Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-517-2022
© Author(s) 2022. 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-14-517-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
08 Feb 2022
Data description paper |
| 08 Feb 2022
| 08 Feb 2022
A global dataset of annual urban extents (1992–2020) from harmonized nighttime lights
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Beijing Normal University, Beijing, 100875, China
Key Laboratory of Environmental Change and Natural Disaster, Beijing
Normal University, Beijing, 100875, China
Center for Geodata and Analysis, Faculty of Geographical Science,
Beijing Normal University, Beijing, 100875, China
Changxiu Cheng
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Beijing Normal University, Beijing, 100875, China
Key Laboratory of Environmental Change and Natural Disaster, Beijing
Normal University, Beijing, 100875, China
Center for Geodata and Analysis, Faculty of Geographical Science,
Beijing Normal University, Beijing, 100875, China
Department of Geological and Atmospheric Sciences, Iowa State
University, Ames, IA 50011, USA
Xuecao Li
College of Land Science and Technology, China Agricultural
University, Beijing, 100083, China
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Beijing Normal University, Beijing, 100875, China
Key Laboratory of Environmental Change and Natural Disaster, Beijing
Normal University, Beijing, 100875, China
Center for Geodata and Analysis, Faculty of Geographical Science,
Beijing Normal University, Beijing, 100875, China
Changqing Song
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Beijing Normal University, Beijing, 100875, China
Center for Geodata and Analysis, Faculty of Geographical Science,
Beijing Normal University, Beijing, 100875, China
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Yangzi Che, Xuecao Li, Xiaoping Liu, Yuhao Wang, Weilin Liao, Xianwei Zheng, Xucai Zhang, Xiaocong Xu, Qian Shi, Jiajun Zhu, Hua Yuan, and Yongjiu Dai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-217, https://doi.org/10.5194/essd-2024-217, 2024
Revised manuscript accepted for ESSD
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Given the limited coverage or spatial resolution of existing datasets, we develop the first global building height map (3D-GloBFP) at the building footprint scale using Earth observation datasets and advanced machine learning techniques. Our map reveals the complex 3-D morphology of the world's building heights at a finer scale and provides reliable results (i.e., R2: 0.66–0.96, RMSEs: 1.9 m–14.6 m) over global regions 3D-GloBFP has great potential to support both macro- and micro-urban analysis
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).
Tao Zhang, Yuyu Zhou, Kaiguang Zhao, Zhengyuan Zhu, Gang Chen, Jia Hu, and Li Wang
Earth Syst. Sci. Data, 14, 5637–5649, https://doi.org/10.5194/essd-14-5637-2022, https://doi.org/10.5194/essd-14-5637-2022, 2022
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We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
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.
Peichao Gao, Yifan Gao, Xiaodan Zhang, Sijing Ye, and Changqing Song
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-123, https://doi.org/10.5194/gmd-2022-123, 2022
Revised manuscript not accepted
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We found that the featured function of CLUMondo – balancing demands and supplies in a many-to-many mode – relies on a parameter called conversion order, but the setting of this parameter should be improved. This parameter should be set manually according to the characteristics of each study area and based on expert knowledge, which is not feasible for users without understanding the whole, detailed mechanism. This problem has been addressed in this study with CLUMondo Version 2.0.
Tao Zhang, Yuyu Zhou, Zhengyuan Zhu, Xiaoma Li, and Ghassem R. Asrar
Earth Syst. Sci. Data, 14, 651–664, https://doi.org/10.5194/essd-14-651-2022, https://doi.org/10.5194/essd-14-651-2022, 2022
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We generated a global seamless 1 km daily (mid-daytime and mid-nighttime) land surface temperature (LST) dataset (2003–2020) using MODIS LST products by proposing a spatiotemporal gap-filling framework. The average root mean squared errors of the gap-filled LST are 1.88°C and 1.33°C, respectively, in mid-daytime and mid-nighttime. The global seamless LST dataset is unique and of great use in studies on urban systems, climate research and modeling, and terrestrial ecosystem studies.
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.
Zuoqi Chen, Bailang Yu, Chengshu Yang, Yuyu Zhou, Shenjun Yao, Xingjian Qian, Congxiao Wang, Bin Wu, and Jianping Wu
Earth Syst. Sci. Data, 13, 889–906, https://doi.org/10.5194/essd-13-889-2021, https://doi.org/10.5194/essd-13-889-2021, 2021
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An extended time series (2000–2018) of NPP-VIIRS-like nighttime light (NTL) data was proposed through a cross-sensor calibration from DMSP-OLS NTL data (2000–2012) and NPP-VIIRS NTL data (2013–2018). Compared with the annual composited NPP-VIIRS NTL data, our extended NPP-VIIRS-like NTL data have a high accuracy and also show a good spatial pattern and temporal consistency. It could be a useful proxy to monitor the dynamics of urbanization for a longer time period compared to existing NTL data.
Chun Hui, Changxiu Cheng, Shi Shen, Peichao Gao, Jin Chen, Jing Yang, and Min Zhao
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-21, https://doi.org/10.5194/nhess-2021-21, 2021
Preprint withdrawn
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This article quantify the effect of the Wenchuan MS 8.0 and Lushan MS 7.0 earthquakes on the size distribution of earthquakes along the Longmenshan fault. The results depict the decreasing trends of b values before the two large earthquakes in the study region. The major aftershock active periods of the Wenchuan MS 8.0 and Lushan MS 7.0 earthquakes were less than one year and ten months. Moreover, both large earthquakes do not change the pattern of
high in the north, low in the south.
Xuecao Li, Yuyu Zhou, Zhengyuan Zhu, and Wenting Cao
Earth Syst. Sci. Data, 12, 357–371, https://doi.org/10.5194/essd-12-357-2020, https://doi.org/10.5194/essd-12-357-2020, 2020
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The information of urban dynamics with fine spatial and temporal resolutions is highly needed in urban studies. In this study, we generated a long-term (1985–2015), fine-resolution (30 m) product of annual urban extent dynamics in the conterminous United States using all available Landsat images on the Google Earth Engine (GEE) platform. The data product is of great use for relevant studies such as urban growth projection, urban sprawl modeling, and urbanization impacts on environments.
Xuecao Li, Yuyu Zhou, Lin Meng, Ghassem R. Asrar, Chaoqun Lu, and Qiusheng Wu
Earth Syst. Sci. Data, 11, 881–894, https://doi.org/10.5194/essd-11-881-2019, https://doi.org/10.5194/essd-11-881-2019, 2019
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We generated a long-term (1985–2015) and medium-resolution (30 m) product of phenology indicators in urban domains in the conterminous US using Landsat satellite observations. The derived phenology indicators agree well with in situ observations and provide more spatial details in complex urban areas compared to the existing coarse resolution phenology products (e.g., MODIS). The published data are of great use for urban phenology studies (e.g., pollen-induced respiratory allergies).
Jianyu Liu, Qiang Zhang, Vijay P. Singh, Changqing Song, Yongqiang Zhang, Peng Sun, and Xihui Gu
Hydrol. Earth Syst. Sci., 22, 4047–4060, https://doi.org/10.5194/hess-22-4047-2018, https://doi.org/10.5194/hess-22-4047-2018, 2018
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Considering effective precipitation (Pe), the Budyko framework was extended to the annual water balance analysis. To reflect the mismatch between water supply (precipitation, P) and energy (potential evapotranspiration,
E0), a climate seasonality and asynchrony index (SAI) were proposed in terms of both phase and amplitude mismatch between P and E0.
Related subject area
Antroposphere – Urban Environment
The Bellinge data set: open data and models for community-wide urban drainage systems research
An extended time series (2000–2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration
Agnethe Nedergaard Pedersen, Jonas Wied Pedersen, Antonio Vigueras-Rodriguez, Annette Brink-Kjær, Morten Borup, and Peter Steen Mikkelsen
Earth Syst. Sci. Data, 13, 4779–4798, https://doi.org/10.5194/essd-13-4779-2021, https://doi.org/10.5194/essd-13-4779-2021, 2021
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A comprehensive data set from a combined sewer system in a 1.7 km2 suburban area is presented. Up to 10 years of observations (2010–2020) from level sensors, a flow meter, position and power sensors, rain gauges, X- and C-band weather radars, and a weather station; distributed hydrodynamic models; and CCTV pipe network data are included. This will enable independent testing and replication of results from future scientific developments within urban hydrology and urban drainage system research.
Zuoqi Chen, Bailang Yu, Chengshu Yang, Yuyu Zhou, Shenjun Yao, Xingjian Qian, Congxiao Wang, Bin Wu, and Jianping Wu
Earth Syst. Sci. Data, 13, 889–906, https://doi.org/10.5194/essd-13-889-2021, https://doi.org/10.5194/essd-13-889-2021, 2021
Short summary
Short summary
An extended time series (2000–2018) of NPP-VIIRS-like nighttime light (NTL) data was proposed through a cross-sensor calibration from DMSP-OLS NTL data (2000–2012) and NPP-VIIRS NTL data (2013–2018). Compared with the annual composited NPP-VIIRS NTL data, our extended NPP-VIIRS-like NTL data have a high accuracy and also show a good spatial pattern and temporal consistency. It could be a useful proxy to monitor the dynamics of urbanization for a longer time period compared to existing NTL data.
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Short summary
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.
We generated a unique dataset of global annual urban extents (1992–2020) using consistent...
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