Chakraborty T C, Venter Zander S, Demuzere Matthias, Zhan Wenfeng, Gao Jing, Zhao Lei, Qian Yun
Atmospheric, Climate, and Earth Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Norwegian Institute for Nature Research - NINA, Oslo, Norway.
Nat Commun. 2024 Oct 24;15(1):9165. doi: 10.1038/s41467-024-52241-5.
Improvements in high-resolution satellite remote sensing and computational advancements have sped up the development of global datasets that delineate urban land, crucial for understanding climate risks in our increasingly urbanizing world. Here, we analyze urban land cover patterns across spatiotemporal scales from several such current-generation products. While all the datasets show a rapidly urbanizing world, with global urban land nearly tripling between 1985 and 2015, there are substantial discrepancies in urban land area estimates among the products influenced by scale, differing urban definitions, and methodologies. We discuss the implications of these discrepancies for several use cases, including for monitoring urban climate hazards and for modeling urbanization-induced impacts on weather and climate from regional to global scales. Our results demonstrate the importance of choosing fit-for-purpose datasets for examining specific aspects of historical, present, and future urbanization with implications for sustainable development, resource allocation, and quantification of climate impacts.
高分辨率卫星遥感技术的改进和计算能力的提升，加速了描绘城市土地的全球数据集的开发，这对于理解在日益城市化的世界中的气候风险至关重要。在此，我们分析了来自几种此类当代产品的跨时空尺度的城市土地覆盖模式。虽然所有数据集都显示出世界正在迅速城市化，1985年至2015年间全球城市土地面积几乎增加了两倍，但受尺度、不同城市定义和方法的影响，这些产品之间在城市土地面积估计上存在重大差异。我们讨论了这些差异对几个应用案例的影响，包括监测城市气候灾害以及模拟从区域到全球尺度城市化对天气和气候的影响。我们的结果表明，选择适合目的的数据集对于研究历史、当前和未来城市化的特定方面具有重要意义，这对可持续发展、资源分配和气候影响量化都有影响。
