Coral Reefs from Space
A team of researchers from Arizona State University have generated the first accurate global coral reef extent map by using AI power and satellite data. The project not only delivers an accurate map, but also provides a valuable tool in world-wide coral health monitoring.
Coral Reefs Mapped World-Wide
After tens of thousands of years of surviving natural changes, approximately one quarter of the entire coral reef population is today deemed damaged beyond repair due to stress factors such as climate change (i.e. 30% of the world’s reefs have been destroyed by heat-stress to date), destructive fishing practices (e.g. cyanide fishing, blast/dynamite fishing, bottom trawling, muroami), overfishing and pollution among others. What is more, other two thirds of the coral reefs are under serious threat as well, with UNESCO assessing that the World Heritage Coral Reefs will be completely gone by 2100, unless carbon emissions are drastically reduced.
The loss of the reefs will have grave repercussions for both marine fauna and human coastal habitats alike. Around 4000 species of fish and around 25% of all marine life are dependent on the reefs at some point in their lives, not to mention that they act as a barrier when it comes to sealevel rise, as well as protect coastlines against erosion.
For this reason, many programmes are developed around the globe to study and protect their habitats from further damage. Nonetheless, assessing their exact location is not an easy task. Themain problem faced by researchers trying to mitigate the damage is an inaccurate estimated distribution of the reefs, as the world-wide observational data (e.g. satellite imagery, diver-based observations) comes from diverse sources and methodologies.
AI and Satellites
For the first time, a global coral reef extent map employing a single methodology able to accurately predict the location of shallow reefs has been generated by researchers from the Arizona State University Center for Global Discovery and Conservation Science (GDCS). The proof-of-concept method is able to predict their location with an accuracy of almost 90%.
The method combined thousands of 3.7-meter resolution satellite images provided by Planet Inc. with a convolutional neural network in order to create the map. Due to the massive stream of daily satellite data (over 11 terabytes per day), both neural networks capabilities and supercomputer power were needed in order to analyse all the images.
For training and validating the reef extent prediction model, the researchers have combined satellite imagery and data from the regional Millennium Coral Reef Mapping Project. The model generated a probability map with a threshold of 60% (reef: probability ≥ 60%, non-reef: probability < 60%), which was later used to generate the global coral reef extent map. As a result, the GDCS team has obtained the worldwide location of all coral reefs within 20 meters of water depth.
The map is available online through the Allen Coral Atlas, which represents a cooperative effort between Arizona State University, Vulcan Inc., Planet Inc., University of Queensland, and the National Geographic Society.
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