地理科学进展 ›› 2008, Vol. 27 ›› Issue (2): 96-103.doi: 10.11820/dlkxjz.2008.02.013

• 经济地理与旅游地理 • 上一篇    下一篇

城市居民认知距离透视认知变形 ———以北京市为例

薛露露,申思,刘瑜,张毅   

  1. 北京大学遥感与地理信息系统研究所,北京 100871
  • 收稿日期:2008-01-01 修回日期:2008-02-01 出版日期:2008-03-25 发布日期:2008-03-25
  • 通讯作者: 刘瑜, Email:liuyu@urban.pku.edu.cn E-mail:liuyu@urban.pku.edu.cn
  • 作者简介:薛露露(1983-), 硕士研究生, 主要研究方向地理信息系统.Email: xuelulu@pku.edu.cn
  • 基金资助:

    国家自然科学基金(40701134), 国家高科技研究发展计划(863 计划) (2007AA12Z216).

Measur ement and Analysis on City Residents'Cognitive Distance Distor tion—A Case Study of Beijing

XUE Lulu,SHEN Si,LIU Yu,ZHANG Yi   

  1. Institute of RS and GIS, Peking University, Beijing 100871
  • Received:2008-01-01 Revised:2008-02-01 Online:2008-03-25 Published:2008-03-25

摘要:

对距离的认知是人类建立认知空间框架的重要基础。本文在相关研究的基础上, 对认知距离的特点进行了分析, 提出从数量认知距离与实际认知距离两种分析角度来分析这一概念。通过分别利用定义一元线性回归, 与 采用多维标度法(MDS)及二维回归(BR), 对认知距离的标量变形和向量变形进行定量分析。在此基础上, 以北京市 为例, 对北京市居民进行抽样调查。通过认知心理学实验的方式, 令被试估计城市主要地标两两之间的距离。对实 验结果分别将上述方法应用于计算北京市居民在标量变形和向量变形的定量化表示, 并进一步通过方差分析 (ANOVA)讨论了影响北京市居民对城市距离认知变形的因素, 包括年龄、居住地区等。

关键词: 变形, 城市, 多维标度法, 二维回归, 距离估计, 认知距离

Abstract:

Through generalizing related literature, we summarized some properties of cognitive distance and reduced all research on this concept into two aspects: pure value, and real cognitive distance. Further, we proposed a Distance Estimate Index (DEI) to quantify the scalar cognitive distance distortion. As far as vector cognitive distance distortion is considered, the Distortion Index (DI) computed by bi- dimensional regression is adopted to descript the degree of vector cognitive distance distortion. Based on these quantification methods, we conducted a survey on sampled Beijing residents, requesting the subjects to estimat the pairwise distances between 8 landmarks. And then we calculated the distortion of the two types of cognitive distances respectively by using linear regression and multidimensional scaling methods. Further, through ANOVA, we analyzed the factors that would possibly have influence on such distortion, like age and neighborhood. The result shows that the years of residence and the resident districts are the demographic variables that could influence an individual's accuracy in cognitive distance.

Key words: Bidimensional Regression (BR), cognitive distance, distance estimate, distortion, intra- urban, Multidimensional Scaling (MDS)