4.7 Article

Very high-resolution remote sensing-based mapping of urban residential districts to help combat COVID-19

Journal

CITIES
Volume 126, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.cities.2022.103696

Keywords

COVID-19; Very high-resolution remote sensing images; Urban residential district; Healthy city planning

Categories

Funding

  1. Program for Innovative Research Team (in Science and Technology) in University of Henan Province [NSFC42071267]
  2. Scientific and technological research projects in Henan Province [21IRTSTHN008]
  3. [222102320472]

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Urban residential districts (URDs) are a crucial element in urban planning, particularly in the context of COVID-19 prevention. This study utilizes high-resolution remote sensing images to map and evaluate the ventilation capacity of URDs in a typical city in northern China. The results highlight that well-designed URDs have almost double the ventilation capacity compared to poorly designed ones, and there is significant variation in ventilation capacity within URDs. Therefore, high-resolution remote sensing data plays a vital role in precise urban planning.
Urban residential districts (URDs) are a major element in the formation of cities that are essential for urban planning. Regarding the COVID-19 virus, which remains variable in aerosols for several hours, airborne transmission tends to occur in areas of poor ventilation and high occupant density. Thus, ventilation capacity is an important factor influencing airborne transmission in URDs, which should be evaluated as part of efforts to fight COVID-19 and guide healthy city planning and implementation. Here, we develop and test systematic methods to map URDs in a typical city in northern China and quantify their ventilation capacity using very high-resolution remote sensing images. Four fundamental spatial forms of URD are identified in the research area: the point group form, parallel form, enclosed form, and hybrid form. Our analyses indicate that the integrated ventilation capacities for well-designed URDs are nearly twice those of poorly designed URDs. Large variations in ventilation capacity are also observed within URDs, with up to 13.42 times difference between the buildings. Therefore, very high-resolution remote sensing data are fundamental for extracting building height and generating precise spatial forms, which can improve the micro-scale URD ventilation planning for the prevention of COVID-19.

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