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Detection of Ocean Litter Plastics with Hyper-to-multispectral Infrared Neural Networks (DOLPHINN)

Fri, 05/13/2022 - 15:18
Start Date: 
2020
Programme: 
Discovery
End Date: 
2021
Programme Reference: 
20-D-S-TEC-01-d
Country: 
Canada
Contractor: 
MDA systems
Status: 
Closed
Description: 

The “Detection of Ocean Litter Plastics with Hyper-to-multispectral Infrared Neural Networks” (DOLPHINN) study explored a novel image processing technique to improve the use of space assets to map the distribution of plastic across the globe. The DOLPHINN project objective was to determine the feasibility of using a hyperspectral-to-multispectral association machine learning approach to improve the capability of space-based short wave infrared (SWIR) multispectral assets to detect, quantify, and track plastic litter in waters and on shorelines.

Application Domain: 
Earth Observation
Technology Domain: 
14 - Life & Physical Sciences
16 - Optics
Competence Domain: 
5-Radiofrequency & Optical Systems and Products
Keywords: 
Marine Litter
Remote Sensing
hyperspectral
multispectral
Executive summary: