手机定位数据在城市规划基础调查中的适用性研究——以深圳市高新园区为例
|
摘要
近年来,手机定位数据越来越多的应用于城市规划基础调查。但文献显示,大部分研究集中于较大尺度(城市、区域)范围下的城市问题,中小尺度的研究则相对较少。主要原因是手机定位数据的适用性受定位精度和地理情景等因素影响,而且这种影响随着研究尺度的缩小而扩大。从手机定位数据的定位精度问题和研究具体问题所遇到的不确定地理情境问题两个方面,对手机定位数据在城市规划中小尺度下基础调研中的适用性进行分析,并通过对比手机定位数据和问卷调查数据,以深圳高新园区员工的居住地分布特征为例子,验证手机定位数据在中小尺度下的适用性。
In recent years,mobile positioning data( MPD) have been applied in urban planning survey. However,literature applying MPD in urban planning mostly focus on macro-scale regions because of two reasons. One is the spatial error of MPD and the other is the uncertain geographic context problem( UGCo P). It is important to discuss the applicability of MPD in a meso-and micro-scale basis,which can widen the scope of application of MPD. This paper aims to discuss the impact factors of the applicability of MPD in urban planning,considering the spatial error of MPD and the UGCo P. Using High-tech Park in Shenzhen as a study case,we verify the applicability of MPD in the micro-scale basis.
In recent years,mobile positioning data( MPD) have been applied in urban planning survey. However,literature applying MPD in urban planning mostly focus on macro-scale regions because of two reasons. One is the spatial error of MPD and the other is the uncertain geographic context problem( UGCo P). It is important to discuss the applicability of MPD in a meso-and micro-scale basis,which can widen the scope of application of MPD. This paper aims to discuss the impact factors of the applicability of MPD in urban planning,considering the spatial error of MPD and the UGCo P. Using High-tech Park in Shenzhen as a study case,we verify the applicability of MPD in the micro-scale basis.
引文
[1]Ratti Carlo,Frenchman Denniset al.Mobile Landscapes:Using Location Data from Cell Phones for Urban Analysis[J].Environment&Planning B Planning&Design,2006(33):727-748.
[2]de Montjoye Y A,Hidalgo C A.et al.Unique in the Crowd:The privacy bounds of human mobility.[J].Scientific Reports,2013(3):776.
[3]Nobis Claudia,Lenz Barbara.Communication and mobility behaviour-a trend and panel analysis of the correlation between mobile phone use and mobility[J].Journal of Transport Geography,2009(17):93-103.
[4]Song Chaoming,Koren Talet al.Modelling the scaling properties of human mobility[J].Nature Physics,2010(6):818-823.
[5]Shaw S L,Yu H.A GIS-based Time-geographic Approach of Studying Individual Activities and Interactions in a Hybrid Physicalvirtual Space[J].Journal of Transport Geography,2009(17):141-149.
[6]申悦,柴彦威.基于GPS数据的城市居民通勤弹性研究---以北京市郊区巨型社区为例[J].地理学报,2012(6):733-744.
[7]申悦,柴彦威.基于GPS数据的北京市郊区巨型社区居民日常活动空间[J].地理学报,2013(64):506-516.
[8]Sun J B,Yuan J.et al.Exploring space-time structure of human mobility in urban space[J].Fuel&Energy Abstracts,2011(390):929-942.
[9]Wang Zhenhua,Tu Laiet al.Analysis of user behaviors by mining large network data sets[J].Future Generation Computer Systems,2014(37):429-437.
[10]Ahas Rein,Aasa Antoet al.Evaluating passive mobile positioning data for tourism surveys:An Estonian case study[J].Tourism Management,2008(29):469-486.
[11]Phithakkitnukoon Santi,Horanont Teerayutet al.Activity-Aware Map:Identifying Human Daily Activity Pattern Using Mobile Phone Data:Human Behavior Understanding,First International Workshop[C].HBU 2010,Istanbul,Turkey,August 22,2010.
[12]Calabrese Francesco,Lorenzo Giusy Diet al.Estimating OriginDestination Flows Using Mobile Phone Location Data[J].Pervasive Computing IEEE,2011(10):36-44.
[13]冉斌.手机数据在交通调查和交通规划中的应用[J].城市交通,2013(11):72-81.
[14]黄美灵,陆百川.基于手机定位的交通OD数据获取技术[J].重庆交通大学学报(自然科学版),2010(29):162-166.
[15]Soto Victor,Friasmartinez Enrique.Robust Land Use Characterization of Urban Landscapes using Cell Phone Data[J].Workshop on Pervasive Urban Applications,2011.
[16]Toole Jameson L,Ulm Michaelet al.Inferring land use from mobile phone activity[J].Proceedings of the Acm Sigkdd International Workshop on Urban Computing,2012:1-8.
[17]Louail T,Lenormand M.et al.From mobile phone data to the spatial structure of cities.[J].Physics,2014(4):61.
[18]Long Vu,Nguyen Phuonget al.Characterizing and modeling people movement from mobile phone sensing traces[J].Pervasive&Mobile Computing,2015(17):220-235.
[19]Buckee Caroline O,Wesolowski Amyet al.Mobile phones and malaria:Modeling human and parasite travel[J].Travel Medicine&Infectious Disease,2013(11):15-22.
[20]Chen Cynthia,Bian Ling,Ma Jingtao.From traces to trajectories:How well can we guess activity locations from mobile phone traces?[J].Transportation Research Part C Emerging Technologies,2014(46):326-337.
[21]Becker R A,Caceres R.et al.A Tale of One City:Using Cellular Network Data for Urban Planning[J].Pervasive Computing IEEE,2011(10):18-26.
[22]Ahas Rein,Silm Siiriet al.Modelling Home and Work Locations of Populations Using Passive Mobile Positioning Data[M].2008.
[23]Ahas Rein,Silm Siiriet al.Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones[J].Journal of Urban Technology,2010(17):3-27.
[24]Isaacman Sibren,Becker Richardet al.Human mobility modeling at metropolitan scales:Proceedings of the 10th international conference on Mobile systems,applications,and services,2012[C].
[25]Yuan Yihong,Raubal Martin,Liu Yu.Correlating mobile phone usage and travel behavior-A case study of Harbin,China[J].Computers Environment&Urban Systems,2012(36):118-130.
[26]Kwan Mei Po.How GIS can help address the uncertain geographic context problem in social science research[J].Annals of Gis,2012(18):245-255.
[27]Kwan Mei Po.The Uncertain Geographic Context Problem[J].Annals of the Association of American Geographers,2012(102):958-968.
[28]Kwan Mei Po.Uncertain Geographic Context Problem:Implications for Environmental Health Research:Apha Meeting and Exposition,2014[C].
[29]Kwana Mei Po,Weberb Joe.Scale and accessibility:Implications for the analysis of land use-travel interaction[J].Applied Geography,2008(28):110-123.
[30]Ahas Rein,Silm Siiriet al.Using mobile positioning data to model locations meaningful to users of mobile phones[J].Journal of Urban Technology,2010(17):3-27.
[31]龙瀛,张宇,崔承印.利用公交刷卡数据分析北京职住关系和通勤出行[J].地理学报,2012(6):1339-1352.
[32]许宁,尹凌,胡金星.从大规模短期规则采样的手机定位数据中识别居民职住地[J].武汉大学学报:信息科学版,2014(6):750-756.
[33]钮心毅,丁亮,宋小冬.基于手机数据识别上海中心城的城市空间结构[J].城市规划学刊,2014(6):61-67.
(1)http://www.airsage.com/Technology/Accuracy/
(2)泰森多边形是由一组由连接两邻点直线的垂直平分线组成的连续多边形组成,包括以下特征:a、每个泰森多边形内仅含有一个基站点数据;b、泰森多边形内的点到相应基站点的距离最近;c、位于泰森多边形边上的点到其两边的基站点的距离相等。
(3)仿真图的参数设置包括:RSRP:(Reference Signal Receiving Power,参考信号接收功率),是LTE网络中可以代表无线信号强度的关键参数以及物理层测量需求之一。SINR:(Signal to Interference plus Noise Ratio,信号与干扰加噪声比)是指接收到的有用信号的强度与接收到的干扰信号(噪声和干扰)的强度的比值。基站周边建筑物及树木的遮挡。它综合考虑了基站的覆盖范围的影响因素,利用射线跟踪模型对基站覆盖范围进行仿真。
(4)因为差值的绝对值是双向增加的,例如数据1在两个区域的比例是51%和49%,数据2在两个区域的比例是49%和51%,那么其差值的绝对之和是4%(|51%-49%|+|49%-51%|),因此对这个差值之和乘以0.5(2%),更能体现两组数据的整体差异。
[2]de Montjoye Y A,Hidalgo C A.et al.Unique in the Crowd:The privacy bounds of human mobility.[J].Scientific Reports,2013(3):776.
[3]Nobis Claudia,Lenz Barbara.Communication and mobility behaviour-a trend and panel analysis of the correlation between mobile phone use and mobility[J].Journal of Transport Geography,2009(17):93-103.
[4]Song Chaoming,Koren Talet al.Modelling the scaling properties of human mobility[J].Nature Physics,2010(6):818-823.
[5]Shaw S L,Yu H.A GIS-based Time-geographic Approach of Studying Individual Activities and Interactions in a Hybrid Physicalvirtual Space[J].Journal of Transport Geography,2009(17):141-149.
[6]申悦,柴彦威.基于GPS数据的城市居民通勤弹性研究---以北京市郊区巨型社区为例[J].地理学报,2012(6):733-744.
[7]申悦,柴彦威.基于GPS数据的北京市郊区巨型社区居民日常活动空间[J].地理学报,2013(64):506-516.
[8]Sun J B,Yuan J.et al.Exploring space-time structure of human mobility in urban space[J].Fuel&Energy Abstracts,2011(390):929-942.
[9]Wang Zhenhua,Tu Laiet al.Analysis of user behaviors by mining large network data sets[J].Future Generation Computer Systems,2014(37):429-437.
[10]Ahas Rein,Aasa Antoet al.Evaluating passive mobile positioning data for tourism surveys:An Estonian case study[J].Tourism Management,2008(29):469-486.
[11]Phithakkitnukoon Santi,Horanont Teerayutet al.Activity-Aware Map:Identifying Human Daily Activity Pattern Using Mobile Phone Data:Human Behavior Understanding,First International Workshop[C].HBU 2010,Istanbul,Turkey,August 22,2010.
[12]Calabrese Francesco,Lorenzo Giusy Diet al.Estimating OriginDestination Flows Using Mobile Phone Location Data[J].Pervasive Computing IEEE,2011(10):36-44.
[13]冉斌.手机数据在交通调查和交通规划中的应用[J].城市交通,2013(11):72-81.
[14]黄美灵,陆百川.基于手机定位的交通OD数据获取技术[J].重庆交通大学学报(自然科学版),2010(29):162-166.
[15]Soto Victor,Friasmartinez Enrique.Robust Land Use Characterization of Urban Landscapes using Cell Phone Data[J].Workshop on Pervasive Urban Applications,2011.
[16]Toole Jameson L,Ulm Michaelet al.Inferring land use from mobile phone activity[J].Proceedings of the Acm Sigkdd International Workshop on Urban Computing,2012:1-8.
[17]Louail T,Lenormand M.et al.From mobile phone data to the spatial structure of cities.[J].Physics,2014(4):61.
[18]Long Vu,Nguyen Phuonget al.Characterizing and modeling people movement from mobile phone sensing traces[J].Pervasive&Mobile Computing,2015(17):220-235.
[19]Buckee Caroline O,Wesolowski Amyet al.Mobile phones and malaria:Modeling human and parasite travel[J].Travel Medicine&Infectious Disease,2013(11):15-22.
[20]Chen Cynthia,Bian Ling,Ma Jingtao.From traces to trajectories:How well can we guess activity locations from mobile phone traces?[J].Transportation Research Part C Emerging Technologies,2014(46):326-337.
[21]Becker R A,Caceres R.et al.A Tale of One City:Using Cellular Network Data for Urban Planning[J].Pervasive Computing IEEE,2011(10):18-26.
[22]Ahas Rein,Silm Siiriet al.Modelling Home and Work Locations of Populations Using Passive Mobile Positioning Data[M].2008.
[23]Ahas Rein,Silm Siiriet al.Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones[J].Journal of Urban Technology,2010(17):3-27.
[24]Isaacman Sibren,Becker Richardet al.Human mobility modeling at metropolitan scales:Proceedings of the 10th international conference on Mobile systems,applications,and services,2012[C].
[25]Yuan Yihong,Raubal Martin,Liu Yu.Correlating mobile phone usage and travel behavior-A case study of Harbin,China[J].Computers Environment&Urban Systems,2012(36):118-130.
[26]Kwan Mei Po.How GIS can help address the uncertain geographic context problem in social science research[J].Annals of Gis,2012(18):245-255.
[27]Kwan Mei Po.The Uncertain Geographic Context Problem[J].Annals of the Association of American Geographers,2012(102):958-968.
[28]Kwan Mei Po.Uncertain Geographic Context Problem:Implications for Environmental Health Research:Apha Meeting and Exposition,2014[C].
[29]Kwana Mei Po,Weberb Joe.Scale and accessibility:Implications for the analysis of land use-travel interaction[J].Applied Geography,2008(28):110-123.
[30]Ahas Rein,Silm Siiriet al.Using mobile positioning data to model locations meaningful to users of mobile phones[J].Journal of Urban Technology,2010(17):3-27.
[31]龙瀛,张宇,崔承印.利用公交刷卡数据分析北京职住关系和通勤出行[J].地理学报,2012(6):1339-1352.
[32]许宁,尹凌,胡金星.从大规模短期规则采样的手机定位数据中识别居民职住地[J].武汉大学学报:信息科学版,2014(6):750-756.
[33]钮心毅,丁亮,宋小冬.基于手机数据识别上海中心城的城市空间结构[J].城市规划学刊,2014(6):61-67.
(1)http://www.airsage.com/Technology/Accuracy/
(2)泰森多边形是由一组由连接两邻点直线的垂直平分线组成的连续多边形组成,包括以下特征:a、每个泰森多边形内仅含有一个基站点数据;b、泰森多边形内的点到相应基站点的距离最近;c、位于泰森多边形边上的点到其两边的基站点的距离相等。
(3)仿真图的参数设置包括:RSRP:(Reference Signal Receiving Power,参考信号接收功率),是LTE网络中可以代表无线信号强度的关键参数以及物理层测量需求之一。SINR:(Signal to Interference plus Noise Ratio,信号与干扰加噪声比)是指接收到的有用信号的强度与接收到的干扰信号(噪声和干扰)的强度的比值。基站周边建筑物及树木的遮挡。它综合考虑了基站的覆盖范围的影响因素,利用射线跟踪模型对基站覆盖范围进行仿真。
(4)因为差值的绝对值是双向增加的,例如数据1在两个区域的比例是51%和49%,数据2在两个区域的比例是49%和51%,那么其差值的绝对之和是4%(|51%-49%|+|49%-51%|),因此对这个差值之和乘以0.5(2%),更能体现两组数据的整体差异。