Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration by Fusing Nighttime Light Data with Weibo Sign-In Data

Bibliographic Data

ID22032989
AuthorsYongwang Cao (0000-0002-2645-2828, Zhejiang Academy of Social Sciences), Song Liu (0000-0002-2248-4283, Zhejiang Academy of Social Sciences), Zaigao Yang (Zhejiang Academy of Social Sciences, corresponding author)
Year2024
Volume13
Issue6
Pages214
Publication date2024-06-19
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi13060214
OpenAlexW4399803108
LanguageEN
References cited53

Accurately identifying the spatial range of urban agglomerations holds significant practical importance for the precise allocation of various elements and coordinated development within urban agglomerations. However, current research predominantly focuses on the physical spaces of urban agglomerations, overlooking their sphere of influence. This study begins with the spatial interactions of population elements within urban agglomerations and fuses Weibo sign-in data with NTL data to identify the spatial range of urban agglomerations. It further compares and validates the results before and after the fusion of data. The results reveal that the accuracy of identifying the spatial range of urban agglomerations with the fusion of NTL data and Weibo sign-in data has improved by 7%, with a Kappa increase of 0.1766 compared to using NTL data alone, which indicates that fusing social media data can significantly enhance the accuracy of identifying the spatial range of urban agglomerations. This study proposes a novel approach for identifying the spatial range of urban agglomerations through the fusion of NTL data and social media data from a data fusion perspective. On one hand, it supplements the application of data fusion in the study of urban agglomeration spaces; on the other hand, it accurately identifies the spatial range of urban agglomerations, which holds great practical value for the sustainable development of urban agglomerations

Archaeology · Cartography · Delta · Economic geography · Geography · Meteorology · Pearl · Remote sensing · Urban agglomeration · Engineering · Environmental Science · Impact of Light on Environment and Health · Land Use and Ecosystem Services · Mathematics · Urban Transport and Accessibility

  • Using multi-source geospatial big data to identify the structure of polycentric cities

    Open Access•Jixuan Cai, Bo Huang et al.•Remote Sensing of Environment•2017

  • Urban agglomeration

    Open Access•Chuanglin Fang, Danlin Yu•Landscape and Urban Planning•2017

  • Exploring Urban Spatial Features of Covid-19 Transmission in Wuhan Based on Social Media Data

    Open Access•Zhenghong Peng, Ru Wang et al.•ISPRS International Journal of…•2020

  • Assessing Regional Development Balance Based on Zipf’s Law

    Open Access•Liang Kong, Qinglin Wu et al.•ISPRS International Journal of…•2023

  • A New Approach to Refining Land Use Types

    Open Access•Xucai Zhang, Yeran Sun et al.•ISPRS International Journal of…•2020

  • A building volume adjusted nighttime light index for characterizing the relationship between urban population and nighttime light intensity

    Open Access•Bin Wu, Wu Bin et al.•Computers Environment and Urban…•2023

  • How do different types and landscape attributes of urban parks affect visitors' positive emotions

    Open Access•Lingqiang Kong, Zhifeng Liu et al.•Landscape and Urban Planning•2022

  • Defining urban clusters to detect agglomeration economies

    Open Access•Clémentine Cottineau‐Mugadza, Olivier Finance et al.•Environment and Planning B Urban…•2019

  • A comparison of nighttime lights data for urban energy research

    Open Access•Michail Fragkias, J Lobo et al.•Environment and Planning B Urban…•2017

  • Understanding Chinese tourist mobility and consumption-related behaviours in London using Sina Weibo check-ins

    Open Access•Zi Ye, Andy Newing et al.•Environment and Planning B Urban…•2021

  • Assessing nighttime lights for mapping the urban areas of 50 cities across the globe

    Open Access•Hasi Bagan, Habura Borjigin et al.•Environment and Planning B Urban…•2019

  • Measuring the coupling of built-up land intensity and use efficiency

    Open Access•Linlin Ruan, Tingting He et al.•Sustainable Cities and Society•2022

  • Extraction and monitoring approach of dynamic urban commercial area using check-in data from Weibo

    Open Access•Qingwu Hu, Guikai Bai et al.•Sustainable Cities and Society•2019

  • Characterizing Depression Issues on Sina Weibo

    Open Access•Xianyun Tian, Philip J Batterham et al.•International Journal of…•2018

  • Using Location-Based Social Media to Chart the Patterns of People Moving between Cities

    Weiyang Zhang, Ben Derudder et al.•Journal of Urban Technology•2016

  • Reconciling big data and thick data to advance the new urban science and smart city governance

    Open Access•Amanda Hong, Lucy Baker et al.•Journal of Urban Affairs•2022

  • Integrated regional development

    Open Access•Lei Li, Shaojun Ma et al.•Land Use Policy•2022

  • Understanding urban China with open data

    Open Access•Xingjian Liu, Yan Song et al.•Cities•2015

  • The coordination relationship between urban development and urban life satisfaction in Chinese cities - An empirical analysis based on multi-source data

    Open Access•Xiong He, Yuquan Zhou et al.•Cities•2024

  • The role of planning policy in the evolution of the spatial structure of the Guangzhou metropolitan area in China

    Open Access•Xiong He, Rongrong Zhang et al.•Cities•2023

  • Quantifying the bias in place emotion extracted from photos on social networking sites

    Open Access•Yingjing Huang, Jun Li et al.•Cities•2020

  • Does urbanization level and types of urban settlements matter for child stunting prevalence in India? Empirical evidence based on nighttime lights data

    Open Access•Nimish Sharma, Shruti Shastri et al.•Cities•2023

  • Urban network externalities, agglomeration economies and urban economic growth

    Open Access•Huang Yin, Yin Huang et al.•Cities•2020

  • The spatial integration and coordinated industrial development of urban agglomerations in the Yangtze River Economic Belt, China

    Open Access•Yaolin Liu, Xianghui Zhang et al.•Cities•2020

  • Delineation of an urban agglomeration boundary based on Sina Weibo microblog ‘check-in’ data

    Open Access•Feng Zhen, Tashi Lobsang et al.•Cities•2017

  • Do Urban Social Enterprises Benefit from Agglomeration? Evidence from Four UK Cities

    Open Access•Steven Pinch, Peter Sunley•Regional Studies•2015

  • Identifying Urban Agglomerations in China Based on Density-Density Correlation Functions

    Xingye Tan, Bo Huang•Annals of the American…•2022

Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae