Articles | Volume 12, issue 3
https://doi.org/10.5194/essd-12-1953-2020
© Author(s) 2020. 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-12-1953-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
02 Sep 2020
Data description paper |
| 02 Sep 2020
| 02 Sep 2020
Earth transformed: detailed mapping of global human modification from 1990 to 2017
David M. Theobald
CORRESPONDING AUTHOR
Conservation Planning Technologies, Fort Collins, CO 80521, USA
Department of Fish, Wildlife, and Conservation Biology, Colorado State
University, Fort Collins, CO 80523, USA
Christina Kennedy
Global Lands Program, The Nature Conservancy, Fort Collins, CO 80524,
USA
Bin Chen
Department of Land, Air and Water Resources, University of California,
Davis, CA 95616, USA
James Oakleaf
Global Lands Program, The Nature Conservancy, Fort Collins, CO 80524,
USA
Sharon Baruch-Mordo
Global Lands Program, The Nature Conservancy, Fort Collins, CO 80524,
USA
Joe Kiesecker
Global Lands Program, The Nature Conservancy, Fort Collins, CO 80524,
USA
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Ziyue Chen, Danlu Chen, Mei-Po Kwan, Bin Chen, Bingbo Gao, Yan Zhuang, Ruiyuan Li, and Bing Xu
Atmos. Chem. Phys., 19, 13519–13533, https://doi.org/10.5194/acp-19-13519-2019, https://doi.org/10.5194/acp-19-13519-2019, 2019
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We employed Kolmogorov–Zurbenko filtering and WRF-CMAQ to quantify the relative contribution of meteorological variations and emission reduction to PM2.5 reduction in Beijing from 2013 to 2017, which is crucial to evaluate the Five-year Clean Air Action Plan. Both models suggested that despite favourable meteorological conditions, the control of anthropogenic emissions accounted for around 80 % of PM2.5 reduction in Beijing. Therefore, such a long-term clean air plan should be continued.
Jianzhong Ma, Christoph Brühl, Qianshan He, Benedikt Steil, Vlassis A. Karydis, Klaus Klingmüller, Holger Tost, Bin Chen, Yufang Jin, Ningwei Liu, Xiangde Xu, Peng Yan, Xiuji Zhou, Kamal Abdelrahman, Andrea Pozzer, and Jos Lelieveld
Atmos. Chem. Phys., 19, 11587–11612, https://doi.org/10.5194/acp-19-11587-2019, https://doi.org/10.5194/acp-19-11587-2019, 2019
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We find a pronounced maximum in aerosol extinction in the upper troposphere and lower stratosphere over the Tibetan Plateau during the Asian summer monsoon, caused mainly by mineral dust emitted from the northern Tibetan Plateau and slope area, lofted to and accumulating within the anticyclonic circulation. Mineral dust, water-soluble compounds, such as nitrate and sulfate, and associated liquid water dominate aerosol extinction around the tropopause within the Asian summer monsoon anticyclone.
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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.
Yating Ru, Brian Blankespoor, Ulrike Wood-Sichra, Timothy S. Thomas, Liangzhi You, and Erwin Kalvelagen
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Hanqin Tian, Zihao Bian, Hao Shi, Xiaoyu Qin, Naiqing Pan, Chaoqun Lu, Shufen Pan, Francesco N. Tubiello, Jinfeng Chang, Giulia Conchedda, Junguo Liu, Nathaniel Mueller, Kazuya Nishina, Rongting Xu, Jia Yang, Liangzhi You, and Bowen Zhang
Earth Syst. Sci. Data, 14, 4551–4568, https://doi.org/10.5194/essd-14-4551-2022, https://doi.org/10.5194/essd-14-4551-2022, 2022
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Nitrogen is one of the critical nutrients for growth. Evaluating the change in nitrogen inputs due to human activity is necessary for nutrient management and pollution control. In this study, we generated a historical dataset of nitrogen input to land at the global scale. This dataset consists of nitrogen fertilizer, manure, and atmospheric deposition inputs to cropland, pasture, and rangeland at high resolution from 1860 to 2019.
Raphaël d'Andrimont, Momchil Yordanov, Laura Martinez-Sanchez, Peter Haub, Oliver Buck, Carsten Haub, Beatrice Eiselt, and Marijn van der Velde
Earth Syst. Sci. Data, 14, 4463–4472, https://doi.org/10.5194/essd-14-4463-2022, https://doi.org/10.5194/essd-14-4463-2022, 2022
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Between 2006 and 2018, 875 661 LUCAS cover (i.e. close-up) photos were taken over a systematic sample of the European Union. This geo-located photo dataset has been curated and is being made available along with the surveyed label data, including land cover and plant species.
Han Su, Bárbara Willaarts, Diana Luna-Gonzalez, Maarten S. Krol, and Rick J. Hogeboom
Earth Syst. Sci. Data, 14, 4397–4418, https://doi.org/10.5194/essd-14-4397-2022, https://doi.org/10.5194/essd-14-4397-2022, 2022
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There are over 608 million farms around the world but they are not the same. We developed high spatial resolution maps showing where small and large farms were located and which crops were planted for 56 countries. We checked the reliability and have the confidence to use them for the country level and global studies. Our maps will help more studies to easily measure how agriculture policies, water availability, and climate change affect small and large farms.
Kandice L. Harper, Celine Lamarche, Andrew Hartley, Philippe Peylin, Catherine Ottlé, Vladislav Bastrikov, Rodrigo San Martín, Sylvia I. Bohnenstengel, Grit Kirches, Martin Boettcher, Roman Shevchuk, Carsten Brockmann, and Pierre Defourny
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-296, https://doi.org/10.5194/essd-2022-296, 2022
Revised manuscript accepted for ESSD
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We built a spatially explicit annual PFT dataset for 1992–2020 exhibiting intraclass spatial variability in PFT fractional cover at 300 m. For each year, 14 maps of PFTs percentage cover are produced: bare soil, water, permanent snow/ice, built, managed grasses, natural grasses, and trees and shrubs each split into leaf type and seasonality. ORCHIDEE and JULES model simulations indicate significant differences in simulated carbon, water, and energy fluxes in some regions using this new PFT set.
Zhen Qian, Min Chen, Yue Yang, Teng Zhong, Fan Zhang, Rui Zhu, Kai Zhang, Zhixin Zhang, Zhuo Sun, Peilong Ma, Guonian Lü, Yu Ye, and Jinyue Yan
Earth Syst. Sci. Data, 14, 4057–4076, https://doi.org/10.5194/essd-14-4057-2022, https://doi.org/10.5194/essd-14-4057-2022, 2022
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Roadside noise barriers (RNBs) are important urban infrastructures to ensure a city is liveable. This study provides the first reliable and nationwide vectorized RNB dataset with street view imagery in China. The generated RNB dataset is evaluated in terms of two aspects, i.e., the detection accuracy and the completeness and positional accuracy. The method is based on a developed geospatial artificial intelligence framework.
Matthias Demuzere, Jonas Kittner, Alberto Martilli, Gerald Mills, Christian Moede, Iain D. Stewart, Jasper van Vliet, and Benjamin Bechtel
Earth Syst. Sci. Data, 14, 3835–3873, https://doi.org/10.5194/essd-14-3835-2022, https://doi.org/10.5194/essd-14-3835-2022, 2022
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Because urban areas are key contributors to climate change but are also susceptible to multiple hazards, one needs spatially detailed information on urban landscapes to support environmental services. This global local climate zone map describes this much-needed intra-urban heterogeneity across the whole surface of the earth in a universal language and can serve as a basic infrastructure to study e.g. environmental hazards, energy demand, and climate adaptation and mitigation solutions.
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, Guido Ceccherini, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Matthew J. McGrath, Julia Nabel, Benjamin Poulter, Simone Rossi, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-245, https://doi.org/10.5194/essd-2022-245, 2022
Revised manuscript accepted for ESSD
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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 transparency and confidence in land-use CO2 flux estimates.
Xin Huang, Jie Yang, Wenrui Wang, and Zhengrong Liu
Earth Syst. Sci. Data, 14, 3649–3672, https://doi.org/10.5194/essd-14-3649-2022, https://doi.org/10.5194/essd-14-3649-2022, 2022
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Using more than 2.7 million Sentinel images, we proposed a global ISA mapping method and produced the 10-m global ISA dataset (GISA-10m), with overall accuracy exceeding 86 %. The inter-comparison between different global ISA datasets showed the superiority of our results. The ISA distribution at urban and rural was discussed and compared. For the first time, courtesy of the high spatial resolution, the global road ISA was further identified, and its distribution was discussed.
Elena Aragoneses, Mariano García, Michele Salis, Luís M. Ribeiro, and Emilio Chuvieco
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-184, https://doi.org/10.5194/essd-2022-184, 2022
Revised manuscript accepted for ESSD
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The authors present a new fuel classification system with a total of 85 fuels, useful for different spatial scales and purposes. Based on it, the authors developed a European fuel map (1 km resolution) using land cover datasets, biogeographic datasets, and bioclimatic modelling. The authors validated the map by comparing it to high-resolution data, obtaining high overall accuracy. Finally, the authors developed a crosswalk to standard fuel models as a first assignment of fuel parameters.
Jeremy Baynes, Anne Neale, and Torrin Hultgren
Earth Syst. Sci. Data, 14, 2833–2849, https://doi.org/10.5194/essd-14-2833-2022, https://doi.org/10.5194/essd-14-2833-2022, 2022
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Census data are typically provided in irregularly shaped spatial units. To get a more refined estimate of population density, we downscaled population counts from United States (US) census blocks to a 30 m grid using intelligent dasymetric mapping. Furthermore, we improved our density estimates by using multiple spatial datasets to identify and mask uninhabited areas. Masking these uninhabited areas improved density estimates for every state in the conterminous US.
Xiaoyong Li, Hanqin Tian, Shufen Pan, and Chaoqun Lu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-135, https://doi.org/10.5194/essd-2022-135, 2022
Revised manuscript accepted for ESSD
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We reconstructed land use and land cover 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.
Yi Zheng, Ana Cláudia dos Santos Luciano, Jie Dong, and Wenping Yuan
Earth Syst. Sci. Data, 14, 2065–2080, https://doi.org/10.5194/essd-14-2065-2022, https://doi.org/10.5194/essd-14-2065-2022, 2022
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Brazil is the largest sugarcane producer. Sugarcane in Brazil can be harvested all year round. The flexible phenology makes it difficult to identify sugarcane in Brazil at a country scale. We developed a phenology-based method which can identify sugarcane with limited training data. The sugarcane maps for Brazil obtain high accuracy through comparison against field samples and statistical data. The maps can be used to monitor growing conditions and evaluate the feedback to climate of sugarcane.
Xiao Zhang, Liangyun Liu, Tingting Zhao, Yuan Gao, Xidong Chen, and Jun Mi
Earth Syst. Sci. Data, 14, 1831–1856, https://doi.org/10.5194/essd-14-1831-2022, https://doi.org/10.5194/essd-14-1831-2022, 2022
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Accurately mapping impervious-surface dynamics has great scientific significance and application value for research on urban sustainable development, the assessment of anthropogenic carbon emissions and global ecological-environment modeling. In this study, a novel and accurate global 30 m impervious surface dynamic dataset (GISD30) for 1985 to 2020 was produced using the spectral-generalization method and time-series Landsat imagery on the Google Earth Engine cloud computing platform.
Vanessa Reinhart, Peter Hoffmann, Diana Rechid, Jürgen Böhner, and Benjamin Bechtel
Earth Syst. Sci. Data, 14, 1735–1794, https://doi.org/10.5194/essd-14-1735-2022, https://doi.org/10.5194/essd-14-1735-2022, 2022
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The LANDMATE plant functional type (PFT) land cover dataset for Europe 2015 (Version 1.0) is a gridded, high-resolution dataset for use in regional climate models. LANDMATE PFT is prepared using the expertise of regional climate modellers all over Europe and is easily adjustable to fit into different climate model families. We provide comprehensive spatial quality information for LANDMATE PFT, which can be used to reduce uncertainty in regional climate model simulations.
Robert Pazúr, Nica Huber, Dominique Weber, Christian Ginzler, and Bronwyn Price
Earth Syst. Sci. Data, 14, 295–305, https://doi.org/10.5194/essd-14-295-2022, https://doi.org/10.5194/essd-14-295-2022, 2022
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We mapped the distribution of cropland and permanent grassland across Switzerland, where the agricultural land is considerably spatially heterogeneous due to strong variability in topography and climate, thus presenting challenges to mapping. The resulting map has high accuracy in lowlands as well as in mountainous areas. Thus, we believe that the presented mapping approach and resulting map will provide a solid ground for further research in agricultural land cover and landscape structure.
George Z. Xian, Kelcy Smith, Danika Wellington, Josephine Horton, Qiang Zhou, Congcong Li, Roger Auch, Jesslyn F. Brown, Zhe Zhu, and Ryan R. Reker
Earth Syst. Sci. Data, 14, 143–162, https://doi.org/10.5194/essd-14-143-2022, https://doi.org/10.5194/essd-14-143-2022, 2022
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Continuous change detection algorithms were implemented with time series satellite records to produce annual land surface change products for the conterminous United States. The land change products are in 30 m spatial resolution and represent land cover and change from 1985 to 2017 across the country. The LCMAP product suite provides useful information for land resource management and facilitates studies to improve the understanding of terrestrial ecosystems.
Audrey Jolivot, Valentine Lebourgeois, Louise Leroux, Mael Ameline, Valérie Andriamanga, Beatriz Bellón, Mathieu Castets, Arthur Crespin-Boucaud, Pierre Defourny, Santiana Diaz, Mohamadou Dieye, Stéphane Dupuy, Rodrigo Ferraz, Raffaele Gaetano, Marie Gely, Camille Jahel, Bertin Kabore, Camille Lelong, Guerric le Maire, Danny Lo Seen, Martha Muthoni, Babacar Ndao, Terry Newby, Cecília Lira Melo de Oliveira Santos, Eloise Rasoamalala, Margareth Simoes, Ibrahima Thiaw, Alice Timmermans, Annelise Tran, and Agnès Bégué
Earth Syst. Sci. Data, 13, 5951–5967, https://doi.org/10.5194/essd-13-5951-2021, https://doi.org/10.5194/essd-13-5951-2021, 2021
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This paper presents nine standardized crop type reference datasets collected between 2013 and 2020 in seven tropical countries. It aims at participating in the difficult exercise of mapping agricultural land use through satellite image classification in those complex areas where few ground truth or census data are available. These quality-controlled datasets were collected in the framework of the international JECAM initiative and contain 27 074 polygons documented by detailed keywords.
Jichong Han, Zhao Zhang, Yuchuan Luo, Juan Cao, Liangliang Zhang, Fei Cheng, Huimin Zhuang, Jing Zhang, and Fulu Tao
Earth Syst. Sci. Data, 13, 5969–5986, https://doi.org/10.5194/essd-13-5969-2021, https://doi.org/10.5194/essd-13-5969-2021, 2021
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The accurate planting area and spatial distribution information is the basis for ensuring food security at continental scales. We constructed a paddy rice map database in Southeast and Northeast Asia for 3 years (2017–2019) at a 10 m spatial resolution. There are fewer mixed pixels in our paddy rice map. The large-scale and high-resolution maps of paddy rice are useful for water resource management and yield monitoring.
David L. A. Gaveau, Adrià Descals, Mohammad A. Salim, Douglas Sheil, and Sean Sloan
Earth Syst. Sci. Data, 13, 5353–5368, https://doi.org/10.5194/essd-13-5353-2021, https://doi.org/10.5194/essd-13-5353-2021, 2021
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Severe burning struck Indonesia in 2019. Drawing on new satellite imagery, we present and validate new 2019 burned-area estimates for Indonesia.
We show that > 3.11 million hectares (Mha) burned in 2019, double the official estimate from the Indonesian Ministry of Environment and Forestry. Our relatively more accurate estimates have important implications for carbon-emission calculations from forest and peatland fires in Indonesia.
Qiaofeng Xue, Xiaobin Jin, Yinong Cheng, Xuhong Yang, and Yinkang Zhou
Earth Syst. Sci. Data, 13, 5071–5085, https://doi.org/10.5194/essd-13-5071-2021, https://doi.org/10.5194/essd-13-5071-2021, 2021
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We reconstructed the walled cities of China that extend from the 15th century to 19th century based on multiple historical documents. By restoring the extent of the city walls, it is helpful to explore the urban area in this period. The correlation and integration of the lifetime and the spatial data led to the creation of the China City Wall Areas Dataset (CCWAD). Based on the proximity to the time of most of the city walls, we produce the China Urban Extent Dataset (CUED) from CCWAD.
Miao Zhang, Bingfang Wu, Hongwei Zeng, Guojin He, Chong Liu, Shiqi Tao, Qi Zhang, Mohsen Nabil, Fuyou Tian, José Bofana, Awetahegn Niguse Beyene, Abdelrazek Elnashar, Nana Yan, Zhengdong Wang, and Yiliang Liu
Earth Syst. Sci. Data, 13, 4799–4817, https://doi.org/10.5194/essd-13-4799-2021, https://doi.org/10.5194/essd-13-4799-2021, 2021
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Cropping intensity (CI) is essential for agricultural land use management, but fine-resolution global CI is not available. We used multiple satellite data on Google Earth Engine to develop a first 30 m resolution global CI (GCI30). GCI30 performed well, with an overall accuracy of 92 %. GCI30 not only exhibited high agreement with existing CI products but also provided many spatial details. GCI30 can facilitate research on sustained cropland intensification to improve food production.
Louise Chini, George Hurtt, Ritvik Sahajpal, Steve Frolking, Kees Klein Goldewijk, Stephen Sitch, Raphael Ganzenmüller, Lei Ma, Lesley Ott, Julia Pongratz, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 4175–4189, https://doi.org/10.5194/essd-13-4175-2021, https://doi.org/10.5194/essd-13-4175-2021, 2021
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Carbon emissions from land-use change are a large and uncertain component of the global carbon cycle. The Land-Use Harmonization 2 (LUH2) dataset was developed as an input to carbon and climate simulations and has been updated annually for the Global Carbon Budget (GCB) assessments. Here we discuss the methodology for producing these annual LUH2 updates and describe the 2019 version which used new cropland and grazing land data inputs for the globally important region of Brazil.
Zoltan Szantoi, Andreas Brink, and Andrea Lupi
Earth Syst. Sci. Data, 13, 3767–3789, https://doi.org/10.5194/essd-13-3767-2021, https://doi.org/10.5194/essd-13-3767-2021, 2021
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The ever-evolving landscapes in the African, Caribbean and Pacific regions should be monitored for land cover changes. The Global Land Monitoring Service of the Copernicus Programme, and in particular the Hot Spot Monitoring activity, developed a satellite-imagery-based workflow to monitor such areas. Here, we present a total of 852 025 km2 of areas mapped with up to 32 land cover classes. Thematic land cover and land cover change maps, as well as validation datasets, are presented.
Zhen Yu, Xiaobin Jin, Lijuan Miao, and Xuhong Yang
Earth Syst. Sci. Data, 13, 3203–3218, https://doi.org/10.5194/essd-13-3203-2021, https://doi.org/10.5194/essd-13-3203-2021, 2021
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We reconstructed the annual, 5 km × 5 km resolution cropland percentage map that covers mainland China and spans from 1900 to 2016. Our results are advantageous, as they reconcile accuracy, temporal coverage, and spatial resolutions. We further examined the cropland shift pattern and its driving factors in China using the reconstructed maps. This work will greatly contribute to the field of global ecology and land surface modeling.
Xueqiong Wei, Mats Widgren, Beibei Li, Yu Ye, Xiuqi Fang, Chengpeng Zhang, and Tiexi Chen
Earth Syst. Sci. Data, 13, 3035–3056, https://doi.org/10.5194/essd-13-3035-2021, https://doi.org/10.5194/essd-13-3035-2021, 2021
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The cropland area of each administrative unit based on statistics in Scandinavia from 1690 to 1999 is allocated into 1 km grid cells. The cropland area increased from 1690 to 1950 and then decreasd in the following years, especially in southeastern Scandinavia. Comparing global datasets with this study, the spatial patterns show considerable differences. Our dataset is validated using satellite-based cropland cover data and results in previous studies.
Jichong Han, Zhao Zhang, Yuchuan Luo, Juan Cao, Liangliang Zhang, Jing Zhang, and Ziyue Li
Earth Syst. Sci. Data, 13, 2857–2874, https://doi.org/10.5194/essd-13-2857-2021, https://doi.org/10.5194/essd-13-2857-2021, 2021
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Large-scale and high-resolution maps of rapeseed are important for ensuring global energy security. We generated a new database for the rapeseed planting area (2017–2019) at 10 m spatial resolution based on multiple data. Also, we analyzed the rapeseed rotation patterns in 25 representative areas from different countries. The derived rapeseed maps are useful for many purposes including crop growth monitoring and production and optimizing planting structure.
Xiao Zhang, Liangyun Liu, Xidong Chen, Yuan Gao, Shuai Xie, and Jun Mi
Earth Syst. Sci. Data, 13, 2753–2776, https://doi.org/10.5194/essd-13-2753-2021, https://doi.org/10.5194/essd-13-2753-2021, 2021
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Over past decades, a lot of global land-cover products have been released; however, these still lack a global land-cover map with a fine classification system and spatial resolution simultaneously. In this study, a novel global 30 m landcover classification with a fine classification system for the year 2015 (GLC_FCS30-2015) was produced by combining time series of Landsat imagery and high-quality training data from the GSPECLib on the Google Earth Engine computing platform.
Bowen Cao, Le Yu, Victoria Naipal, Philippe Ciais, Wei Li, Yuanyuan Zhao, Wei Wei, Die Chen, Zhuang Liu, and Peng Gong
Earth Syst. Sci. Data, 13, 2437–2456, https://doi.org/10.5194/essd-13-2437-2021, https://doi.org/10.5194/essd-13-2437-2021, 2021
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In this study, the first 30 m resolution terrace map of China was developed through supervised pixel-based classification using multisource, multi-temporal data based on the Google Earth Engine platform. The classification performed well with an overall accuracy of 94 %. The terrace mapping algorithm can be used to map large-scale terraces in other regions globally, and the terrace map will be valuable for studies on soil erosion, carbon cycle, and ecosystem service assessments.
Dominik Kaim, Marcin Szwagrzyk, Monika Dobosz, Mateusz Troll, and Krzysztof Ostafin
Earth Syst. Sci. Data, 13, 1693–1709, https://doi.org/10.5194/essd-13-1693-2021, https://doi.org/10.5194/essd-13-1693-2021, 2021
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We present a dataset of mid-19th-century building structure locations in former Galicia and Austrian Silesia (parts of the Habsburg Monarchy), located in present-day Czechia, Poland, and Ukraine. It consists of two kinds of building structures: residential and farm-related buildings. The dataset may serve as an important input in studying long-term socio-economic processes and human–environmental interactions or as a valuable reference for continental settlement reconstructions.
Adrià Descals, Serge Wich, Erik Meijaard, David L. A. Gaveau, Stephen Peedell, and Zoltan Szantoi
Earth Syst. Sci. Data, 13, 1211–1231, https://doi.org/10.5194/essd-13-1211-2021, https://doi.org/10.5194/essd-13-1211-2021, 2021
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Decision-making for sustainable vegetable oil production requires accurate global oil crop maps. We used high-resolution satellite data to train a deep learning model that accurately classified industrial and smallholder oil palm, the main oil-producing crop. Our results outperformed previous studies and proved the suitability of deep learning for land use mapping. The global oil palm area was 21±0.42 Mha for 2019; however, young and sparse plantations were not included in this estimate.
Johannes H. Uhl, Stefan Leyk, Caitlin M. McShane, Anna E. Braswell, Dylan S. Connor, and Deborah Balk
Earth Syst. Sci. Data, 13, 119–153, https://doi.org/10.5194/essd-13-119-2021, https://doi.org/10.5194/essd-13-119-2021, 2021
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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.
Wenhui Kuang, Shu Zhang, Xiaoyong Li, and Dengsheng Lu
Earth Syst. Sci. Data, 13, 63–82, https://doi.org/10.5194/essd-13-63-2021, https://doi.org/10.5194/essd-13-63-2021, 2021
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We propose a hierarchical principle for remotely sensed urban land use and land cover change for mapping intra-urban structure and component dynamics. China’s Land Use/cover Dataset (CLUD) is updated, delineating the imperviousness and green surface conditions in cities from 2000 to 2018. The newly developed datasets can be used to enhance our understanding of urbanization impacts on ecological and regional climatic conditions and on urban dwellers' environments.
Qiangyi Yu, Liangzhi You, Ulrike Wood-Sichra, Yating Ru, Alison K. B. Joglekar, Steffen Fritz, Wei Xiong, Miao Lu, Wenbin Wu, and Peng Yang
Earth Syst. Sci. Data, 12, 3545–3572, https://doi.org/10.5194/essd-12-3545-2020, https://doi.org/10.5194/essd-12-3545-2020, 2020
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SPAM makes plausible estimates of crop distribution within disaggregated units. It moves the data from coarser units such as countries and provinces to finer units such as grid cells and creates a global gridscape at the confluence between earth and agricultural-production systems. It improves spatial understanding of crop production systems and allows policymakers to better target agricultural- and rural-development policies for increasing food security with minimal environmental impacts.
Jie Dong, Yangyang Fu, Jingjing Wang, Haifeng Tian, Shan Fu, Zheng Niu, Wei Han, Yi Zheng, Jianxi Huang, and Wenping Yuan
Earth Syst. Sci. Data, 12, 3081–3095, https://doi.org/10.5194/essd-12-3081-2020, https://doi.org/10.5194/essd-12-3081-2020, 2020
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For the first time, we produced a 30 m winter wheat distribution map in China for 3 years during 2016–2018. Validated with 33 776 survey samples, the map had perfect performance with an overall accuracy of 89.88 %. Moreover, the method can identify planting areas of winter wheat 3 months prior to harvest; that is valuable information for production predictions and is urgently necessary for policymakers to reduce economic loss and assess food security.
Zoltan Szantoi, Andreas Brink, Andrea Lupi, Claudio Mammone, and Gabriel Jaffrain
Earth Syst. Sci. Data, 12, 3001–3019, https://doi.org/10.5194/essd-12-3001-2020, https://doi.org/10.5194/essd-12-3001-2020, 2020
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Larger ecological zones and wildlife corridors in sub-Saharan Africa require monitoring, as social and economic demands put high pressure on them. Copernicus’ Hot-Spot Monitoring service developed a satellite-imagery-based monitoring workflow to map such areas. Here, we present a total of 560 442 km2 from which 153 665 km2 is mapped with eight land cover classes while 406 776 km2 is mapped with up to 32 classes. Besides presenting the thematic products, we also present our validation datasets.
Miao Lu, Wenbin Wu, Liangzhi You, Linda See, Steffen Fritz, Qiangyi Yu, Yanbing Wei, Di Chen, Peng Yang, and Bing Xue
Earth Syst. Sci. Data, 12, 1913–1928, https://doi.org/10.5194/essd-12-1913-2020, https://doi.org/10.5194/essd-12-1913-2020, 2020
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Global cropland distribution is critical for agricultural monitoring and food security. We propose a new Self-adapting Statistics Allocation Model (SASAM) to develop the global map of cropland distribution. SASAM is based on the fusion of multiple existing cropland maps and multilevel statistics of cropland area, which is independent of training samples. The synergy map has higher accuracy than the input datasets and better consistency with the cropland statistics.
Xiao Zhang, Liangyun Liu, Changshan Wu, Xidong Chen, Yuan Gao, Shuai Xie, and Bing Zhang
Earth Syst. Sci. Data, 12, 1625–1648, https://doi.org/10.5194/essd-12-1625-2020, https://doi.org/10.5194/essd-12-1625-2020, 2020
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The amount of impervious surface is an important indicator in the monitoring of the intensity of human activity and environmental change. In this study, a global 30 m impervious surface map was developed by using multisource, multitemporal remote sensing data based on the Google Earth Engine platform. The accuracy assessment indicated that the generated map had more optimal measurement accuracy compared with other state-of-art impervious surface products.
Cited articles
Allred, B. W., Smith, W. K., Tidwell, D., Haggerty, J. H., Running, S. W.,
Naugle, D. E., and Fuhlendorf, S. D.: Ecosystem services lost to oil and gas in
North America, Science, 348, 401–402, 2015.
Alonso, W.: A theory of the urban land market, Papers in Regional Science,
6, 149–157, 1960.
Baruch-Mordo, S., Kiesecker, J., Kennedy, C. M., Oakleaf, J. R., and Opperman,
J. J.: From Paris to practice: sustainable implementation of renewable energy
goals, Environ. Res. Lett., 14, 1–8, https://doi.org/10.1088/1748-9326/aaf6e0, 2019.
Bonham-Carter, G. F.: Geographic information systems for geoscientists:
modelling with GIS (Vol. 13), Elsevier, Tarrytown, New York, 1994.
Brown, M. T. and Vivas, M. B.: Landscape development intensity index,
Environ. Monitor. Assess., 101, 289–309, 2005.
Chaudhary, A. and Brooks, T. M.: Land use intensity-specific global
characterization factors to assess product biodiversity footprints,
Environ. Sci. Technol., 52, 5094–5104, 2018.
CIESIN: Global Rural-Urban
Mapping Project, Version 1 (GRUMPv1): Settlement Points, Revision 01,
Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC),
https://doi.org/10.7927/H4BC3WG1, 2017.
CIESIN: Gridded Population of the World, Version 4 (GPWv4):
Administrative Unit Center Points with Population Estimates, Revision 11,
Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC),
https://doi.org/10.7927/H4BC3WMT, 2018.
Corbane, C., Florczyk, A., Pesaresi, M., Politis, P., and Syrris, V.: GHS
built-up grid, derived from Landsat, multitemporal (1975–1990–2000–2014),
R2018A. European Commission, Joint Research Centre (JRC), https://doi.org/10.2905/jrc-ghsl-10007, 2018.
Costanza, J. K. and Terando, A. J.: Landscape Connectivity Planning for
Adaptation to Future Climate and Land-Use Change, Current Landscape Ecology Reports, 4, 1–13, 2019.
Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., van Aardenne, J. A., Monni, S., Doering, U., Olivier, J. G. J., Pagliari, V., and Janssens-Maenhout, G.: Gridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2, Earth Syst. Sci. Data, 10, 1987–2013, https://doi.org/10.5194/essd-10-1987-2018, 2018.
Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A., and Hansen, M. C.:
Classifying drivers of global forest loss, Science, 361, 1108–1111,
2018.
Delmas, R., Serca, D., and Jambert, C.: Global inventory of NOx sources,
Nutr. Cycl. Agroecosys., 48, 51–60, 1997.
Dinerstein, E., Olson, D., Joshi, A., Vynne, C., Burgess, N. D.,
Wikramanayake, E., Hahn, N., Palminteri, S., Hedao, P., Noss, R., and Hansen,
M.: An ecoregion-based approach to protecting half the terrestrial realm,
BioScience, 67, 534–545, 2017.
Dinerstein, E., Vynne, C., Sala, E., Joshi, A. R., Fernando, S., Lovejoy, T.
E., and Burgess, N. D.: A Global Deal For Nature: Guiding principles,
milestones, and targets, Sci. Adv., 5, eaaw2869, https://doi.org/10.1126/sciadv.aaw2869, 2019.
Doll, C. N.: CIESIN thematic guide to night-time light remote sensing and its applications. Center for International Earth Science Information Network of Columbia University, Palisades, NY, 2008.
Dunnett, S., Sorichetta, A., Taylor, G., and Eigenbrod, F.: Harmonised global datasets of wind and solar farm locations and power, Sci. Data, 7, 1–12, 2020.
Ellis, E.: Anthropocene: A very short introduction, Oxford University Press, Oxford, UK, 2018.
Ellis, E. C. and Ramankutty, N.: Putting people in the map: anthropogenic
biomes of the world, Front. Ecol. Environ., 6, 439–447,
2008.
Elvidge, C. D., Imhoff, M. L., and Baugh, K. E.: Night-time lights of the world:
1994–1995, ISPRS J. Photogramm. Remote S., 56, 81–99,
2001.
Elvidge, C., Ziskin, D., Baugh, K., Tuttle, B., Ghosh, T., Pack, D., Erwin,
E., and Zhizhin, M.: A Fifteen Year Record of Global Natural Gas Flaring Derived
from Satellite Data, Energies, 2, 595, https://doi.org/10.3390/en20300595, 2009.
Elvidge, C. D., Baugh, K. E., Zhizhin, M., and Hsu, F. C.: Why VIIRS data are
superior to DMSP for mapping nighttime lights, Proceedings of the
Asia-Pacific Advanced Network, 35, 62–69, 2013.
Elvidge, C., Zhizhin, M., Baugh, K., Hsu, F. C., and Ghosh, T.: Methods for
global survey of natural gas flaring from visible infrared imaging
radiometer suite data, Energies, 9, 14, https://doi.org/10.3390/en9010014, 2016.
ESA CCI: Land Cover CCI Product User Guide v2 (CCI-LC-PUGv2), Table 3–6, Universite catholique de Louvain, Louvain, Belgium,
2017.
Esteves, C. F., de Barros Ferraz, S. F., de Barros, K. M., Ferraz, M. G.,
and Theobald, D. M.: Human accessibility modelling applied to protected areas
management, Natureza Conservacao, 9, 232–923, 2011.
Gardner, R. H. and Urban, D. L.: Neutral models for testing landscape
hypotheses, Landscape Ecol., 22, 15–29, 2007.
Geldmann, J., Joppa, L. N., and Burgess, N. D.: Mapping change in human pressure
globally on land and within protected areas, Conserv. Biol., 28,
1604–1616, 2014.
Geldmann, J., Joppa, L., and Burgess, N. D.: Temporal Human Pressure Index, v2,
Dryad, Dataset, https://doi.org/10.5061/dryad.p8cz8w9kf, 2019a.
Geldmann, J., Manica, A., Burgess, N. D., Coad, L., and Balmford, A.: A
global-level assessment of the effectiveness of protected areas at resisting
anthropogenic pressures, P. Natl. Acad. Sci. USA,
116, 23209–23215, 2019b.
Gerber, P., Mooney, H. A., Dijkman, J., Tarawal, S., and De Haan, C.: Livestock
in a Changing Landscape, Volume 2: Experiences and Regional Perspectives, Island Press,
Washington, D.C., 2010.
Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S.
O., Wint, G. W., and Robinson, T. P.: Global distribution data for cattle,
buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010,
Sci. Data, 5, 180227, https://doi.org/10.1038/sdata.2018.227, 2018a.
Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S., Wint, W. G. R., and Robinson, T. P.: Global sheep distribution in 2010 (5 minutes of arc), Harvard Dataverse, V3, https://doi.org/10.7910/DVN/BLWPZN, 2018b.
Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S., Wint, W. G. R., and Robinson, T. P.: Global pigs distribution in 2010 (5 minutes of arc), Harvard Dataverse, V3, https://doi.org/10.7910/DVN/33N0JG, 2018c.
Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S., Wint, W. G. R., and Robinson, T. P.: Global horses distribution in 2010 (5 minutes of arc), Harvard Dataverse, V3, https://doi.org/10.7910/DVN/7Q52MV, 2018d.
Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S., Wint, W. G. R., and Robinson, T. P.: Global goats distribution in 2010 (5 minutes of arc), Harvard Dataverse, V3, https://doi.org/10.7910/DVN/OCPH42, 2018e.
Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S., Wint, W. G. R., and Robinson, T. P.: Global ducks distribution in 2010 (5 minutes of arc), Harvard Dataverse, V3, https://doi.org/10.7910/DVN/ICHCBH, 2018f.
Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S., Wint, W. G. R., and Robinson, T. P.: Global cattle distribution in 2010 (5 minutes of arc), Harvard Dataverse, V3, https://doi.org/10.7910/DVN/GIVQ75, 2018g.
Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S., Wint, W. G. R., and Robinson, T. P.: Global chickens distribution in 2010 (5 minutes of arc), Harvard Dataverse, V3, https://doi.org/10.7910/DVN/SUFASB, 2018h.
Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S., Wint, W. G. R., and Robinson, T. P.: Global buffaloes distribution in 2010 (5 minutes of arc), Harvard Dataverse, V3, https://doi.org/10.7910/DVN/5U8MWI, 2018i.
González-Abraham, C., Ezcurra, E., Garcillán, P. P., Ortega-Rubio,
A., Kolb, M., and Creel, J. E. B.: The human footprint in Mexico: physical
geography and historical legacies, PloS ONE, 10, e0121203, https://doi.org/10.1371/journal.pone.0121203, 2015.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R.:
Google Earth Engine: Planetary-scale geospatial analysis for everyone,
Remote Sens. Environ., 202, 18–27, 2017.
Grill, G., Lehner, B., Thieme, M., Geenen, B., Tickner, D., Antonelli, F.,
and Macedo, H. E.: Mapping the world's free-flowing rivers, Nature, 569,
215–221, 2019.
Haddad, N. M., Brudvig, L. A., Clobert, J., Davies, K. F., Gonzalez, A.,
Holt, R. D., and Cook, W. M.: Habitat fragmentation and its lasting impact on
Earth's ecosystems, Sci. Adv., 1, e1500052, https://doi.org/10.1126/sciadv.1500052, 2015.
Hajkowicz, S. and Collins, K.: A review of multiple criteria analysis for water
resource planning and management, Water Resour. Manage., 21,
1553–1566, 2007.
Halpern, B. S. and Fujita, R.: Assumptions, challenges, and future directions in
cumulative impact analysis, Ecosphere, 4, 1–11, 2013.
Halpern, B. S., Mcleod, K. L., Rosenberg, A. A., and Crowder, L. B.: Managing for
cumulative impacts in ecosystem-based management through ocean zoning, Ocean
Coast. Manage., 51, 203–211, 2008.
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A. A.,
Tyukavina, A., and Kommareddy, A.: High-resolution global maps of 21st-century
forest cover change, Science, 342, 850–853, 2013.
Hoekstra, J. M., Boucher, T. M., Ricketts, T. H., and Roberts, C.: Confronting a
biome crisis: global disparities of habitat loss and protection, Ecol.
Lett., 8, 23–29, 2005.
Hurtt, G. C., Frolking, S., Fearon, M. G., Moore, B., Shevliakova, E.,
Malyshev, S., Pacal, 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, Global Change Biol., 12,
1208–1229, https://doi.org/10.1111/j.1365-2486.2006.01150.x, 2006.
IPBES: Summary for policymakers of the global assessment report on
biodiversity and ecosystem services of the Intergovernmental Science-Policy
Platform on Biodiversity and Ecosystem Services, edited by: Díaz, S., Settele, J., Brondizio,
E. S., Ngo, H. T., Guèze, M., Agard, J., Arneth, A.,
Balvanera, P., Brauman, K. A., Butchart, S. H. M., Chan, K. M. A., Garibaldi, L. A., Ichii,
K., Liu, J., Subramanian, S. M., Midgley, G. F., Miloslavich, P.,
Molnár, Z., Obura, D., Pfaff, A., Polasky, S., Purvis, A., Razzaque, J.,
Reyers, B., Roy Chowdhury, R., Shin, Y. J., Visseren-Hamakers, I. J., Willis, K. J.,
and Zayas, C. N., IPBES secretariat, Bonn, Germany, 2019.
IPCC: Climate change and land: summary for policymakers, available at:
https://www.ipcc.ch/report/srccl/, last access: 21 November 2019.
Jacobson, A. P., Riggio, J., Tait, A., and Baillie, J.: Global areas of low human
impact (“Low Impact Areas”) and fragmentation of the natural world,
Sci. Rep.-UK, 9, 14179, https://doi.org/10.1038/s41598-019-50558-6, 2019.
Jantke, K., Kuempel, C. D., McGowan, J., Chauvenet, A. L., and Possingham, H. P.:
Metrics for evaluating representation target achievement in protected area
networks, Divers. Distrib., 25, 170–175, 2019.
Jordan, M., Meyer, W. B., Kates, R. W., Clark, W. C., Richards, J. F.,
Turner, B. L., and Mathews, J. T.: The earth as transformed by human action: global and regional changes in the biosphere over the past 300 years, CUP Archive, 1990.
Kehoe, L., Romero-Muñoz, A., Polaina, E., Estes, L., Kreft, H.,
and Kuemmerle, T.: Biodiversity at risk under future cropland expansion and
intensification, Nat. Ecol. Evol., 1, 1129, https://doi.org/10.1038/s41559-017-0234-3, 2017.
Kennedy, C. M., Oakleaf, J., Theobald, D. M., Baruch-Mordo, S., and Kiesecker, J.:
Global Human Modification, figshare, Dataset, https://doi.org/10.6084/m9.figshare.7283087.v1, 2018.
Kennedy, C. M., Oakleaf, J. R., Baruch-Mordo, S., Theobald, D. M., and
Kiesecker, J.: Finding middle ground: Extending conservation beyond
wilderness areas, Global Change Biol., 26, 333–336, https://doi.org/10.1111/gcb.14900, 2019a.
Kennedy, C. M., Oakleaf, J. R., Theobald, D. M., Baruch-Mordo, S., and Kiesecker,
J.: Managing the middle: A shift in conservation priorities based on the
global human modification gradient, Global Change Biol., 25, 811–826,
2019b.
Kennedy, C. M., Oakleaf, J. R., Theobald, D. M., Baruch-Mordo, S., and Kiesecker,
J.: Supplementary information for: Managing the middle: A shift in
conservation priorities based on the global human modification gradient,
Global Change Biol., 25, 811–826, 2019c.
Kiesecker, J., Baruch-Mordo, S., Kennedy, C. M., Oakleaf, J. R., Baccini, A.,
and Griscom, B. W.: Hitting the Target but Missing the Mark: Unintended
Environmental Consequences of the Paris Climate Agreement, Front. Environ. Sci., https://doi.org/10.3389/fenvs.2019.00151, 2019.
Klein Goldewijk, K., Van Drecht, G., and Bouwman, A. F.: Mapping contemporary
global cropland and grassland distributions on a 5×5 minute
resolution, J. Land Use Sci., 2, 167–190, 2007.
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.
Larson, C. L., Reed, S. E., Merenlender, A. M., and Crooks, K. R.: Accessibility
drives species exposure to recreation in a fragmented urban reserve network,
Landscape Urban Plan., 175, 62–71, 2018.
Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete,
B., Crouzet, P., and Nilsson, C.: High-resolution mapping of the world's
reservoirs and dams for sustainable river-flow management, Front.
Ecol. Environ., 9, 494–502, 2011.
Li, W., MacBean, N., Ciais, P., Defourny, P., Lamarche, C., Bontemps, S., Houghton, R. A., and Peng, S.: Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015), Earth Syst. Sci. Data, 10, 219–234, https://doi.org/10.5194/essd-10-219-2018, 2018.
Li, X. and Zhou, Y.: Urban mapping using DMSP/OLS stable night-time light: a
review, Int. J. Remote Sens., 38, 6030–6046, https://doi.org/10.1080/01431161.2016.1274451, 2017.
Mace, G. M., Barrett, M., Burgess, N. D., Cornell, S. E., Freeman, R.,
Grooten, M., and Purvis, A.: Aiming higher to bend the curve of
biodiversity loss, Nature Sustainability, 1, 448–451, 2018.
Malczewski, J.: GIS and multicriteria decision analysis, John Wiley &
Sons, New York, 1999.
Marsh, G. P.: The earth as modified by human action, C. Scribner's Sons, London,
1885.
McBride, M. F., Garnett, S. T., Szabo, J. K., Burbidge, A. H., Butchart, S.
H., Christidis, L., and Burgman, M. A.: Structured elicitation of expert
judgments for threatened species assessment: a case study on a continental
scale using email, Meth. Ecol. Evol., 3, 906–920, 2012.
Nelson, A.: Travel time to major cities: a global map of accessibility,
Report to: Global Environment Monitoring Unit, Joint Research Centre of the
European Commission, Aspra, Italy, 2008.
Nelson, A., Weiss, D. J., van Etten, J., Cattaneo, A., McMenomy, T. S., and Koo,
J.: A suite of global accessibility indicators, Sci. Data, 6, 1–9, 2019.
OpenStreetMap: OpenStreetMap, available at: http://www.openstreetmap.org, last access: 27 April 2019.
Parks, S. A., Carroll, C., Dobrowski, S. Z., and Allred, B. W.: Human land
uses reduce climate connectivity across North America, Global Change
Biol., 26, 2944–2955, 2020.
Pekel, J. F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution
mapping of global surface water and its long-term changes, Nature,
540, 418–422, https://doi.org/10.1038/nature20584, 2016.
Pérez-Hoyos, A., Rembold, F., Kerdiles, H., and Gallego, J.: Comparison
of global land cover datasets for cropland monitoring, Remote Sensing,
9, 1118, https://doi.org/10.3390/rs9111118, 2017.
Pesaresi, M., Ehrilch, D., Florczyk, A. J., Freire, S., Julea, A., Kemper,
T., Soille, P., and Syrris, V.: GHS built-up grid, derived from Landsat,
multitemporal (1975, 1990, 2000, 2015), European Commission, Joint Research
Centre, JRC Data Catalogue, Aspra, Italy, 2015.
Ramankutty, N., Evan, A. T., Monfreda, C., and Foley, J. A.: Farming the
planet: 1. Geographic distribution of global agricultural lands in the year
2000, Global Biogeochem. Cycles, 22, 1–19, https://doi.org/10.1029/2007GB002952, 2008.
R Core Team: R: A language and environment for statistical computing, R
Foundation for Statistical Computing, Vienna, Austria,
available at: https://www.R-project.org/, last access: 28 December 2019.
Riggio, J., Baillie, J. E. M., Brumby, S., Ellis, E., Kennedy, C. M., Oakleaf,
J. R., Tait, A., Tepe, T., Theobald, D. M., Venter, O., Watson, J. E. M.,
and Jacobson, A. P.: Global human influence maps reveal clear opportunities in
conserving Earth's remaining intact terrestrial ecosystems, Global Change
Biol., 26, 4344–4356, https://doi.org/10.1111/gcb.15109, 2020.
Riitters, K. H., Wickham, J. D., and Wade, T. G.: An indicator of forest
dynamics using a shifting landscape mosaic, Ecol. Indic., 9,
107–117, 2009.
Robinson, T. P., Wint, G. W., Conchedda, G., Van Boeckel, T. P., Ercoli, V.,
Palamara, E., and Gilbert, M.: Mapping the global distribution of livestock,
PloS one, 9, e96084, https://doi.org/10.1371/journal.pone.0096084, 2014.
Roszkowska, E.: Rank ordering criteria weighting methods – a comparative
overview, OPTIMUM. STUDIA EKONOMICZNE, 5, 14–33, 2013.
S&P: S&P Global Market Intelligence, Thomson Reuters, New York, United
States, 2018.
Salafsky, N., Salzer, D., Stattersfield, A. J., Hilton-Taylor, C.,
Neugarten, R., Butchart, S. H., and Wilkie, D.: A standard lexicon for
biodiversity conservation: unified classifications of threats and actions,
Conserv. Biol., 22, 897–911, 2008.
Sanderson, E. W., Jaiteh, M., Levy, M. A., Redford, K. H., Wannebo, A. V.,
and Woolmer, G.: The human footprint and the last of the wild, BioScience,
52, 891–904, 2002.
Schultz, M. T.: A critique of EPA's index of watershed indicators, J. Environ. Manage., 62,
429–442, 2001.
Secretariat of the Convention on Biological Diversity: Strategic plan for
biodiversity 2011–2020 and the Aichi targets, available at:
https://www.cbd.int/sp/targets/default.shtml (last access: 24 December 2018), 2010.
Theobald, D. M.: Reducing linear and perimeter measurement errors in
raster-based data, Cartogr. Geogr. Inf. Sc., 27,
111–116, 2000.
Theobald, D. M.: Network and accessibility methods to estimate the human use
of ecosystems, in: Proceedings of the 11th AGILE international conference on
geographic information science, University of Girona, Spain, 2008.
Theobald, D. M.: Estimating natural landscape changes from 1992 to 2030 in
the conterminous US, Landscape Ecol., 25, 999–1011, 2010.
Theobald, D. M.: A general model to quantify ecological integrity for
landscape assessments and US application, Landscape Ecol., 28,
1859–1874, 2013.
Theobald, D. M.: A general-purpose spatial survey design for collaborative
science and monitoring of global environmental change: the global grid,
Remote Sensing, 8, 813, https://doi.org/10.3390/rs8100813, 2016.
Theobald, D. M., Norman, J. B., and Newman, P.: Estimating visitor use of protected
areas by modeling accessibility: A case study in Rocky Mountain National
Park, Colorado, J. Conserv. Plan., 6, 1–20, 2010.
Theobald, D. M., Kennedy, C., Chen, B., Oakleaf, J., Baruch-Mordo, S., and Kiesecker, J.: Data for detailed temporal mapping of global human modification from 1990 to 2017 (Version v1) [Data set], Zenodo, https://doi.org/10.5281/zenodo.3963013, 2020.
Titeux, N., Henle, K., Mihoub, J. B., Regos, A., Geijzendorffer, I. R.,
Cramer, W., Verburg, P. H., and Brotons, L.: Biodiversity scenarios neglect
future land-use changes, Global Change Biol., 22, 2505–2515, 2016.
Tobler, W.: Non-isotropic geographic modeling, National Center for
Geographic Information and Analysis Technical Report TR-93-1, 1991.
Tulloch, V. J., Tulloch, A. I., Visconti, P., Halpern, B. S., Watson, J. E.,
Evans, M. C., and Giakoumi, S.: Why do we map threats? Linking threat mapping
with actions to make better conservation decisions, Front. Ecol.
Environ., 13, 91–99, 2015.
Valenta, R. K., Kemp, D., Owen, J. R., Corder, G. D., and Lèbre, É.:
Re-thinking complex orebodies: Consequences for the future world supply of
copper, J. Clean. Prod., 220, 816–826, 2019.
van Asselen, S. and Verburg, P. H.: A Land System representation for global
assessments and land-use modeling, Global Change Biol., 18, 3125–3148,
2012.
van Etten, A.: City-scale road extraction from satellite imagery,
arXiv:1904.09901v2 [cs.CV], 22 July 2019.
Venter, O., Sanderson, E. W., Magrach, A., Allan, J. R., Beher, J., Jones,
K. R., Possingham, H. P., Laurance, W. F., Wood, P., Fekete, B. M., Levy, M. A.,
Watson, J. E. M.: Global terrestrial Human Footprint maps for 1993
and 2009, Sci. Data, 3, 160067, https://doi.org/10.1038/sdata.2016.67, 2016.
Venter, O., Possingham, H. P., and Watson, J. E.: The human footprint
represents observable human pressures: Reply to Kennedy et al., Global Change Biol., 26,
330–332, 2019.
Verdone, M. and Seidl, A.: Time, space, place, and the Bonn Challenge global
forest restoration target, Restor. Ecol., 25, 903–911, 2017.
Vitousek, P. M., Mooney, H. A., Lubchenco, J., and Melillo, J. M.: Human
domination of Earth's ecosystems, Science, 277, 494–499, 1997.
Waldner, F., Fritz, S., Di Gregorio, A., Plotnikov, D., Bartalev, S.,
Kussul, N., and Löw, F.: A unified cropland layer at 250 m for global
agriculture monitoring, Data, 1, 3, https://doi.org/10.3390/data1010003, 2016.
Weiss, D. J., Nelson, A., Gibson, H. S., Temperley, W., Peedell, S., Lieber,
A., Hancher, M., Poyart, E., Belchior, S., Fullman, N., and Mappin, B.: A global
map of travel time to cities to assess inequalities in accessibility in
2015, Nature, 553, 333–336, https://doi.org/10.1038/nature25181, 2018.
Wickham, J., Stehman, S. V., Gass, L., Dewitz, J. A., Sorenson, D. G.,
Granneman, B. J., and Baer, L. A.: Thematic accuracy assessment of the 2011
national land cover database (NLCD), Remote Sens. Environ., 191,
328–341, 2017.
WRI: Global Energy Observatory, Google, KTH Royal Institute of Technology in
Stockholm, Enipedia, World Resources Institute, Global Power Plant Database,
Published on Resource Watch and Google Earth Engine, available at:
http://resourcewatch.org, last access: 14 April 2019.
Zhang, Q., Pandey, B., and Seto, K.C.: A robust method to generate a consistent
time series from DMSP/OLS nighttime light data, IEEE T.
Geosci. Remote, 54, 5821–5831, https://doi.org/10.1109/TGRS.2016.2572724, 2016.
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Short summary
We developed a global, high-resolution dataset and quantified recent rates of land transformation and current patterns of human modification for 2017, globally. Briefly, we found that increased human activities and land use modification have caused 1.6 × 106 km2 of natural land to be lost between 1990 and 2015 and the rate of loss has increased over that time. While troubling, we believe these findings are invaluable to underpinning global and national discussions of conservation priorities.
We developed a global, high-resolution dataset and quantified recent rates of land...
