测绘学报 ›› 2018, Vol. 47 ›› Issue (8): 1105-1113.doi: 10.11947/j.AGCS.2018.20180110

• 虚拟地理环境 • 上一篇    下一篇

大众点评数据下的城市场所范围感知方法

王圣音1, 刘瑜2, 陈泽东1, 施力2, 张晶1   

  1. 1. 首都师范大学资源环境与旅游学院, 北京 100048;
    2. 北京大学遥感与地理信息系统研究所, 北京 100871
  • 收稿日期:2018-03-15 修回日期:2018-06-12 出版日期:2018-08-20 发布日期:2018-08-22
  • 通讯作者: 张晶 E-mail:zhangjing5946@sina.com
  • 作者简介:王圣音(1992-),女,硕士生,研究方向为空间认知、空间数据挖掘。E-mail:sywang092@163.com
  • 基金资助:
    虚拟现实技术与系统国家重点实验室开放基金(01117220010020)

Representing Multiple Urban Places' Footprints from Dianping.com Data

WANG Shengyin1, LIU Yu2, CHEN Zedong1, SHI Li2, ZHANG Jing1   

  1. 1. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China;
    2. Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China
  • Received:2018-03-15 Revised:2018-06-12 Online:2018-08-20 Published:2018-08-22
  • Supported by:
    The Open Fund of National Key Laboratory of Virtual Reality Technology and Systems(No. 01117220010020)

摘要: “场所(place)”是具有特定语义和人文体验的地理位置,是虚拟地理环境中地理知识表达的核心要素,能够为深入理解与表达人们的地理空间认知,以及基于虚拟地理环境的分析模拟提供支持,因而对城市内部现有场所的识别与模糊建模是城市空间结构研究的基础之一。众源数据为提取和表达模糊场所提供了新的途径,然而目前研究多针对单个或少数几个场所进行建模。本研究针对城市多场所空间范围的多尺度建模,提出基于自适应核密度估计的模糊集方法,为进一步理解城市场所的模糊认知范围提供了可视化解决方案。并以北京市五环内场所为实例,采用大众点评网中商户自行上传的兴趣点(POI)数据,对其进行提取与表达。通过对比百度地图所展示的场所相应范围,发现该方法在大众点评数据集下的应用能更好地揭示商圈语义下的场所认知。

关键词: 模糊场所, 空间认知, 模糊集, 众源数据

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 5th 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

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