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

[摘要] Understanding the spatiotemporal dynamics of globalurbanization over a long time series is increasingly important forsustainable development goals. The harmonized nighttime light(NTL) time-series composites created by fusing multi-source NTL observations provide a long andconsistent record of the nightscape for characterizing and understanding global urban dynamics. In this study, we generated a global dataset ofannual urban extents (1992–2020) using consistent NTL observations andanalyzed the spatiotemporal patterns of global urban dynamics over nearly 30 years. The urbanized areas associated with locally high intensity humanactivities were mapped from the global NTL time-series imagery using a newstepwise-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. Wefound that the global urban land area percentage of the Earth's land surfacerose from 0.22 % to 0.69 % between 1992 and 2020. Urbandynamics over the past 3 decades at the continent, country, and citylevels exhibit various spatiotemporal patterns. Our resulting global urbanextents (1992–2020) were evaluated using other urban remote sensing productsand socioeconomic data. The evaluations indicate that this dataset isreliable for characterizing spatial extents associated with intensive humansettlement and high-intensity socioeconomic activities. The dataset ofglobal urban extents from this study can provide unique information tocapture the historical and future trajectories of urbanization and tounderstand and tackle urbanization impacts on food security,biodiversity, climate change, and public well-being and health. This datasetcan be downloaded from https://doi.org/10.6084/m9.figshare.16602224.v1 (Zhao et al., 2021).

[学科分类] 眼科学