4.7 Article

Quantitative Evaluation of Urban Expansion using NPP-VIIRS Nighttime Light and Landsat Spectral Data

Journal

SUSTAINABLE CITIES AND SOCIETY
Volume 76, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scs.2021.103338

Keywords

NPP-VIIRS nighttime light; Landsat imaging; Guangdong-Hong Kong-Macao Greater Bay; Area; Urban expansion; Quantitative assessment; Agglomeration effects

Funding

  1. Strategic Priority Research Program (A) of the Chinese Academy of Sciences [XDA23030103, XDA23030105]
  2. National Key Research and Development Program of China [2016YFC0501101]

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The study developed the ENUI to assess urban expansion in the GBA, revealing a circular and radial expansion pattern, stronger development potential in sub-central cities, and a continuous dispersion trend in spatial expansion.
Quantifying the evolution of urban expansion is of vital importance for optimizing land use patterns and promoting sustainable urban development. This research constructed the Enhanced Nighttime Light Urban Index (ENUI), which combines NPP-VIIRS nighttime light with Landsat spectral data, and used this index for quantitative evaluation of urban expansion in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) urban agglomeration. The results showed that, between 2012 and 2018, (1) the extraction using the ENUI achieved overall accuracy of 0.93-0.94, producer's accuracy in urban areas of 0.82-0.84, user's accuracy in urban areas 0.73-0.75, and Kappa values of 0.75-0.78, showing a relatively high extraction accuracy; (2) the GBA urban expansion followed a circular and radial expansion pattern; (3) the growth trend of expansion intensity and development potential for sub-central cities was stronger than central cities; and (4) the agglomeration auto correlation of the spatial expansion in the GBA presents a continuous dispersion trend. Compared with previous methods, our study improved the extraction accuracy of urban expansion and effectively reduced the deficiency of overflow effect for NPP-VIIRS nighttime light. The research can thus provide valuable datasets and reference for decision-making to adjust and optimize urban development pattern and design urban sustainable development.

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