A new coral reef protection tool has been developed by the American University. Hawaii Manoa researchers utilize cutting-edge artificial intelligence (AI) technology. By developing a new deep learning algorithm, coral ecologists at the University of Manoa School of Ocean Earth Science and Technology (SOEST) can now identify and measure reef halos from space. This research was recently published in the journal Remote Sensing of the Environment.
These features, also known as halos or halos, consist of ring-like patterns of bare sand that occur around coral reefs and are readily visible on satellite images.
“Coral reef halos can be important indicators of reef health and vitality, but until now measuring and tracking them has been a difficult and time-consuming process,” said lead author of the study, Ph.D. said researcher Simone Franceschini.at Madin Labs Hawaii Marine Biology Laboratory (HIMB) at SOEST. “But with this new method, we can accurately identify and measure reef halos on a global scale in a fraction of the time it would take humans to do the same task.”
As one of the most diverse ecosystems on the planet, and relied upon by millions of people worldwide, coral reefs are under threat from overfishing, climate change and many other factors. The impacts of these ecosystems, especially fisheries and marine reserves, on them are notoriously difficult to monitor at scale and over time.
“We aim to develop freely available remote sensing tools to monitor ecological processes at scale to improve our understanding and management of coral reef ecosystems,” says the study. said Elizabeth Madin, senior author of , and associate research professor at HIMB. “Our current research shows that reef halos may represent a new opportunity to monitor the functioning of large-scale reef ecosystems, including in remote and inaccessible areas.”
Better ecosystem analysis, wildlife protection
In recent years, computer vision techniques have been increasingly used to recognize patterns in medical and biological research. In ecology, the application of image analysis and advances in satellite imaging technology have improved large-scale ecosystem analysis and wildlife conservation.
“This research grew out of our team’s understanding of the current state of AI technology and its potential applications in coral reef ecosystem conservation research,” added Madin.
AI technologies have shown good performance in the area of image analysis, but identifying halos (complex and ecological patterns with many variations) has been a challenge that required a combination of various deep learning algorithms.
“Coral reef halos can be very sharp in satellite imagery, with sharp edges and high contrast with background vegetation, but in some cases they are very faint and can be seen by highly trained observers. Sometimes it’s hard to tell them apart,” Franceschini said. “Ultimately, our team was able to consider the diversity of these patterns on a global scale and develop a set of algorithms that can identify and measure halos with amazing accuracy. We are very happy to have built something that can accurately identify over 90% of the halos in the region.”
coral reefs under threat
“This breakthrough is an important step towards expanding our ability to monitor and quantify aspects of coral reef ecosystem health both spatially and temporally,” said Madin. “This new method contributes to the development of global coral reef protection and monitoring tools based on reef halo phenomena by providing a more efficient and effective way to measure reefs and their surrounding halos.” open the way.”
In the near future, the team aims to develop a free web app that will allow conservation practitioners, scientists and resource managers to remotely monitor coral reef health using satellite and drone imagery, quickly and inexpensively.
