A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Identification of urban shrinkage using NPP-VIIRS nighttime light data at the county level in China
Abstract Urban shrinkage, as a global socioeconomic issue, has raised the attention of many geographers and urban planners. However, researches on urban shrinkage have mainly focused on case studies of individual cities, and there is a lack of research on shrinking city groups. Here we use nighttime light (NTL) data obtained by the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar Orbiting Partnership (NPP) to build a framework for identifying shrinking cities, and take the county-level cities in China as a case. Then, it explores the urban scale, function, and traffic conditions of China's shrinking cities and analyzes the impact of these three fundamental factors to urban shrinkage. Therefore, we can understand the relationship between shrinking cities from a regional perspective. The results of the research show the following: (1) the method of using NTL data to identify shrinking cities is reasonable and effective; (2) 20.3% of county-level cities in China have experienced urban shrinkage and the distribution of shrinking cities is dominated by low-low cluster; (3) The smaller the size of the city, the lower level of the urban function and the worse the traffic conditions, the easier it is for the city to shrink.
Highlights Using Nighttime Light Data to identify the shrinking cities at the County Level in China 20.3% of county-level cities have experienced urban shrinkage The smaller the size of the city, the easier it is for the city to shrink. Resource-based cities and processing-oriented cities are more likely to shrink The worse the traffic conditions, the easier it is for the city to shrink
Identification of urban shrinkage using NPP-VIIRS nighttime light data at the county level in China
Abstract Urban shrinkage, as a global socioeconomic issue, has raised the attention of many geographers and urban planners. However, researches on urban shrinkage have mainly focused on case studies of individual cities, and there is a lack of research on shrinking city groups. Here we use nighttime light (NTL) data obtained by the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar Orbiting Partnership (NPP) to build a framework for identifying shrinking cities, and take the county-level cities in China as a case. Then, it explores the urban scale, function, and traffic conditions of China's shrinking cities and analyzes the impact of these three fundamental factors to urban shrinkage. Therefore, we can understand the relationship between shrinking cities from a regional perspective. The results of the research show the following: (1) the method of using NTL data to identify shrinking cities is reasonable and effective; (2) 20.3% of county-level cities in China have experienced urban shrinkage and the distribution of shrinking cities is dominated by low-low cluster; (3) The smaller the size of the city, the lower level of the urban function and the worse the traffic conditions, the easier it is for the city to shrink.
Highlights Using Nighttime Light Data to identify the shrinking cities at the County Level in China 20.3% of county-level cities have experienced urban shrinkage The smaller the size of the city, the easier it is for the city to shrink. Resource-based cities and processing-oriented cities are more likely to shrink The worse the traffic conditions, the easier it is for the city to shrink
Identification of urban shrinkage using NPP-VIIRS nighttime light data at the county level in China
Zhou, Ying (author) / Li, Chenggu (author) / Zheng, Wensheng (author) / Rong, Yuefang (author) / Liu, Wei (author)
Cities ; 118
2021-07-21
Article (Journal)
Electronic Resource
English
A global analysis of factors controlling VIIRS nighttime light levels from densely populated areas
| Online Contents | 2017