Representing Multiple Urban Places' Footprints from Dianping.com Data

doi:10.11947/j.AGCS.2018.20180110

Abstract

Abstract: A place is a geographical area with a particular semantic and humanistic experience.In virtual geographic environment studies,places play an important role in spatial knowledge representation,by providing the support for human-centroid understanding of geographic environment and VGE-based analysis and simulation.Identifying and modeling the existing vague places in cities are therefore fundamental to VGE studies.Crowd-sourced geo-data provide a new approach to extracting and representing vague places.The most of existing research,however,focused on modeling single or a few places but not considering the influence of threshold selection among multiple point sets of places in diverse scales.In order to model multiple places of the city at different spatial scales,we proposed the fuzzy set method based on adaptive kernel density estimation for generating the spatial footprints of places,which can provide a reasonable and efficient way to model multiple vague places.In the case study,POIs inside the 5^th Ring Road of Beijing,collected from Dianping.com,are used to visually represent footprints of places in the way of fuzzy sets and α-cuts,with the former one avoiding the over simplified representation of continuous surface while the latter focusing more on the crisp boundaries.By comparing the results and the corresponding places' scales showed by base maps,we found that the use of the dataset harvested from dianping.com could provide a better understanding of the places' footprints of commercial context.

Key words: vague places, spatial cognition, fuzzy set, crowdsourced data

CLC Number:

P281

WANG Shengyin, LIU Yu, CHEN Zedong, SHI Li, ZHANG Jing. Representing Multiple Urban Places' Footprints from Dianping.com Data[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(8): 1105-1113.

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