School of Geographical Sciences, East China Normal University, Shanghai, 200241, China; Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, 47907, USA.
Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, 47907, USA.
J Environ Manage. 2021 Jul 1;289:112574. doi: 10.1016/j.jenvman.2021.112574. Epub 2021 Apr 14.
An accurate and efficient extraction of urban extent is important for understanding the dynamics of urban expansion process and for sustainable planning and management of cities. We proposed an improved dynamic nightlight threshold method to model urban extent and to reveal the spatiotemporal dynamics and driving forces of urban expansion. Differing from previous studies, we correct the blooming and over-saturation problems of nighttime light (NTL), and highlight a combination of NTL with urban population data for determining a yearly-continued and city-class-wide threshold for urban mapping. China is selected as a case study area to test the improved method and to gain insights to its urban expansion process. Through the validation, our method has been proven to be more accurate than the traditional NTL threshold method. Accordingly, the yearly-continued NTL data can better describe the changing patterns and driving forces of urban expansion than the yearly-discontinued land use and land cover data do. It is found that the total urban area in China has more than quadrupled from 25.2 in 1992 to 108.2 thousand km in 2013. Some significant pulses of urban expansion have been detected in our study, which may be attributed to the policy and socioeconomic impacts. Moreover, the panel regression based on annual NTL data indicates that GDP is a more important driver of urban expansion than urban population.
准确高效地提取城市范围对于理解城市扩张过程的动态以及城市的可持续规划和管理非常重要。我们提出了一种改进的动态夜光阈值方法来模拟城市范围，并揭示城市扩张的时空动态和驱动因素。与以往的研究不同，我们纠正了夜间灯光（NTL）的绽放和过饱和问题，并强调将 NTL 与城市人口数据相结合，以确定用于城市制图的逐年连续和全市范围的阈值。选择中国作为案例研究区来测试改进的方法，并深入了解其城市扩张过程。通过验证，我们的方法被证明比传统的 NTL 阈值方法更准确。因此，逐年连续的 NTL 数据比逐年不连续的土地利用和土地覆盖数据更能描述城市扩张的变化模式和驱动因素。研究发现，中国的城市总面积从 1992 年的 25.2 千平方公里增加到 2013 年的 108.2 千平方公里，增长了四倍多。我们的研究中检测到了一些明显的城市扩张脉冲，这可能归因于政策和社会经济影响。此外，基于年度 NTL 数据的面板回归表明，GDP 是城市扩张的一个比城市人口更重要的驱动因素。
