Preprints
https://doi.org/10.5194/essd-2021-302
https://doi.org/10.5194/essd-2021-302

  22 Oct 2021

22 Oct 2021

Review status: this preprint is currently under review for the journal ESSD.

A global dataset of annual urban extents (1992–2020) from harmonized nighttime lights

Min Zhao1,2,3, Changxiu Cheng1,2,3, Yuyu Zhou4, Xuecao Li5, Shi Shen1,2,3, and Changqing Song1,3 Min Zhao et al.
  • 1State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China
  • 2Key Laboratory of Environmental Change and Natural Disaster, Beijing Normal University, Beijing, 100875, China
  • 3Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • 4Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA, 50011, USA
  • 5College of Land Science and Technology, China Agricultural University, Beijing, 100083, China

Abstract. Understanding the spatiotemporal dynamics of global urbanization over a long time series is increasingly important for sustainable development goals. The harmonized time-series nighttime light (NTL) composites by fusing multi-source NTL observations provide a long and consistent record of the nightscape for characterizing and understanding the global urban dynamics. In this study, we generated a global dataset of annual urban extents (1992–2020) using consistent NTL observations and analyzed the spatiotemporal patterns of global urban dynamics over nearly 30 years. The urbanized areas associated with locally high-intensity human activities were mapped from the time-series global NTL imagery using a new stepwise-partitioning framework. This framework includes three components: (1) clustering of NTL signals to generate potential urban clusters; (2) identification of optimal thresholds to delineate annual urban extents; and (3) check of temporal consistency to correct pixel-level urban dynamics. We found that the global urban land area percentage to the Earth’s land surface raised from 0.22 % to 0.69 % in 1992 and 2020, respectively. Urban dynamics over the past three decades at the continent, country, and city levels exhibit various spatiotemporal patterns. Our resulting global urban extents (1992–2020) were evaluated using other urban remote sensing products and socioeconomic data. The evaluations indicate that this dataset is reliable for characterizing spatial extents associated with intensive human settlement and high-intensity socioeconomic activities. The dataset of global urban extents from this study can provide unique information to capture the historical and future trajectories of urbanization, and understand and tackle the urbanization impacts on food security, biodiversity, climate change, and public well-being and health. This dataset can be downloaded from https://doi.org/10.6084/m9.figshare.16602224.v1 (Zhao et al., 2021).

Min Zhao et al.

Status: open (until 17 Dec 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2021-302', Anonymous Referee #1, 01 Nov 2021 reply
  • RC2: 'Comment on essd-2021-302', Anonymous Referee #2, 02 Dec 2021 reply

Min Zhao et al.

Data sets

A global dataset of annual urban extents (1992-2020) from harmonized nighttime lights Min Zhao, Changxiu Cheng, Yuyu Zhou, Xuecao Li, Shi Shen, Changqing Song https://doi.org/10.6084/m9.figshare.16602224.v1

Min Zhao et al.

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Short summary
We generated a unique dataset of global annual urban extents (1992–2020) using consistent NTL observations and analyzed the global urban dynamics over the past three decades. The evaluations using other urbanization 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 studies on urbanization and its impacts.