Maritime
Detect and identify vessels in strategic areas of interest, augmenting ships' detection with crucial information from AIS data.
Fuse satellite imagery and ship detection algorithms with AIS data to accurately detect, identify, and gather information on vessels in a specific area.
Intro
Monitoring maritime activity is of great interest for several reasons, from optimizing coastline support to monitoring and tackling suspicious activity. Advances in satellite imagery resolution, accessibility of AIS data streams, and machine learning enable vessel detection and identification to be fully automated.
Overview
High-resolution satellite imagery
Access a vast archive of SPOT 6/7 imagery with a 1.5m resolution or commission the SPOT 6/7 constellation to take images of your AOI for a given period.
Ship detection
Process your satellite imagery with machine-learning algorithms that accurately identify vessels in your area of interest.
Ship identification with AIS data
Fuse AIS data to your ship identification results to provide AIS information, such as vessel name, cargo, and destination. Identify ships without AIS data to detect potential dark vessels.
Detect and identify vessels in strategic areas of interest, augmenting ships' detection with crucial information from AIS data.
Understand maritime transportation globally through the detection and identification of vessels along global shipping lines.
The technical details
High-resolution satellite imagery
Access SPOT satellite imagery
Whether you want to monitor activity in the past or set up monitoring for the future, UP42 has you covered. We maintain access to a vast library of archive imagery from SPOT while also offering a bespoke tasking service that enables you to commission regular or one-off satellite imagery of your area of interest, guaranteeing a low cloud coverage and consistent incidence angle.
Ship detection algorithms
Automatically detect vessels
Run your satellite imagery through an analytics workflow that identifies vessels from large aircraft carriers to the smaller ships that are more likely to be dark vessels. The ship detection algorithm's output is available as a GeoJSON, which can be easily overlaid and visualized with your archive imagery.
AIS data
Gather vessel information
Our Ship Identification processing block fuses AIS data with the Ship Detection block's outputs to provide information on all vessels transmitting data via AIS. This enables access to a wide range of information on registered vessels. It also allows the detection of dark vessels that are detected by the algorithm but for which no AIS data is being transmitted.
API and Python SDK
Easily download or integrate results
The outputs of your entire analytics workflow are easily accessible via API. The Python SDK enables the comfortable download or integration of the results into external tools. The downloaded outputs can be visualized in GIS tools, such as QGIS. Furthermore, the SDK allows the workflow to be triggered automatically or, for larger areas of interest, for the jobs to be parallelized for extra scalability.
import up42
up42.authenticate(project_id="12345", project_api_key="12345")
project=up42.initialize_project()
workflow = project.create_workflow(name="Vessels", use_existing=True)
input_tasks=['oneatlas-spot-aoiclipped', 'tiling', 'ship-detection', 'ship-identification']
workflow.add_workflow_tasks(input_tasks=input_tasks)
parameter = workflow.construct_parameters(
geometry=[13.452029, 52.496316, 13.459797, 52.500888],
geometry_operation="bbox",
scene_ids="DS_SPOT7_201909220949204_FR1_FR1_SV1_SV1_E013N53_03414")
parameter["tiling:1"].update({"match_extents":True})
job = workflow.run_job(input_parameters=parameter, track_status=True)
job.download_results()
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