转载 【轨迹数据集】GPS轨迹数据集整理

原博文：https://blog.csdn.net/liangyihuai/article/details/58335510

本文主要是整理了GPS轨迹数据集免费资源库，从这些库中能够免费下载到GPS数据，同时还整理出了这些数据的格式，数据集的简单描述等等。如果你发现更好的相关数据资源，欢迎共享 :)

https://www.microsoft.com/en-us/download/details.aspx?id=52367

  • 数据格式：

    • 一个文件夹存储一个用户的GPS日志，这些日志文件都被转换成了plt格式。为了避免时间区间问题，统一使用了GMT格式的时间表示。其他具体格式为：

    1.   Line 1…6 are useless in this dataset, andcan be ignored. Points are described in following lines, one for each line.
    2.   Field 1: Latitude in decimal degrees.
    3.   Field 2: Longitude in decimal degrees.
    4.   Field 3: All set to 0 for this dataset.
    5.   Field 4: Altitude in feet (-777 if notvalid).
    6.   Field 5: Date - number of days (withfractional part) that have passed since 12/30/1899.
    7.   Field 6: Date as a string.
    8.   Field 7: Time as a string.
    9.   Note that field 5 and field 6&7represent the same date/time in this dataset. You may use either of them.
    10.    
    11.   Example:
    12.   39.906631,116.385564,0,492,40097.5864583333,2009-10-11,14:04:30
    13.   39.906554,116.385625,0,492,40097.5865162037,2009-10-11,14:04:35

    交通方式数据集格式：

    可能的交通方式有：walk,bike, bus, car, subway, train, airplane, boat, run and motorcycle，再次强调，虽然大多数数据是在中国产生的，但是，还是把时间或者日期都统一以GMT的时间形式表示。

    例如：

    Start Time End Time Transportation Mode

    2008/04/02 11:24:21 2008/04/02 11:50:45bus

    具体说明在下载的文件压缩包中！

    • 使用到该数据的论文有：

    Q. Li, Y. Zheng, X. Xie, Y. Chen, W. Liu, and M. Ma. 2008.Mining user similarity based on location history. In Proceedings of the 16thAnnual ACM International Conference on Advances in Geographic InformationSystems. ACM, 34.

    Z. Chen, H. T. Shen, X. Zhou, Y. Zheng, and X. Xie. 2010.Searching trajectories by locations—An efficient study. In Proceedings of the29th ACM SIGMOD International Conference on Management of Data. ACM,255–266.

    [1] Yu Zheng, Lizhu Zhang, Xing Xie, Wei-Ying Ma. Mininginteresting locations and travel sequences from GPS trajectories. InProceedings of International conference on World Wild Web (WWW 2009), MadridSpain. ACM Press: 791-800.

    [2] Yu Zheng, Quannan Li, Yukun Chen, Xing Xie, Wei-Ying Ma.Understanding Mobility Based on GPS Data. In Proceedings of ACM conference onUbiquitous Computing (UbiComp 2008), Seoul, Korea. ACM Press: 312-321.

    [3] Yu Zheng, Xing Xie, Wei-Ying Ma, GeoLife: ACollaborative Social Networking Service among User, location and trajectory.Invited paper, in IEEE Data Engineering Bulletin. 33, 2, 2010, pp. 32-40.

    https://www.microsoft.com/en-us/research/publication/t-drive-trajectory-data-sample/

    • 数据详细说明：

    https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/User_guide_T-drive.pdf

    • 数据格式：

    Here is a piece ofsample in a file:

    1.   1,2008-02-0215:36:08,116.51172,39.92123
    2.   1,2008-02-0215:46:08,116.51135,39.93883
    3.   1,2008-02-0215:46:08,116.51135,39.93883
    4.   1,2008-02-0215:56:08,116.51627,39.91034
    5.   1,2008-02-0216:06:08,116.47186,39.91248
    6.   1,2008-02-0216:16:08,116.47217,39.92498
    7.   1,2008-02-02 16:26:08,116.47179,39.90718
    8.   1,2008-02-0216:36:08,116.45617,39.90531
    9.   1,2008-02-0217:00:24,116.47191,39.90577
    10.   1,2008-02-0217:10:24,116.50661,39.9145
    11.   1,2008-02-0220:30:34,116.49625,39.9146

    每一个字段的所代表的意思是：

    taxi id, date time,longitude, latitude

    • 使用到该数据集的论文有：

    J. Yuan, Y. Zheng, and X. Xie. 2012. Discovering regions ofdifferent functions in a city using human mobility and POIs. In Proceedings ofthe 18th ACM SIGKDD International Conference on Knowledge Discovery and DataMining. ACM, 186–194.

    J. Yuan, Y. Zheng, C. Zhang, W. Xie, X. Xie, G. Sun, and Y.Huang. 2010a. T-Drive: Driving directions based on taxi trajectories. InProceedings of the 18th Annual ACM International Conference on Advances inGeographic Information Systems. ACM, 99–108.

    J. Yuan, Y. Zheng, X. Xie, and G. Sun. 2011a. Driving withknowledge from the physical world. In Proceedings of the 17th ACM SIGKDDInternational Conference on Knowledge Discovery and Data Mining. ACM, 316–324.

    J. Yuan, Y. Zheng, X. Xie, and G. Sun. 2013a. T-Drive:Enhancing driving directions with taxi drivers’

    intelligence. IEEE Transaction on Knowledge and DataEngineering 25, 1 (2013), 220–232.

    N. J. Yuan, Y. Zheng, L. Zhang, and X. Xie. 2013b. T-Finder:A recommender system for finding passengers and vacant taxis. IEEE Transactionon Knowledge and Data Engineering 25, 10 (2013), 2390–2403.

    N. J. Yuan, Y. Zheng, X. Xie, Y. Wang, K. Zheng, and H.Xiong. 2015. Discovering urban functional zones using latent activitytrajectories. IEEE Transactions on Knowledge and Data Engineering 27, 3 (2015),1041–4347.

    S. Ma, Y. Zheng, and O. Wolfson. 2013. T-Share: Alarge-scale dynamic taxi ridesharing service. In Proceedings of the 29th IEEEInternational Conference on Data Engineering. IEEE, 410–421.

    S. Ma, Y. Zheng, and O. Wolfson. 2015. Real-time city-scaletaxi ridesharing. IEEE Transactions on Knowledge and Data Engineering 99.DOI:http://doi.ieeecomputersociety.org/10.1109/TKDE.2014.2334313

    Jing Yuan, Yu Zheng, Xing Xie, and Guangzhong Sun. Drivingwith knowledge from the physical world. In The 17th ACM SIGKDD internationalconference on Knowledge Discovery and Data mining, KDD’11, New York, NY, USA,2011. ACM.

    Jing Yuan, Yu Zheng, Chengyang Zhang, Wenlei Xie, Xing Xie, Guangzhong Sun, and 
    Yan Huang. T-drive: driving directions based on taxi trajectories. In 
    Proceedings of the 18th SIGSPATIAL International Conference on Advances in 
    Geographic Information Systems, GIS ’10, pages 99-108, New York, NY, USA,2010. 
    ACM.

    https://www.microsoft.com/en-us/research/publication/gps-trajectories-with-transportation-mode-labels/

    • 数据格式：

    交通方式数据格式：

    1.   Date Start Time End Time Transportationmodes
    2.   2008/3/1 11:07:00 11:40:00 walk
    3.   2008/3/1 11:44:00 12:07:00 bus
    4.   2008/3/1 12:07:00 13:30:00 walk
    5.   2008/3/1 13:30:00 13:55:00 car
    6.   2008/3/1 13:55:00 14:16:00 walk

    Plt格式文件数据的格式：

    1.   39.977685,116.3276249,1,0,39539.1428935185,2008/04/01,03:25:46
    2.   39.9777233,116.3276216,0,0,39539.1429050926,2008/04/01,03:25:47
    3.   39.9778499,116.3276266,0,0,39539.1429398148,2008/04/01,03:25:50
    4.   39.9779866,116.3276249,0,0,39539.142974537,2008/04/01,03:25:53
    5.   39.97812,116.3276133,0,0,39539.1430092593,2008/04/01,03:25:56
    6.   第一个字段：纬度（十进制）
    7.   第二个字段：纬度（十进制）
    8.   第三个字段：0表示正常，1表示在轨迹中断
    9.   第四个字段：海拔高度（英尺），-777表示无效
    10.   第五个字段：日期—注意下面的日期格式，如果是空白的，就会使用一个预设的日期。
    11.   第六个字段：日期字符串
    12.   第七个字段：时间字符串

    需要注意的是： 
    这里写图片描述

    具体请查看官方说明：

    https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/User20Guide-with20labels.pdf）

    • 使用到该数据集的论文：

    Y. Zheng, Q. Li, Y. Chen, and X. Xie. 2008a. Understandingmobility based on GPS data. In Proceedings of the 11th International Conferenceon Ubiquitous Computing. ACM, 312–321.

    Y. Zheng, L. Liu, L. Wang, and X. Xie. 2008b. Learningtransportation mode from raw GPS data for geographic application on the Web. InProceedings of the 17th International Conference on World Wide Web.ACM,247–256.

    [1] Yu Zheng, Like Liu, Longhao Wang, Xing Xie. LearningTransportation Modes from Raw GPS Data for Geographic Application on the Web,In Proceedings of International conference on World Wild Web (WWW 2008), Beijing,China. ACM Press: 247-256

    [2] Yu Zheng, Quannan Li, Yukun Chen, Xing Xie. Understanding Mobility Based on 
    GPS Data. In Proceedings of ACM conference on Ubiquitous Computing (UbiComp 
    2008), Seoul, Korea. ACM Press: 312–321.

    [3] Yu Zheng, Yukun Chen, Quannan Li, Xing Xie, Wei-Ying Ma.Understanding transportation modes based on GPS data for Web applications. ACMTransaction on the Web. Volume 4, Issue 1, January, 2010. pp. 1-36.

    https://snap.stanford.edu/data/loc-gowalla.html

    这个也是上面同一家网站所产生的数据，也是基于社交网络数据，大约300M， 详情和下载网址为；http://www.yongliu.org/datasets

    • 使用到该数据集的论文有：

    E. Cho, S. A. Myers, J. Leskovec. Friendship and Mobility: Friendship and Mobility: User Movement in Location-BasedSocial Networks ACM SIGKDD International Conference on KnowledgeDiscovery and Data Mining (KDD), 2011.

    • 使用了check-in类型数据集的论文有：

    L. Wei, Y. Zheng, and W. Peng. 2012. Constructing popularroutes from uncertain trajectories. In Proceedings of the 18th ACM SIGKDD InternationalConference on Knowledge Discovery and Data Mining. ACM, 195–203.

    J. Bao, Y. Zheng, and M. F. Mokbel. 2012. Location-based andpreference-aware recommendation using sparse geo-social networking data. InProceedings of the 20th ACM SIGSPATIAL International Conference on Advances inGeographic Information Systems. ACM, 199–208.

    2013年Foursquare的数据集(150M)：

    • 详情：https://archive.org/details/201309_foursquare_dataset_umn
    • 下载：https://archive.org/download/201309_foursquare_dataset_umn
    • 其他check-in数据集下载地址： https://sites.google.com/site/yangdingqi/home/foursquare-dataset

    http://www.nhc.noaa.gov/data/hurdat/hurdat2-1851-2015-070616.txt
  • 其他详细信息：http://www.nhc.noaa.gov/data/
  • 还可以查看：http://www.nhc.noaa.gov/data/hurdat/hurdat2-format-atlantic.pdf
  • 数据格式：

    • 这个数据集用逗号分隔的文本，六小时信息的位置，最大的风，中央的压力，和（从2004开始）所有已知的热带气旋和热带气旋的大小。

    这里写图片描述

    （2）1949-2015年东北部和北部太平洋中心飓风数据库，大概3.2兆。

    • 下载地址：http://www.nhc.noaa.gov/data/hurdat/hurdat2-nepac-1949-2015-050916.txt
    • 数据格式和上面的数据集的是一样子的。
    • 具体还可以查看：http://www.nhc.noaa.gov/data/hurdat/hurdat2-format-nencpac.pdf

    http://dm.uestc.edu.cn/resource/

    Natural Earth :http://www.naturalearthdata.com/

    Machine Learning Repository: http://archive.ics.uci.edu/ml/

    Google Trends Datastore: http://googletrends.github.io/data/

    Open Data Network: https://www.opendatanetwork.com/

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