Articles | Volume 18, issue 7
https://doi.org/10.5194/essd-18-5329-2026
© Author(s) 2026. 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-18-5329-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Mapping three decades of urban growth in China: a 30 m annual building height dataset (1990–2019)
Yizhi Zhang
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
Yi Wang
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing, 100081, China
Innovation Center for FengYun Meteorological Satellite, Beijing, 100081, China
Xiao-Jian Chen
School of Public Affairs, Xiamen University, Xiamen, 361005, China
Fan Zhang
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
Xuecao Li
Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-Sen University, Guangzhou, 510275, China
Yu Liu
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIX-B2-2026, 559–567, https://doi.org/10.5194/isprs-archives-XLIX-B2-2026-559-2026, https://doi.org/10.5194/isprs-archives-XLIX-B2-2026-559-2026, 2026
Hanyu Yin, Fan Zhang, Yuqing Wang, Lun Wu, and Yu Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-345, https://doi.org/10.5194/essd-2026-345, 2026
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The exterior surfaces of buildings shape how cities use energy, store heat, and respond to disasters. However, this information is missing from most urban building datasets. BMAT fills this gap by mapping exterior wall materials for 22 million buildings in 73 cities from 147 million street-view images collected between 2007 and 2025. The open dataset, validated with 91 % accuracy, can support research on urban climate, energy use, planning, and disaster resilience.
Yanan Wen, Tuo Chen, Xuecao Li, Tiecheng Bai, Ke Yao, Liheng Zhong, Han Chen, Meiling Liu, Xieqin Huang, Shunlin Liang, Shuangxi Miao, and Jianxi Huang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-347, https://doi.org/10.5194/essd-2026-347, 2026
Preprint under review for ESSD
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We developed a new method to track winter wheat growth across the world from 2001 to 2020. Using satellite data, we produced high-resolution maps (1 km) that show exactly where and how much winter wheat was planted over the last two decades. The results proved to be highly accurate when compared against international agricultural records. As the first long-term, global view of its kind, this map series is a vital tool for scientists and policymakers working to eliminate hunger.
Hongquan Cheng, Mengqing Geng, Xuecao Li, Shijie Li, Min Zhao, Chen Lin, Jie Wang, Peng Gong, and Yuyu Zhou
Earth Syst. Sci. Data, 18, 3449–3479, https://doi.org/10.5194/essd-18-3449-2026, https://doi.org/10.5194/essd-18-3449-2026, 2026
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Monthly records of nighttime light are scarce, especially over long periods, yet they are vital for tracking short-term economic shifts and seasonal urban change. This study provides a temporally consistent global 500 m-resolution monthly VIIRS (Visible Infrared Imaging Radiometer Suite)-like nighttime light dataset (1992–2024). By combining DMSP (Defense Meteorological Satellite Program) and VIIRS through reconstruction and correction, a consistent long-term record is created. The dataset supports improved analysis of urban growth and economic activity worldwide.
Kaiqi Du, Guilong Xiao, Jianxi Huang, Xiaoyan Kang, Xuecao Li, Yelu Zeng, Quandi Niu, Haixiang Guan, and Jianjian Song
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-432, https://doi.org/10.5194/essd-2024-432, 2025
Manuscript not accepted for further review
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In this manuscript, we developed a 500-m spatial resolution monthly SIF dataset for the China region (CNSIF) from 2003 to 2022 based on high-resolution apparent reflectance and thermal infrared data. The comparison of CNSIF with tower-based SIF observations, tower-based GPP observations, MODIS GPP products, and other SIF datasets has validated CNSIF's ability to capture photosynthetic activity across different vegetation types and its potential for estimating carbon fluxes.
Yangzi Che, Xuecao Li, Xiaoping Liu, Yuhao Wang, Weilin Liao, Xianwei Zheng, Xucai Zhang, Xiaocong Xu, Qian Shi, Jiajun Zhu, Honghui Zhang, Hua Yuan, and Yongjiu Dai
Earth Syst. Sci. Data, 16, 5357–5374, https://doi.org/10.5194/essd-16-5357-2024, https://doi.org/10.5194/essd-16-5357-2024, 2024
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Most existing building height products are limited with respect to either spatial resolution or coverage, not to mention the spatial heterogeneity introduced by global building forms. Using Earth Observation (EO) datasets for 2020, we developed a global height dataset at the individual building scale. The dataset provides spatially explicit information on 3D building morphology, supporting both macro- and microanalysis of urban areas.
Wanru He, Xuecao Li, Yuyu Zhou, Zitong Shi, Guojiang Yu, Tengyun Hu, Yixuan Wang, Jianxi Huang, Tiecheng Bai, Zhongchang Sun, Xiaoping Liu, and Peng Gong
Earth Syst. Sci. Data, 15, 3623–3639, https://doi.org/10.5194/essd-15-3623-2023, https://doi.org/10.5194/essd-15-3623-2023, 2023
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Most existing global urban products with future projections were developed in urban and non-urban categories, which ignores the gradual change of urban development at the local scale. Using annual global urban extent data from 1985 to 2015, we forecasted global urban fractional changes under eight scenarios throughout 2100. The developed dataset can provide spatially explicit information on urban fractions at 1 km resolution, which helps support various urban studies (e.g., urban heat island).
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.
Quandi Niu, Xuecao Li, Jianxi Huang, Hai Huang, Xianda Huang, Wei Su, and Wenping Yuan
Earth Syst. Sci. Data, 14, 2851–2864, https://doi.org/10.5194/essd-14-2851-2022, https://doi.org/10.5194/essd-14-2851-2022, 2022
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In this paper we generated the first national maize phenology product with a fine spatial resolution (30 m) and a long temporal span (1985–2020) in China, using Landsat images. The derived phenological indicators agree with in situ observations and provide more spatial details than moderate resolution phenology products. The extracted maize phenology dataset can support precise yield estimation and deepen our understanding of the response of agroecosystem to global warming in the future.
Min Zhao, Changxiu Cheng, Yuyu Zhou, Xuecao Li, Shi Shen, and Changqing Song
Earth Syst. Sci. Data, 14, 517–534, https://doi.org/10.5194/essd-14-517-2022, https://doi.org/10.5194/essd-14-517-2022, 2022
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We generated a unique dataset of global annual urban extents (1992–2020) using consistent nighttime light observations and analyzed global urban dynamics over the past 3 decades. Evaluations using other urbanization-related ancillary data indicate that the derived urban areas are reliable for characterizing spatial extents associated with intensive human settlement and high-intensity socioeconomic activities. This dataset can provide unique information for studying urbanization and its impacts.
Bowen Cao, Le Yu, Xuecao Li, Min Chen, Xia Li, Pengyu Hao, and Peng Gong
Earth Syst. Sci. Data, 13, 5403–5421, https://doi.org/10.5194/essd-13-5403-2021, https://doi.org/10.5194/essd-13-5403-2021, 2021
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In the study, the first 1 km global cropland proportion dataset for 10 000 BCE–2100 CE was produced through the harmonization and downscaling framework. The mapping result coincides well with widely used datasets at present. With improved spatial resolution, our maps can better capture the cropland distribution details and spatial heterogeneity. The dataset will be valuable for long-term simulations and precise analyses. The framework can be extended to specific regions or other land use types.
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Short summary
China’s cities have transformed dramatically over the past 30 years. Using multi-source satellite data and machine learning, this study maps annual building heights at 30-meter detail from 1990 to 2019, revealing both horizontal and vertical urban growth. The open dataset offers new insights into how Chinese cities expand and renew, supporting research and planning for urban development.
China’s cities have transformed dramatically over the past 30 years. Using multi-source...
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