Advanced search
1 file | 8.42 MB Add to list

Urban nighttime leisure space mapping with nighttime light images and POI data

(2020) REMOTE SENSING. 12(3).
Author
Abstract
Urban nighttime leisure spaces (UNLSs), important urban sites of nighttime economic activity, have created enormous economic and social benefits. Both the physical features (e.g., location, shape, and area) and the social functions (e.g., commercial streets, office buildings, and entertainment venues) of UNLSs are important in UNLS mapping. However, most studies rely solely on census data or nighttime light (NTL) images to map the physical features of UNLSs, which limits UNLS mapping, and few studies perform UNLS mapping from a social function perspective. Point-of-interest (POI) data, which can reflect social activity functions, are needed. As a result, a novel methodological UNLS mapping framework, that integrates NTL images and POI data is required. Consequently, we first extracted high-NTL intensity and high-POI density areas from composite data as areas with high nightlife activity levels. Then, the POI data were analyzed to identify the social functions of leisure spaces revealing that nighttime leisure activities are not abundant in Beijing overall, the total UNLS area in Beijing is 31.08 km(2), which accounts for only 0.2% of the total area of Beijing. In addition, the nightlife activities in the central urban area are more abundant than those in the suburbs. The main urban area has the largest UNLS area. Compared with the nightlife landmarks in Beijing established by the government, our results provide more details on the spatial pattern of nighttime leisure activities throughout the city. Our study aims to provide new insights into how multisource data can be leveraged for UNLS mapping to enable researchers to broaden their study scope. This investigation can also help government departments better understand the local nightlife situation to rationally formulate planning and adjustment measures.
Keywords
General Earth and Planetary Sciences

Downloads

  • remotesensing-12-00541-v2.pdf
    • full text (Published version)
    • |
    • open access
    • |
    • PDF
    • |
    • 8.42 MB

Citation

Please use this url to cite or link to this publication:

MLA
Liu, Jiping, et al. “Urban Nighttime Leisure Space Mapping with Nighttime Light Images and POI Data.” REMOTE SENSING, vol. 12, no. 3, 2020.
APA
Liu, J., Deng, Y., Wang, Y., Huang, H., Du, Q., & Ren, F. (2020). Urban nighttime leisure space mapping with nighttime light images and POI data. REMOTE SENSING, 12(3).
Chicago author-date
Liu, Jiping, Yue Deng, Yong Wang, Haosheng Huang, Qingyun Du, and Fu Ren. 2020. “Urban Nighttime Leisure Space Mapping with Nighttime Light Images and POI Data.” REMOTE SENSING 12 (3).
Chicago author-date (all authors)
Liu, Jiping, Yue Deng, Yong Wang, Haosheng Huang, Qingyun Du, and Fu Ren. 2020. “Urban Nighttime Leisure Space Mapping with Nighttime Light Images and POI Data.” REMOTE SENSING 12 (3).
Vancouver
1.
Liu J, Deng Y, Wang Y, Huang H, Du Q, Ren F. Urban nighttime leisure space mapping with nighttime light images and POI data. REMOTE SENSING. 2020;12(3).
IEEE
[1]
J. Liu, Y. Deng, Y. Wang, H. Huang, Q. Du, and F. Ren, “Urban nighttime leisure space mapping with nighttime light images and POI data,” REMOTE SENSING, vol. 12, no. 3, 2020.
@article{8656078,
  abstract     = {Urban nighttime leisure spaces (UNLSs), important urban sites of nighttime economic activity, have created enormous economic and social benefits. Both the physical features (e.g., location, shape, and area) and the social functions (e.g., commercial streets, office buildings, and entertainment venues) of UNLSs are important in UNLS mapping. However, most studies rely solely on census data or nighttime light (NTL) images to map the physical features of UNLSs, which limits UNLS mapping, and few studies perform UNLS mapping from a social function perspective. Point-of-interest (POI) data, which can reflect social activity functions, are needed. As a result, a novel methodological UNLS mapping framework, that integrates NTL images and POI data is required. Consequently, we first extracted high-NTL intensity and high-POI density areas from composite data as areas with high nightlife activity levels. Then, the POI data were analyzed to identify the social functions of leisure spaces revealing that nighttime leisure activities are not abundant in Beijing overall, the total UNLS area in Beijing is 31.08 km(2), which accounts for only 0.2% of the total area of Beijing. In addition, the nightlife activities in the central urban area are more abundant than those in the suburbs. The main urban area has the largest UNLS area. Compared with the nightlife landmarks in Beijing established by the government, our results provide more details on the spatial pattern of nighttime leisure activities throughout the city. Our study aims to provide new insights into how multisource data can be leveraged for UNLS mapping to enable researchers to broaden their study scope. This investigation can also help government departments better understand the local nightlife situation to rationally formulate planning and adjustment measures.},
  articleno    = {541},
  author       = {Liu, Jiping and Deng, Yue and Wang, Yong and Huang, Haosheng and Du, Qingyun and Ren, Fu},
  issn         = {2072-4292},
  journal      = {REMOTE SENSING},
  keywords     = {General Earth and Planetary Sciences},
  language     = {eng},
  number       = {3},
  pages        = {23},
  title        = {Urban nighttime leisure space mapping with nighttime light images and POI data},
  url          = {http://dx.doi.org/10.3390/rs12030541},
  volume       = {12},
  year         = {2020},
}

Altmetric
View in Altmetric
Web of Science
Times cited: