Shipmap.org

Shipmap.org

Organisation: Kiln for UCL (United Kingdom)

Publication Date: 04/08/2016

Size of team/newsroom:small

Description

Created by Kiln for University College London's Energy Institute, Shipmap.org is an ambitious interactive WebGL map of commercial shipping movements based on hundreds of millions of data points from throughout 2012 (the most recent year for which all the raw input data was available). The project's aim is to highlight for a broad audience the extraordinary scale of modern commercial shipping, the routes these huge vessels take around the world, the geographic spread of different types of cargo boats, and the amount of carbon dioxide they produce – something possibly only because UCL researchers cross-checked positional data with another database to get the vessel characteristics, such as engine type and hull measurements. The unique base map shows ocean depth and major rivers, while the ships can be viewed as a high-resolution animation of movements over time (the 'ships' view) or as a plot showing all the positions at once (the 'routes' view), optionally colour-coded by ship type. A Talkie voiceover introduction sets the scene and highlights areas of interest on the map.

What makes this project innovative? What was its impact?

The project is innovative in various ways: • This is the first time such a large volume of shipping data (multiple gigabytes) has been visualised interactively • The 'ships' view uses advanced WebGL techniques to allow tens of thousands of points to be smoothly animated simultaneously, even on a phone • Creating the 'routes' view involved compositing more than a quarter of a billion points into two additional sets of map tiles that are layered above the base map • The base map itself was created from multiple raw geographic data sources in order to combine bathymetry (ocean depth) data, major rivers, land masses, and ports • Advance binary encoding techniques are used to compress the data into files small enough for online use • The map's 'data file streaming' system renders each day of data while downloading the next day, allowing it to smoothly animate the entire huge dataset

Technologies used for this project:

JavaScript, Python, WebGL, Mapnik, Talkie
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