP): Urban/rural population
grids., 2004. a
City of Los Angeles Controller's Office: Affordable Housing: Incentives
and Oversight, available at:
https://lacontroller.org/data-stories-and-maps/affordable-housing-incentives-and-oversight/ (last access: 25 January 2021),
2017. a
Clarke, W. and Freedman, M.: The rise and effects of homeowners associations,
J. Urban Econ., 112, 1–15, 2019. a
Connor, D. S., Gutmann, M. P., Cunningham, A. R., Clement, K. K., and Leyk, S.:
How Entrenched Is the Spatial Structure of Inequality in Cities? Evidence
from the Integration of Census and Housing Data for Denver from 1940 to 2016,
Ann. Am. Assoc. Geogr., 110, 1022–1039, 2020. a
D'Lima, W. and Schultz, P.: Residential Real Estate Investments and Investor
Characteristics, J. Real Estate Financ., 1–40, https://doi.org/10.1007/s11146-020-09771-8,
2020. a
Dobson, J. E., Bright, E. A., Coleman, P. R., Durfee, R. C., and Worley, B. A.:
LandScan: a global population database for estimating populations at risk,
Photogramm. Eng. Rem. S., 66, 849–857, 2000. a
ESRI: ArcPy, available at: https://pro.arcgis.com/en/pro-app/arcpy/ (last access: 25 January 2021), 2019. a
Financial Times: Mapping how railroads built America, available at:
https://www.ft.com/video/28ef4d98-ac46-4b68-84da-3ef5cc70e730, last access: 15 July 2020. a
Freire, S., Doxsey-Whitfield, E., MacManus, K., Mills, J., and Pesaresi, M.: Development of new open and free multi-temporal global population grids at 250 m resolution,
Proceedings of the 19th AGILE International Conference on Geographic Information Science, AGILE 2016, Helsinki, Finland, 14–17 June 2016. a
GDAL/OGR contributors: GDAL/OGR Geospatial Data Abstraction software
Library, Open Source Geospatial Foundation, available at: https://gdal.org (last access: 25 January 2021),
2020. a
Gindelsky, M., Moulton, J., and Wentland, S. A.: Valuing housing services in
the era of big data: A user cost approach leveraging Zillow microdata, in:
Big Data for 21st Century Economic Statistics, University of Chicago Press, Chicago, USA,
2019. a
Hedefalk, F., Svensson, P., and Harrie, L.: Spatiotemporal historical datasets
at micro-level for geocoded individuals in five Swedish parishes, 1813–1914,
Sci. Data, 4, 1–13, 2017. a
Homer, C., Dewitz, J., Fry, J., Coan, M., Hossain, N., Larson, C., Herold, N., McKerrow, A., VanDriel, J. N., and Wickham, J.: Completion of the 2001
national land cover database for the counterminous United States,
Photogramm. Eng. Rem. S., 73, 337–341, 2007. a
Huber, P. J.: Robust regression: asymptotics, conjectures and Monte
Carlo, Ann. Stat., 1, 799–821, 1973. a
Iglesias, V. and Travis, W.: Escalating risk and pronounced inter-regional differences in exposure to natural hazards due to development patterns in the United States, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21287, https://doi.org/10.5194/egusphere-egu2020-21287, 2020 a
Jordahl, K., den Bossche, J. V., Wasserman, J., McBride, J., Fleischmann, M.,
Gerard, J., Tratner, J., Perry, M., Farmer, C., Hjelle, G. A., Gillies, S.,
Cochran, M., Bartos, M., Culbertson, L., Eubank, N., Bilogur, A., and
Albert, M.: geopandas/geopandas: v0.7.0, Zenodo, https://doi.org/10.5281/zenodo.3669853, 2020. a
Kaim, D., Kozak, J., Kolecka, N., Ziółkowska, E., Ostafin, K.,
Ostapowicz, K., Gimmi, U., Munteanu, C., and Radeloff, V. C.: Broad scale
forest cover reconstruction from historical topographic maps, Appl.
Geogr., 67, 39–48, 2016. a
Kim, M., Norwood, B., O'Connor, S., and Shen, L.: I am Jane. Do I pay more
in the housing market?, Econ. Bull., 39, 1612–1620, 2019. a
Kitchin, R.: The data revolution: Big data, open data, data infrastructures and
their consequences, Sage, London, UK, 2014. a
Klein Goldewijk, K., Beusen, A., Van Drecht, G., and De Vos, M.: The HYDE 3.1
spatially explicit database of human-induced global land-use change over the
past 12,000 years, Global Ecol. Biogeogr., 20, 73–86, 2011. a
Kugler, T. A., Grace, K., Wrathall, D. J., de Sherbinin, A., Van Riper, D., Aubrecht, C., Comer, D., Adamo, S. B., Cervone, G., Engstrom, R., and Hultquist, C.:
People and Pixels 20 years later: the current data landscape and research
trends blending population and environmental data, Popul.
Environ., 41, 209–234, 2019. a
Leyk, S. and Uhl, J. H.: Historical settlement composite layer for the U.S.
1810–2015, https://doi.org/10.7910/DVN/PKJ90M, 2018c. a, b, c, d
Leyk, S. and Uhl, J. H.: County-level uncertainty statistics accompanying the
historical settlement layers for the U.S. 1810–2015,
https://doi.org/10.7910/DVN/CXD9BW, 2018d. a, b, c, d
Leyk, S., Gaughan, A. E., Adamo, S. B., de Sherbinin, A., Balk, D., Freire, S., Rose, A., Stevens, F. R., Blankespoor, B., Frye, C., Comenetz, J., Sorichetta, A., MacManus, K., Pistolesi, L., Levy, M., Tatem, A. J., and Pesaresi, M.: The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use, Earth Syst. Sci. Data, 11, 1385–1409, https://doi.org/10.5194/essd-11-1385-2019, 2019. a, b
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. a, b, c, d
Lieskovský, J., Kaim, D., Balázs, P., Boltižiar, M., Chmiel, M., Grabska, E., Király, G., Konkoly-Gyuró, É., Kozak, J., Antalová, K., and Kuchma, T.: Historical land use dataset of the Carpathian
region (1819–1980), J. Maps, 14, 644–651, 2018. a
Marconcini, M., Gorelick, N., Metz-Marconcini, A., and Esch, T.: Accurately
monitoring urbanization at global scale – the world settlement footprint, IOP
Conference Series: Earth and Environmental Science, 509, 012036, https://doi.org/10.1088/1755-1315/509/1/012036, 2020. a
McShane, C., Uhl, J. H., and Leyk, S.: Gridded annual land use data for the
conterminous United States 1945–2016, in preparation, 2021. a
Mietkiewicz, N., Balch, J. K., Schoennagel, T., Leyk, S., St Denis, L. A., and
Bradley, B. A.: In the Line of Fire: Consequences of Human-Ignited Wildfires
to Homes in the US (1992–2015), Fire, 3, 1–20, 2020. a
Millhouser, P.: Evaluating Landscape Connectivity and Habitat Fragmentation
Effects on Elk in the Roaring Fork and Eagle Valleys, Master's Thesis,
Pennsylvania State University, University Park, Pennsylvania, 2019. a
NYC Housing Authority: Map of NYCHA Developments, available at:
https://data.cityofnewyork.us/Housing-Development/Map-of-NYCHA-Developments/i9rv-hdr5 (last access: 25 January 2021),
2020. a
Oliphant, T. E.: A guide to NumPy, vol. 1, Trelgol Publishing, USA, 2006. a
Onda, K., Branham, J., BenDor, T. K., Kaza, N., and Salvesen, D.: Does removal
of federal subsidies discourage urban development? An evaluation of the US
Coastal Barrier Resources Act, PloS one, 15, e0233888, https://doi.org/10.1371/journal.pone.0233888, 2020. a
OpenStreetMap contributors: Planet dump retrieved from
https://planet.osm.org, available at: https://www.openstreetmap.org (last access: 1 December 2020), 2020. a
Ostafin, K., Kaim, D., Siwek, T., and Miklar, A.: Historical dataset of
administrative units with social-economic attributes for Austrian Silesia
1837–1910, Sci. Data, 7, 1–14, 2020. a
Peng, L. and Zhang, L.: House Prices and Systematic Risk: Evidence from
Microdata, Real Estate Econom., 1–24, https://doi.org/10.1111/1540-6229.12277, 2019. a
Pesaresi, M., Huadong, G., Blaes, X., Ehrlich, D., Ferri, S., Gueguen, L., Halkia, M., Kauffmann, M., Kemper, T., Lu, L., and Marin-Herrera, M. A.: A global human
settlement layer from optical HR/VHR RS data: concept and first results, IEEE J. Sel. Top. Appl.,
6, 2102–2131, 2013. a
Reba, M., Reitsma, F., and Seto, K. C.: Spatializing 6,000 years of global
urbanization from 3700 BC to AD 2000, Sci. Data, 3, 1–16, 2016. a
Safe Software Inc.: Feature Manipulation Engine, available at:
https://www.safe.com/fme/fme-desktop/, last access: 1 July 2020. a
Shen, X., Liu, P., Qiu, Y. L., Patwardhan, A., and Vaishnav, P.: Estimation of
change in house sales prices in the United States after heat pump adoption,
Nature Energy, 6, 30–37, 2021. a
Smith, J. H., Wickham, J. D., Stehman, S. V., and Yang, L.: Impacts of patch
size and land-cover heterogeneity on thematic image classification accuracy,
Photogramm. Eng. Rem. S., 68, 65–70, 2002. a
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,
2016. a
SQLite: SQLite SQL database engine, available at: https://www.sqlite.org, last access: 1 July 2020. a
Stern, M. and Lester, T. W.: Does Local Ownership of Vacant Land Reduce Crime?
An Assessment of Chicago's Large Lots Program, J. Am.
Plan. Assoc., 87, 73–84, https://doi.org/10.1080/01944363.2020.1792334, 2020. a
Tarafdar, S., Rimjha, M., Hinze, N., Hotle, S., and Trani, A. A.: Urban air
Mobility Regional Landing Site Feasibility and Fare Model Analysis in the
Greater Northern California Region, in: 2019 Integrated Communications,
Navigation and Surveillance Conference (ICNS), pp. 1–11, IEEE, 9–11 April 2019,
Herndon, VA, USA, 2019. a
Tatem, A. J.: WorldPop, open data for spatial demography, Sci. Data, 4,
1–4, 2017. a
Uhl, J. H. and Leyk, S.: Uncertainty surfaces accompanying the BUPR, BUPL, and
BUA gridded surface series, https://doi.org/10.7910/DVN/T8H5KF, 2020d. a, b, c
Uhl, J. H. and Leyk, S.: Towards a novel backdating strategy for creating
built-up land time series data using contemporary spatial constraints, Remote
Sens. Environ., 238, 111197, https://doi.org/10.1016/j.rse.2019.05.016, 2020e. a
Uhl, J. H., Leyk, S., Florczyk, A. J., Pesaresi, M., and Balk, D.: Assessing
spatiotemporal agreement between multi-temporal built-up land layers and
integrated cadastral and building data, in: International Conference on
GIScience Short Paper Proceedings, vol. 1, September 2016,
Montreal, Canada, 2016. a, b
Uhl, J. H., Zoraghein, H., Leyk, S., Balk, D., Corbane, C., Syrris, V., and
Florczyk, A. J.: Exposing the urban continuum: Implications and
cross-comparison from an interdisciplinary perspective, International Journal
of Digital Earth, 13,
22–44,
2020. a
Uhl, J. H., Connor, D. S., Leyk, S., and Braswell, A. E.: A century of decoupling size and structure of urban spaces in the United States, Commun. Earth Environ.,
1–14,
https://doi.org/10.1038/s43247-020-00082-7, 2021. a, b, c
US Census Bureau: Table 4: Population from 1790 to 1990, available at:
https://www.census.gov/population/censusdata/table-4.pdf (last access: 15 July 2020), 1993. a
US Census Bureau: American Community Survey: 2011–2015,
https://www.census.gov/newsroom/press-releases/2016/cb16-210.html (last access: 25 January 2021),
2016. a
US Census Bureau, Department of Commerce: TIGER/Line Shapefile, 2016, Series
Information for the Current Place State-based Shapefile, available at:
https://catalog.data.gov/dataset/tiger-line-shapefile-2016-series-information-for-the-current-place-state-based-shapefile (last access: 1 December 2020),
2016. a
USDA Economic Research Service: Rural-Urban Continuum Codes 2013,
Documentation, available at:
https://www.ers.usda.gov/data-products/rural-urban-continuum-codes/documentation/ (last access: 1 December 2020),
2019. a
U.S. Department of Housing and Urban Development: Assisted housing: national
and local, county-level summaries 2019, available at:
https://www.huduser.gov/portal/datasets/assthsg.html (last access: 1 December 2020), 2019. a
USGS National Geospatial Technical Operations Center: USGS National
Structures Dataset – USGS National Map Downloadable Data Collection, available at:
https://catalog.data.gov/dataset/usgs-national-structures-dataset-nsd-downloadable-data-collection-national-geospatial-data-ass (last access: 1 December 2020),
2016. a
Wentland, S. A., Ancona, Z. H., Bagstad, K. J., Boyd, J., Hass, J. L.,
Gindelsky, M., and Moulton, J. G.: Accounting for land in the United States:
Integrating physical land cover, land use, and monetary valuation, Ecosystem
Services, 46, 101178, https://doi.org/10.1016/j.ecoser.2020.101178, 2020.
a
Wickham, J. D., Stehman, S. V., Gass, L., Dewitz, J., Fry, J. A., and Wade,
T. G.: Accuracy assessment of NLCD 2006 land cover and impervious surface,
Remote Sens. Environ., 130, 294–304, 2013. a
Zoraghein, H. and Leyk, S.: Data-enriched interpolation for temporally
consistent population compositions, GIScience Remote Sens., 56,
430–461, 2019. a
Short summary
Fine-grained geospatial data on the spatial distribution of human settlements are scarce prior to the era of remote-sensing-based Earth observation. In this paper, we present datasets derived from a large, novel building stock database, enabling the spatially explicit analysis of 200 years of land development in the United States at an unprecedented spatial and temporal resolution. These datasets greatly facilitate long-term studies of socio-environmental systems in the conterminous USA.
Fine-grained geospatial data on the spatial distribution of human settlements are scarce prior...
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