基于空间网格的多尺度人文地理特征分析

doi:10.11947/j.AGCS.2016.F011

测绘学报 ›› 2016, Vol. 45 ›› Issue (S1): 85-89.doi: 10.11947/j.AGCS.2016.F011

基于空间网格的多尺度人文地理特征分析

翟卫欣¹, 段杰雄¹, 童晓冲², 程承旗³, 宋树华⁴, 李爽¹

1. 北京大学遥感与地理信息系统研究所, 北京 100871;
2. 北京师范大学地表过程与资源生态国家重点实验室, 北京 100875;
3. 北京大学工学院, 北京 100871;
4. 北京苍穹数码测绘有限公司, 北京 100081

收稿日期:2016-08-10 修回日期:2016-10-20 出版日期:2016-12-31 发布日期:2017-03-29
通讯作者: 程承旗 E-mail:ccq@pku.edu.cn
作者简介:翟卫欣(1991-),博士,主要从事空间数据库索引、网格地理信息系统研究。E-mail:pkuzhaiweixin@gmail.com
基金资助:
高分辨率对地观测系统国家重大专项（11-Y20A02-9001-16117；30-Y20A01-9003-16/17；30-Y30B13-9003-14/16）；测绘地理信息公益性行业科研专项（201512020）

Geo-spatial Cognition on Human's Social Activity Space Based on Multi-scale Grids

ZHAI Weixin¹, DUAN Jiexiong¹, TONG Xiaochong², CHENG Chengqi³, SONG Shuhua⁴, LI Shuang¹

1. Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China;
2. State Key Laboratory of Earth Surface Process and Resource Ecology, Beijing Normal University, Beijing 100875, China;
3. College of Engineering, Peking University, Beijing 100871, China;
4. KQ GEO Technologies CO., LTD., Beijing 100081, China

Received:2016-08-10 Revised:2016-10-20 Online:2016-12-31 Published:2017-03-29
Supported by:
National Major Projects on High-Resolution Earth Observation System (Nos.11-Y20A02-9001-16117;30-Y20A01-9003-16117;30-Y30B13-9003-14116);Surveying and Mapping Geographic Information Public Welfare Industry Scientific Research Project (No.201512020)

摘要/Abstract

摘要： 随着手机等移动互联网设备的广泛使用，海量的人类社会活动的地理数据为地理学研究提供了新的数据基础，基于移动互联网的社会研究成为当前地理学研究的热点。本文以空间网格为基础，选取了2004年到2014年5月之间在中国境内上传至Flickr的包含位置信息的数据作为研究对象，以Alexander分形理论为依据探讨了地理空间中的尺度特征与人文地理特征的关系。选取了HT-指数测量地理对象分化程度的表征指标，并用信息熵理论对其进行检验。研究结果表明，尺度的特征一定程度上与人文地理特征是有正相关性的。可以用网格作为控制尺度的工具从不同尺度来认知人类社会活动的空间分布模式。

关键词: 社会活动空间, HT-指数, 网格, 多尺度

Abstract: Widely applied location aware devices, including mobile phones and GPS receivers, have provided great convenience for collecting large volume individuals' geographical information. The researches on the human's society behavior space has attracts an increasingly number of researchers. In our research, based on location-based Flickr data From 2004 to May, 2014 in China, we choose five levels of spatial grids to form the multi-scale frame for investigate the correlation between the scale and the geo-spatial cognition on human's social activity space. The HT-index is selected as the fractal inspired by Alexander to estimate the maturity of the society activity on different scales. The results indicate that that the scale characteristics are related to the spatial cognition to a certain extent. It is favorable to use the spatial grid as a tool to control scales for geo-spatial cognition on human's social activity space.

Key words: social activity space, HT-index, grids, multi-scale

中图分类号:

P208

翟卫欣, 段杰雄, 童晓冲, 程承旗, 宋树华, 李爽. 基于空间网格的多尺度人文地理特征分析[J]. 测绘学报, 2016, 45(S1): 85-89.

ZHAI Weixin, DUAN Jiexiong, TONG Xiaochong, CHENG Chengqi, SONG Shuhua, LI Shuang. Geo-spatial Cognition on Human's Social Activity Space Based on Multi-scale Grids[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(S1): 85-89.

参考文献

[1] 刘瑜, 肖昱, 高松, 等. 基于位置感知设备的人类移动研究综述[J]. 地理与地理信息科学, 2011, 27(4):8-13, 31. LIU Yu, XIAO Yu, GAO Song, et al. Human Movement Research Review Based on Location Aware Devices[J]. Geography and Geo-Information Science, 2011, 27(4):8-13, 31.
[2] BAYIR M A, DEMIRBAS M, EAGLE N. Mobility Profiler:A Framework for Discovering Mobility Profiles of Cell Phone Users[J]. Pervasive and Mobile Computing, 2010, 6(4):435-454.
[3] BLONDEL V D, DECUYPER A, KRINGS G. A Survey of Results on Mobile Phone Datasets Analysis[J]. EPJ Data Science, 2015, 4:10.
[4] PHITHAKKITNUKOON S, SMOREDA Z, OLIVIER P. Socio-Geography of Human Mobility:A Study Using Longitudinal Mobile Phone Data[J]. PLoS One, 2012, 7(6):e39253.
[5] ALEXANDER C. The Nature of Order:An Essay on the Art of Building and the Nature of the Universe, Book 3-A Vision of A Living World[M]. Berkeley, CA:Routledge, 2005.
[6] ANDERSON G, GE Ying. Do Economic Reforms Accelerate Urban Growth? The Case of China[J]. Urban Studies, 2004, 41(11):2197-2210.
[7] RÉNYI A. On Measures of Entropy and Information[C]//Proceedings of the 4th Berkeley Symphony Mathematical Statistics and Probability. Berkeley, CA:[s.n.], 1961.
[8] SHANNON C E, WEAVER W. The Mathematical Theory of Communication[M]. Urbana:University of Illinois Press, 1971.
[9] JIANG Bin. A City Is a Complex Network[C]//MEHAFFY M W. Christopher Alexander A City is Not a Tree:50th Anniversary Edition. Portland, OR:Sustasis Press, 2015.
[10] JIANG Bin, YIN Junjun. Ht-Index for Quantifying the Fractal or Scaling Structure of Geographic Features[J]. Annals of the Association of American Geographers, 2014, 104(3):530-540.
[11] JIANG Bin. Street Hierarchies:A Minority of Streets Account for A Majority of Traffic Flow[J]. International Journal of Geographical Information Science, 2009, 23(8):1033-1048.
[12] JIANG Bin, LIU Xintao. Scaling of Geographic Space from the Perspective of City and Field Blocks and Using Volunteered Geographic Information[J]. International Journal of Geographical Information Science, 2012, 26(2):215-229.
[13] JIANG Bin. Wholeness as A Hierarchical Graph to Capture the Nature of Space[J]. International Journal of Geographical Information Science, 2015, 29(9):1632-1648.
[14] JIANG Bin. Head/Tail Breaks for Visualization of City Structure and Dynamics[J]. Cities, 2015, 43:69-77.
[15] THOMEE B, SHAMMA D A, FRIEDLAND G, et al. YFCC100M:the New Data in Multimedia Research[J]. Communications of the ACM, 2016, 59(2):64-73.
[16] 程承旗. 空间信息剖分组织导论[M]. 北京:科学出版社, 2012. CHENG Chengqi. An Introduction to Spatial Information Subdivision Organization[M]. Beijing:Science Press, 2012.
[17] 李德仁, 朱欣焰, 龚健雅. 从数字地图到空间信息网格——空间信息多级网格理论思考[J]. 武汉大学学报(信息科学版), 2003, 28(6):642-650. LI Deren, ZHU Xinyan, GONG Jianya. From Digital Map to Spatial Information Multi-Grid-A Thought of Spatial Information Multi-Grid Theory[J]. Geomatics and Information Science of Wuhan University, 2003, 28(6):642-650.
[18] 宋树华, 程承旗, 关丽, 等. 全球空间数据剖分模型分析[J]. 地理与地理信息科学, 2008, 24(4):11-15. SONG Shuhua, CHENG Chengqi, GUAN Li, et al. Analysis on Global Geodata Partitioning Models[J]. Geography and Geo-Information Science, 2008, 24(4):11-15.
[19] 金安, 程承旗. 基于全球剖分网格的空间数据编码方法[J]. 测绘科学技术学报, 2013, 30(3):284-287. JIN An, CHENG Chengqi. Spatial Data Coding Method Based on Global Subdivision Grid[J]. Journal of Geomatics Science and Technology, 2013, 30(3):284-287.
[20] JIANG Bin, YIN Junjun, LIU Qingling. Zipf's Law for All the Natural Cities Around the World[J]. International Journal of Geographical Information Science, 2015, 29(3):498-522.

基于空间网格的多尺度人文地理特征分析

Geo-spatial Cognition on Human's Social Activity Space Based on Multi-scale Grids

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