Authors 1.Email: isaacdura@heraspace.com
- Paper number
IAC-20,B1,IP,18,x56880
- Author
Mr. Isaac Durá, Germany, HeraSpace UG
- Year
2020
- Abstract
“Exploring fish stocks sustainable management with EO Copernicus satellite data and AI” More than 10 years ago, ESA kicked off the Technology Transfer Programme Office (TTPO). Their mission is to inspire, and to facilitate the use of space technology, systems and know-how for non-space applications. ESA has been very active promoting this program in the entrepreneurial scene. For example, the ESA sponsored the Junction hackathon in Helsinki in November 2016, where there were more than 1,400 competitors. ESA awarded one of the two main prizes to the application HeraSpace for the best idea for the Arctic. Today, HeraSpace is a Copernicus Accelerator Alumni and has been selected to be incubated at the ESA BIC Darmstadt. HeraSpace helps fishermen to locate the most profitable and sustainable fishing grounds, optimizing operating budgets while reducing environmental impacts. The system supports healthy food production, income, employment, and sustainable fishing, as described in this Copernicus use case. HeraSpace dynamically predicts and updates fish distribution patterns. By combining Copernicus satellite data with actual fishing data, the selection of optimal fishing grounds can be drastically improved, as well as the efficient routing of vessels to those locations. Particularly interesting are the features aimed at supporting sustainable exploitation of ocean resources, promoting circularity (circular economy), low carbon activities by the seafood companies, and the support of current and anticipated environmental regulations by global governments and regional fisheries authorities. The key spatial state-of-the-art technology providing improved accuracy, increased temporal coverage and improved spatial resolution is the Copernicus Sentinel 3A-B OLCI Level 2 instrument, a continuation of ENVISAT-MERIS. The technologies used are data from the Copernicus Sentinel 3A-B OLCI, SRAL, SLSTR L2, the Sentinel 2 MSI instrument data products (10 metres resolution), and the multi-mission CMEMS products. Sentinel 3A has already been calibrated and validated (ongoing) with in-situ devices. Data from the second satellite, Sentinel 3B, will be available in the middle of 2018. HeraSpace also uses CMEMS multi-mission products, which are mostly mature already. The high quality, near-real time data retrieved from Sentinel 3 includes variables like temperature, salinity, water depth, and dissolved oxygen levels. These data are supplemented with near-real-time data from the Sentinel 2 SMI from ESA and additional technologies from other government space agencies like NASA. HeraSpace proposes a core machine learning algorithm that will “learn” and successfully apply satellite oceanography patterns to fish behaviour. As the algorithm is applied in a real scenario with an integrated customer feedback loop, the more accurate it becomes. It helps fishermen by forecasting the closest legal fishing grounds, dynamically updating fish distribution patterns that may become outdated due to climate change, fishing pressure, migration patterns, or typical interannual variability.
- Abstract document
- Manuscript document
(absent)