Overview

Container ports are generally measured by container throughput and facility productivity, etc. Being able to measure the performance quantitatively is important for researchers to design models for port operation and container logistics. The port performance indicators are directly related to the number of ships arriving at a port and the number of containers handled at each ship. In this work, we propose a framework to estimate the ship arriving number and container handling number from ship GPS traces and maritime open data. Based on this, we derive a set of port performance metrics, including ship traffic, container throughput, berth utilization, and terminal productivity, and compare the top-100 container ports worldwide using these metrics. (This work has been published in UbiComp’14)


Publications

  1. Longbiao Chen, Daqing Zhang, Gang Pan, Leye Wang, Xiaojuan Ma, Chao Chen, Shijian Li
    Container Throughput Estimation Leveraging Ship GPS Traces and Open Data [PDF]
    The ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp’14), Seattle, Washington, USA, September 13-17, 2014. (CORE Rank: A*, CCF Rank: A)

  2. Longbiao Chen, Daqing Zhang, Xiaojuan Ma, Leye Wang, Shijian Li, Zhaohui Wu, Gang Pan
    Container Port Performance Measurement and Comparison Leveraging Ship GPS Traces and Maritime Open Data
    IEEE Transactions on Intelligent Transportation Systems (T-ITS), 99 (2015): 1-16 (IF: 2.472, JCR Section I, CCF Rank B)


Dataset

shipdata.zip (10 MB)

Please note that due to agreements with port authorities and shipfinder.com, we are not allowed to publish the whole dataset.

This dataset includes the following resources.

  1. Sample AIS Traces/xxxxxxxxx

    This folder contains a sample set of 20 AIS traces extracted from our AIS database. Each file in the folder denotes a ship trace, and each row in the file denotes an AIS point. The filenames correspond to ship IDs (MMSIs), and the columns are separated by comma.

    • Column 1 denotes the time-stamp of the record
    • Column 2 denotes the speed of the ship in knots (1.852 km per hour)
    • Column 3 denotes the longitude of the ship
    • Column 4 denotes the latitude of the ship
  2. Container Ship Information Dataset.csv

    This file contains the information of 4,881 container ships. Each row represents a container ship.

    • Column MMSI denotes the unique ship ID
    • Column LENGTH denotes the ship length in meters
    • Column BREADTH denotes the ship breadth in meters
    • Column CAPACITY denotes the maximum capacity of the ship in TEUs
  3. JOC Top 50 World Container Ports 2011.pdf

    This is a copy of the container port ranking list in 2011 from the Journal of Commerce (JOC), which we use to compare our port ranking with.

  4. Hong Kong Container Terminal Coordinates.txt and Singapore Container Terminal Coordinates.txt

    These two files contain the coordinates of the terminal layouts extracted from digital maps. We provide the data of two sample ports Hong Kong and Singapore.

  5. Hong Kong Container Terminals Facilities.pdf and Singapore Container Terminals Facilities.pdf

    These two files contain the detailed terminal facilities (e.g., QC numbers) of two sample ports Hong Kong and Singapore.

  6. Hong Kong Ship Arrivals.pdf and Port of Singapore Ship Arrivals.pdf

    These two files contain the monthly statistics of container ship arrivals in 2011 and 2012 of the two sample ports Hong Kong and Singapore.

  7. Hong Kong Container Throughput.pdf and Singapore Container Throughput.pdf

    These two files contain the monthly statistics of container throughput in 2011 and 2012 of the two sample ports Hong Kong and Singapore.


REFERENCES

Please cite our paper if you publish material based on this dataset.

	@inproceedings{
	Chen:2014:CTE:2632048.2632050,
	 author = {Chen, Longbiao and Zhang, Daqing and Pan, Gang and Wang, Leye and Ma, Xiaojuan and Chen, Chao and Li, Shijian},
	 title = {Container Throughput Estimation Leveraging Ship GPS Traces and Open Data},
	 booktitle = {Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing},
	 series = {UbiComp14},
	 year = {2014},
	 isbn = {978-1-4503-2968-2},
	 location = {Seattle, Washington},
	 pages = {847--851},
	 numpages = {5},
	 url = {http://doi.acm.org/10.1145/2632048.2632050},
	 doi = {10.1145/2632048.2632050},
	 acmid = {2632050},
	 publisher = {ACM},
	 address = {New York, NY, USA},
	 keywords = {AIS trace, container throughput estimation, open data},
	}