Maps not only have the power to help us trace a location but can save loss of lives and protect the planet and its ecosystem. Here is an apt example where with the help of high-resolution maps depleting coral reefs can be protected.
One such project which has the true potential to address this grave issue is Allen Coral Atlas. First, of its kind, the project entails high-resolution maps of all coral reefs around the world with the help of data gathered from Planet Labs.
How does it work?
The motive of the project is to identify and map regions covered by reefs. With the help of Planet Labs’ satellite imagery, the process of mapping has become quicker and more accurate. By 2020 researchers hope to map each and every coral reef in detail which will help in extensive monitoring of the reefs.
Recently at the Ocean Conference held in Bali, Indonesia, first detailed maps of five coral reefs were released where automated processes for classifying the satellite images are still on. To make these raw images more suitable for mapping corals, the Allen Coral Atlas has taken the help of an ecologist Greg Asner of the Carnegie Institution for Science. Asner’s team has worked hard with Planet Labs to strip the images of visual elements that cover the reefs like the atmosphere, the sun’s reflection off the sea, the clouds and the sea water itself.
Once Asner’s team and Planet Labs clean up the images they transfer the photograph off to the University of Queensland where a team led by Stuart Phinn and Chris Roelfsemauses classify each image as coral, rock, algae, sand or other materials.
Setting alarm system for corals
Once the Allen Coral Atlas has mapped Earth’s reefs, its goal will be to monitor these reefs for flashes of short-term change, acting as a global coral alarm system.
The idea is to scan Planet Labs’ images for sudden changes in brightness within the pixels that correspond to live coral reefs. If a patch of coral quickly lightens, the coral may have bleached, or perhaps blast fishing has shattered a reef and exposed the corals’ white skeletons. If corals quickly darken, it can be a sign of algae, either growing over the corals themselves or blooming in the water nearby. The project also aims to highlight natural resilient ‘super corals.’
Also Read: Satellite imagery shows surface area of rivers and streams is 45 percent higher than anticipated
Picture Courtesy FRANS LANTING
What led to Allen Coral Atlas?
Interestingly Microsoft co-founder and philanthropist Paul Allen was an avid SCUBA diver. Even though he was already funding coral research, his real concern grew in 2017 when he found that most of his favorite reef dive sites were getting bleached and sickened.
The project takes on new meaning since the recent deaths of its two driving forces: Microsoft co-founder and philanthropist Paul Allen, who funded its creation, and Hawai’i Institute of Marine Biology director Ruth Gates, one of the project’s scientists. Allen died suddenly on October 15 from non-Hodgkin lymphoma, and Gates died on October 26 from brain cancer.
“Ruth Gates was one of the world’s most visionary, passionate and committed voices for science, conservation, and coral reefs,” said Andrew Zolli, the vice president of global impact initiatives at Planet Labs, in an email. “Her spirit animated our shared work from the outset … Even in grief, we are energized by her example and her fierce urgency, and doubly committed to seeing her vision realized.”
So, too, with Allen. “It has been really hard, but the important thing is how we deliver on the mission that Paul set out for us,” says Lauren Kickham, the director of project management at Vulcan, the company that oversees Allen’s business and philanthropic ventures.
Gates, whose research Allen funded, helped bring together the project’s brain trust. In the summer of 2017, Gates met Zolli. The pair realized that they knew the same researchers at the Carnegie Institution for Science and invited them to join the project. In short order, the University of Queensland, too, came on board.
Also Read: The tremendous potential of Machine Learning in satellite imagery
