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題名:基於北京公交刷卡資料和興趣點的功能區識別
書刊名:城市規劃
作者:韓昊英于翔龍瀛
出版日期:2016
卷期:2016(6)
頁次:52-60
主題關鍵詞:公交IC卡刷卡數據興趣點出行行為功能區識別北京Bus smart card dataSCDPOIsTravel behaviorIdentification of functional zonesBeijing
原始連結:連回原系統網址new window
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  • 共同引用共同引用:69
  • 點閱點閱:7
城市在其發展過程中逐漸形成居住區、工業區和商業區等不同的功能區。識別這些功能區并理解其分布特征,對于把握城市結構以及制定和使用科學合理的規劃具有重要作用。本研究基于2008年4月北京市連續一周的7797余萬條公交IC卡刷卡數據,將其轉換為每個公交站臺流量的二維時間序列數據,結合居民日常出行行為研究,利用數據挖掘技術,構建了基于公交刷卡數據和興趣點的城市功能區識別模型,并將識別結果在交通分析小區尺度上匯總。研究結果顯示,利用城市功能區識別模型,通過冗余數據的篩除和特征的創建實現對數據的有效降維,并選用期望最大化算法對處理后的數據進行聚類分析,結合居民日常出行相關特征和興趣點分布數據對聚類結果進行詮釋,可以快速有效地識別出與北京市土地利用現狀地圖具有一定匹配度的北京市各功能區。本研究的方法可以輔助規劃人員和公眾有效識別和理解復雜的城市空間結構,對城市地理及規劃研究具有重要的理論和實踐價值。
Cities form various functional zones including residential zone, industrial zone, commercial zone, etc, during their development process. It is important for urban planners to identify different functional zones and understand their spatial distribution characteristics in order to better comprehend city structure and formulate and use rational urban plans. In this research, we used 77,976,010 bus smart card data(SCD) records of Beijing City in one week in April 2008 and converted them into two-dimensional time series data of each bus platform. Then, by applying the data mining techniques in combination with citizens’ daily travel behavior, we established the DZoF(discovering zones of different functions) model based on SCD(smart card data) and POIs(points of interest), and pooled the results at the TAZ(traffic analysis zone) level. The results suggest that DZoF model and cluster analysis based on dimensionality reduction and EM(expectationmaximization) algorithm can identify functional zones that well match the actual land uses in Beijing. The methodology in the present research can help urban planners and the public understand the complex urban spatial structure and contribute to the academia of urban geography and urban planning.
期刊論文
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10.Goodchild, Michael F.、Klinkenberg Brian、Janelle, Donald G.(1993)。A Factorial Model of Aggregate Patio-Temporal Behavior: Application to the Diurnal Cycle。Geographical Analysis,5,277-294。  new window
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15.Lu, Dengsheng、Weng, Qihao(2005)。Urban classification using full spectral information of landsat ETM+ imagery in Marion County, Indiana。Photogrammetric Engineering & Remote Sensing,71(11),1275-1284。  new window
16.龍瀛、張宇、崔承印(2012)。利用公交刷卡數據分析北京職住關係和通勤出行。地理學報,67(10),1-12。  延伸查詢new window
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21.柴彥威、翁桂蘭、龔華(2004)。深圳居民購物消費行為的時空間特徵。人文地理,19(6),80-84。  延伸查詢new window
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會議論文
1.Qi, G.、Li, X.、Li, S.、Pan, G.、Wang, Z.、Zhang, D.(2011)。Measuring social functions of city regions from large-scale taxi behaviors。9th IEEE International Conference on Pervasive Computing and Communications,(會議日期: March 21-25, 2011)。Seattle。384-388。  new window
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研究報告
1.Batty, M.(2009)。Cities as Complex Systems: Scaling, Interaction, Networks, Dynamics and Urban Morphologies。Berlin:Springer。  new window
2.Neuhaus, F.(2009)。Urban Diapy-a Tracking Project。  new window
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圖書
1.胡俊(1995)。中國城市:模式與演進。北京:中國建築工業出版社。  延伸查詢new window
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