Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
The Big Picture: An Improved Method for Mapping Shipping Activities
by
Zissis, Dimitris
, Bereta, Konstantina
, Spiliopoulos, Giannis
, Troupiotis-Kapeliaris, Alexandros
, Karantaidis, Giannis
, Vodas, Marios
in
Accuracy
/ automatic identification system
/ Cultural heritage
/ data collection
/ Datasets
/ Density
/ Environmental aspects
/ Identification systems
/ Image analysis
/ Image processing
/ Image reconstruction
/ map visualization
/ maritime traffic monitoring
/ remote sensing
/ Satellite imagery
/ Shipment of goods
/ Shipping
/ Shipping industry
/ traffic
/ trajectory reconstruction
/ vessel trajectory mining
/ Vessels
/ Visualization
2023
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
The Big Picture: An Improved Method for Mapping Shipping Activities
by
Zissis, Dimitris
, Bereta, Konstantina
, Spiliopoulos, Giannis
, Troupiotis-Kapeliaris, Alexandros
, Karantaidis, Giannis
, Vodas, Marios
in
Accuracy
/ automatic identification system
/ Cultural heritage
/ data collection
/ Datasets
/ Density
/ Environmental aspects
/ Identification systems
/ Image analysis
/ Image processing
/ Image reconstruction
/ map visualization
/ maritime traffic monitoring
/ remote sensing
/ Satellite imagery
/ Shipment of goods
/ Shipping
/ Shipping industry
/ traffic
/ trajectory reconstruction
/ vessel trajectory mining
/ Vessels
/ Visualization
2023
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
The Big Picture: An Improved Method for Mapping Shipping Activities
by
Zissis, Dimitris
, Bereta, Konstantina
, Spiliopoulos, Giannis
, Troupiotis-Kapeliaris, Alexandros
, Karantaidis, Giannis
, Vodas, Marios
in
Accuracy
/ automatic identification system
/ Cultural heritage
/ data collection
/ Datasets
/ Density
/ Environmental aspects
/ Identification systems
/ Image analysis
/ Image processing
/ Image reconstruction
/ map visualization
/ maritime traffic monitoring
/ remote sensing
/ Satellite imagery
/ Shipment of goods
/ Shipping
/ Shipping industry
/ traffic
/ trajectory reconstruction
/ vessel trajectory mining
/ Vessels
/ Visualization
2023
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
The Big Picture: An Improved Method for Mapping Shipping Activities
Journal Article
The Big Picture: An Improved Method for Mapping Shipping Activities
2023
Request Book From Autostore
and Choose the Collection Method
Overview
Density maps support a bird’s eye view of vessel traffic, through providing an overview of vessel behavior, either at a regional or global scale in a given timeframe. However, any inaccuracies in the underlying data, due to sensor noise or other factors, evidently lead to erroneous interpretations and misleading visualizations. In this work, we propose a novel algorithmic framework for generating highly accurate density maps of shipping activities, from incomplete data collected by the Automatic Identification System (AIS). The complete framework involves a number of computational steps for (1) cleaning and filtering AIS data, (2) improving the quality of the input dataset (through trajectory reconstruction and satellite image analysis) and (3) computing and visualizing the subsequent vessel traffic as density maps. The framework describes an end-to-end implementation pipeline for a real world system, capable of addressing several of the underlying issues of AIS datasets. Real-world data are used to demonstrate the effectiveness of our framework. These experiments show that our trajectory reconstruction method results in significant improvements up to 15% and 26% for temporal gaps of 3–6 and 6–24 h, respectively, in comparison to the baseline methodology. Additionally, a use case in European waters highlights our capability of detecting “dark vessels”, i.e., vessel positions not present in the AIS data.
This website uses cookies to ensure you get the best experience on our website.