Sustainability · 2019 · 17 citations · 21 references
Social SciencesGeographyUrban PlanningSpatial AnalysisSpatial Data AnalysisUrban DevelopmentCity GrowthUrban ExpansionUrban GrowthUrban Spatial AnalysisUrban Spatial DistributionUrban Spatial StructureBlock Structure AnalysisCity Growth PatternsGeospatial Big DataGeospatial Big Data AnalyticsGeospatial Big Data ProcessingSpatial Pattern MiningUrban Block StructureUrban Pattern Analysis
As a kind of geospatial big data, point of interest (POI) with useful information has become a hot research topic. Compared with traditional methods, big data has great potential in developing a more accurate method for identifying the urban spatial pattern. This paper uses diversity index and kernel density analysis of POI data on several types of urban infrastructure to investigate the identification of urban block development stages in Wuhan, and divides them into the primary, growth, and mature stage. Its accuracy is verified by exploring urban micro-centers. Results show that: (1) the spatial pattern of urban blocks in Wuhan presents the distribution of “mature blocks concentrated like a core, growth blocks distributed like two wings, and primary blocks with wide range distributed surround”; (2) areas with more connected construction land and streets with better socio-economic status tend to have a higher level of maturity, vice versa; (3) balancing the number of micro-centers at different stages is beneficial to promote the flattened urban development of Wuhan in the future. The research proves that this method is feasible, and it is also applicable to the study of urban spatial pattern in other cities.
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Detecting Urban Polycentric Structure from POI Data
Yue Deng, Jiping Liu, Yang Liu et al. · ISPRS International Journal of Geo-Information · 2019 · 102 citations · Full text