Identification of Polycentric Cities in China Based on NPP-VIIRS Nighttime Light Data

Abstract

Nighttime light data play an important role in the research on cities, while the urban centers over a large spatial scale are still far from clearly understood. Aiming at the current challenges in monitoring the spatial structure of cities using nighttime light data, this paper proposes a new method for identifying urban centers for massive cities at the large spatial scale based on the brightness information captured by the Suomi National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) sensor. Based on the method for extracting the peak point based on digital elevation model (DEM) data in terrain analysis, the maximum neighborhood and difference algorithms were applied to the NPP-VIIRS data to extract the pixels with the peak nighttime light intensity to identify the potential locations of urban centers. The results show 7239 urban centers in 2200 cities in China in 2017, with an average of 3.3 urban centers per city. Approximately 68% of the cities had significant polycentric structures. The developed method in this paper is useful for identifying the urban centers and can provide the reference to the city planning and construction.

Spatio-Temporal Evolution and Driving Mechanism of Urbanization in Small Cities: Case Study from Guangxi

“…The areas with greater intensity of (brighter) night lighting show more frequent human production (intensity of economic behavior) and living (concentration of population) activities, and higher quality of urbanization development in general [53,54]. Now the night light data are widely used for the identification of urban built-up areas [55] and urban centers [56,57], the extraction of urban impervious surfaces [58], and the evaluation of urban spatial expansion and growth trend [59,60], land use and cover changes [61,62], Spatial estimation of socio-economic indicators [63], major events [64], ecological environment [65] and other fields [66], which are still in their infancy in the urbanization process research.…”

The Classification and Regulation of Mountain Villages in the Context of Rural Revitalization—The Example of Zhaotong, Yunnan Province

“…The data covered in this paper mainly include nighttime light remote sensing data, various land use data, geological disaster data, DEM data, earthquake data, POI data, administrative division data at all levels and other geographic information data. The NPP/VIIRS night light remote sensing data come from the academic department of Corolla University of Mines (https://payneinstitute.mines.edu/eog/) (accessed on 15 March 2022), which has been widely used in various studies [36] and was resampled to 30 m in this study. All kinds of land use data, including urban development boundaries, ecological protection zones, industrial land, urban and village roads, etc., as well as historical records of geological disasters and administrative divisions at all levels are all from the land and resources department.…”

Spatiotemporal Characteristics of Urban Land Expansion and Population Growth in Africa from 2001 to 2019: Evidence from Population Density Data

“…There are five classification schemes included in the land cover products MCD12Q1, of which the International Geosphere-Biosphere Programme (IGBP) is the most widely used [34]. In this study, the IGBP classification scheme was adopted to extract land-use types, which were reclassified into seven types, namely, forest, grassland, built-up land, cropland, barren land, water, and other.…”