Unprecedented Study Reveals 75% of Industrial Fishing Ships Conceal Locations: Global Fishing Watch Report

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Global Fishing Watch, a nonprofit organization backed by Google, has conducted an unprecedented study revealing that over 75% of industrial fishing ships conceal their locations. These findings shed light on the hidden world of dark fleets, a term used to describe maritime vessels that don’t publicly report their whereabouts. The study, published in Nature, utilized artificial intelligence analysis of global satellite imagery to uncover the extent of humanity’s impact on our oceans.

Maritime watchdogs have traditionally relied on the Automatic Identification System (AIS) to track vessel locations. However, this tool has its limitations, as ships can easily turn off their transponders to stay off the grid. As a result, a significant portion of industrial fishing vessels remains hidden from public view.

To address this data void, the researchers collected 2 million gigabytes of global imaging data taken by the European Space Agency’s Sentinel-1 satellite constellation between 2017 and 2021. Unlike AIS, the ESA satellite’s radar technology can detect surface activity or movement regardless of cloud coverage or time of day. By combining this information with GPS data, the team was able to identify previously undocumented fishing vessels.

The study’s findings challenge previous assumptions and reveal the alarming prevalence of dark fleets globally. Contrary to publicly available data suggesting similar amounts of fishing activity in Asia and Europe, the mapping revealed that Asia dominates the industry, with seven out of every ten fishing vessels found on the water located in Asia, compared to only one in Europe.

In addition to highlighting the concerning reality of dark fleets, the study also sheds light on positive developments. The findings indicate that the number of green offshore energy projects more than doubled over the analyzed five-year period. Wind turbines now outnumber the world’s oil platforms, with China leading the way by increasing its number of wind farms by a staggering 900%.

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This research marks a new era in ocean management and transparency, as satellite monitoring becomes accessible to all nations, rather than limited to those who can afford it. The comprehensive understanding of global industrial fishing provided by this study offers valuable insights for sustainable ocean management.

Overall, the study’s findings provide a balanced view of the world’s maritime industry, revealing both concerning trends and encouraging advancements in offshore energy. The utilization of AI analysis and satellite technology demonstrates the power of these innovative tools in understanding and managing our impact on the oceans. As we unveil the hidden realms of our seas, we gain the knowledge necessary to address the intensity and breadth of human activity at sea effectively.

Frequently Asked Questions (FAQs) Related to the Above News

What is the study conducted by Global Fishing Watch about?

The study conducted by Global Fishing Watch reveals that over 75% of industrial fishing ships conceal their locations, uncovering the existence of dark fleets - maritime vessels that do not publicly report their whereabouts.

How was the study conducted?

The study utilized artificial intelligence analysis of global satellite imagery, specifically data collected by the European Space Agency's Sentinel-1 satellite constellation between 2017 and 2021. This radar technology allowed researchers to detect surface activity or movement of fishing vessels.

What is the significance of this study's findings?

The study's findings challenge previous assumptions about fishing activity and reveal the widespread prevalence of dark fleets globally. It highlights the concerning reality of ships hiding their locations and the need for improved transparency in the maritime industry.

How does this study address the limitations of the Automatic Identification System (AIS)?

The study addresses the limitations of AIS by using satellite radar technology that can detect vessel movement regardless of cloud coverage or time of day. Unlike AIS, which can be turned off, this technology allows for the identification of fishing vessels that were previously undocumented.

What surprising information did the mapping of fishing activity reveal?

The mapping revealed that Asia dominates the industrial fishing industry, with seven out of every ten fishing vessels found on the water located in Asia. This contrasts with previous assumptions that suggested similar amounts of fishing activity in Asia and Europe.

Besides the concerning prevalence of dark fleets, what positive developments did the study uncover?

The study revealed that the number of green offshore energy projects, such as wind turbines, more than doubled over the analyzed five-year period. China, in particular, showed significant progress by increasing its number of wind farms by 900%.

What does this research signify for ocean management and transparency?

This research marks a new era in ocean management and transparency, as it demonstrates the accessibility of satellite monitoring to all nations, rather than being limited to those who can afford it. This comprehensive understanding of global industrial fishing provides valuable insights for sustainable ocean management.

How do the AI analysis and satellite technology used in this study contribute to understanding human impact on the oceans?

The utilization of AI analysis and satellite technology in this study showcases the power of these innovative tools in understanding and managing our impact on the oceans. By uncovering the hidden realms of the seas, this research provides crucial knowledge necessary to effectively address the intensity and breadth of human activity at sea.

Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.

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