Earth System Science Data (Aug 2023)

Global urban fractional changes at a 1 km resolution throughout 2100 under eight scenarios of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs)

  • W. He,
  • X. Li,
  • X. Li,
  • Y. Zhou,
  • Y. Zhou,
  • Z. Shi,
  • G. Yu,
  • T. Hu,
  • Y. Wang,
  • J. Huang,
  • J. Huang,
  • T. Bai,
  • Z. Sun,
  • X. Liu,
  • P. Gong,
  • P. Gong

DOI
https://doi.org/10.5194/essd-15-3623-2023
Journal volume & issue
Vol. 15
pp. 3623 – 3639

Abstract

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The information of global spatially explicit urban extents under scenarios is important to mitigate future environmental risks caused by global urbanization and climate change. Although future dynamics of urban extent were commonly modeled with conversion from non-urban to urban extent using cellular-automata (CA)-based models, gradual changes of impervious surface area (ISA) at the pixel level were limitedly explored in previous studies. In this paper, we developed a global dataset of urban fractional changes at a 1 km resolution from 2020 to 2100 (5-year interval), under eight scenarios of socioeconomic pathways and climate change. First, to quantify the gradual change of ISA within the pixel, we characterized ISA growth patterns over the past decades (i.e., 1985–2015) using a sigmoid growth model and annual global artificial impervious area (GAIA) data. Then, by incorporating the ISA-based growth mechanism with the CA model, we calibrated the state-specific urban CA model with quantitative evaluation at the global scale. Finally, we projected future urban fractional changes at 1 km resolution under eight development pathways based on the harmonized urban growth demand from Land Use Harmonization2 (LUH2). The evaluation results show that the ISA-based urban CA model performs well globally, with an overall R2 of 0.9 and a root mean square error (RMSE) of 0.08 between modeled and observed ISAs in 2015. With the inclusion of temporal contexts of urban sprawl gained from GAIA, the dataset of global urban fractional change shows good agreement with 30-year historical observations from satellites. The dataset can capture spatially explicit variations of ISA and gradual ISA change within pixels. The dataset of global urban fractional change is of great use in supporting quantitative analysis of urbanization-induced ecological and environmental change at a fine scale, such as urban heat islands, energy consumption, and human–nature interactions in the urban system. The developed dataset of global urban fractional change is available at https://doi.org/10.6084/m9.figshare.20391117.v4 (He et al., 2022).