AIS Data Visualization for Maritime Spatial Planning (MSP)

Abstract: 

AIS data help with understanding where are important areas for navigation and fishing. However, extracting routes from AIS data sets is generally not easy, because of the quantity of data that needs to be handled and associated computing capacity. This innovative approach for reducing the data volume shows a more time and ressource efficient way of visualsing AIS data.

Year: 
2016
Application in MSP: 
Unknown effect
Sectors: 
Ports
Shipping
Type of Issue: 
Data
Type of practice: 
Methodology
Stage of MSP cycle: 
Stocktake

Questions this practice may help answer

  • How can one visualise AIS data for MSP in a less time- and resource-consuming way?
  • Which software is suitable for visualisation?

Implementation Context

AIS data help with understanding where are important areas for navigation and fishing. However, extracting routes from AIS data sets is generally not easy, because of the quantity of data that needs to be handled and the associated computing capacity.

Objectives

The aim is to provide an innovative approach to visualise shipping routes with AIS data with open source software.

Method

Data are imported from a source into a database.  The authors used data from October 2015 from the source exactEarth.

The database was a PostgreSGL database with PostGIS extension. The data was imported into a table. This table has a many rows and a considerable number of columns. The size of this database was reduced  i) by reducing the number of columns from 139 to six as well as  ii) aggregating the number of records in the rows. This is done by grouping records based on spatial proximity, i.e. AIS records that are close to each other in terms of latitude and longitude values were aggregated to a single record. The initial table had a total of 91,324,868 rows. This was reduced to 216,466 rows.

The aggregated data set is sent to a server for sharing the geospatial data in a format that can be visualsed in a map. In their study, the authors chose a data format that complies with Open Geospatial Consortium standards. GeoServer is used to visualise the data on a map, .

 

 

Main Outputs / Results

The result is a traffic density map that allows filtering for particular features, e.g. vessel types.

Contact persons

  • Michele Fiorini, The Institution of Engineering and Technology, Italy Network
  • Andrea Capata, Meetatnine Srls,
  • Domenico D. Bloisi, Dept. of Computer, Control, and Management Engineering, Sapienza University of Rome

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