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).
Highlights
A better understanding of global urban dynamics over the long term is crucial for sustainable development goals in a 30 changing world experiencing complex human-environment interactions (Li and Gong, 2016; Li et al, 2019; Zhu et al, 2019).With increased populations, intensified socioeconomic activities, spatially expanded built-up areas and infrastructures, and 1Data escalated industrial structures, such complex processes of urbanization worldwide are supposed to accelerate human-driven modifications of earth landscape and climate change from local, regional to global scales (Defries et al, 2002)
To further extend the applications of NTL observations for delineating, understanding, and predicting pathways of global urban growth associated with socioeconomic activities, as well as to better support future sustainable development, we generated a global dataset of annual urban extents from 1992 to 2020 using long-term and consistent nighttime lights
Through overlaying the derived urban boundaries on the impervious surface area (ISA) percentage maps, we found that our mapped urban results can reveal the spatial distribution of the contiguous areas with relatively high proportions of ISA
Summary
A better understanding of global urban dynamics over the long term is crucial for sustainable development goals in a 30 changing world experiencing complex human-environment interactions (Li and Gong, 2016; Li et al, 2019; Zhu et al, 2019). The characteristics of NTL spatial structures in potential urban domains have been demonstrated to help identify the ambiguous boundary between urban and surrounding non-urban areas, but previous studies were limited regarding spatial coverages or temporal periods The key of this type of method is to capture differences of NTL signals from rural areas to urban cores at local scales (Zhao et al, 2020b). A salient advantage of this framework is to map the urban extents over different spaces and time by effectively characterizing the diverse patterns of NTL spatial gradients at the local scales from urban to surrounding non-urban areas (Zhao et al, 2020b) Far, this approach has been initially applied to Southeast Asia for monitoring its annual urban extents (1992-2018), showing great potential in further applications for studies over 90 large regions and long periods. 110 urban mapping (Sect. 3), a discussion of the results and findings (Sect. 4), and conclusions (Sect. 5)
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