Extraction of urban built-up area based on the fusion of night-time light data and point of interest data.

Luojia1-01 POI multi-source data fusion urban construction urbanization

Journal

Royal Society open science
ISSN: 2054-5703
Titre abrégé: R Soc Open Sci
Pays: England
ID NLM: 101647528

Informations de publication

Date de publication:
Aug 2021
Historique:
received: 11 05 2021
accepted: 12 07 2021
entrez: 13 8 2021
pubmed: 14 8 2021
medline: 14 8 2021
Statut: epublish

Résumé

The accurate extraction of urban built-up areas is an important prerequisite for urban planning and construction. As a kind of data that can represent urban spatial form, night-time light data has been widely used in the extraction of urban built-up areas. As one of the geographic open-source big data, point of interest (POI) data has a high spatial coupling with night-time light data, so researchers are beginning to explore the fusion of the two data in order to achieve more accurate extraction of urban built-up areas. However, the current research methods and theoretical applications of the fusion of POI data and night-time light data are still insufficient compared with the dramatically changing urban built-up areas, which needed to be further supplemented and deepened. This study proposes a new method to fuse POI data and night-time light data. The results before and after data fusion are compared, and the accuracy of urban built-up area extracted by different data and methods is analysed. The results show that the data fusion can avoid the shortage of single data and effectively improve the extraction accuracy of urban built-up areas, which is greatly helpful to supplement the study of data fusion in urban built-up areas, and also can provide decision-making guidance for urban planning and construction.

Identifiants

pubmed: 34386264
doi: 10.1098/rsos.210838
pii: rsos210838
pmc: PMC8334853
doi:

Types de publication

Journal Article

Langues

eng

Pagination

210838

Informations de copyright

© 2021 The Authors.

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Auteurs

Xiong He (X)

School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, People's Republic of China.
School of Ecology and Environmental Science, Yunnan University, Kunming 650031, People's Republic of China.
School of Architecture and Planning, Yunnan University, Kunming 650031, People's Republic of China.

Zhiming Zhang (Z)

School of Ecology and Environmental Science, Yunnan University, Kunming 650031, People's Republic of China.

Zijiang Yang (Z)

School of Architecture and Planning, Yunnan University, Kunming 650031, People's Republic of China.

Classifications MeSH