Friday’s Food for Thought: Mapping Coral Reefs

A team of researchers from Australia, Bermuda, and the United States are using a NASA Gulfstream jet to modernize the way the world studies coral reefs

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Scientists are employing mapping technology to learn more about coral reefs and visualize the lasting effects caused by climate change.

A team of researchers from Australia, Bermuda, and the United States are using a NASA Gulfstream jet to modernize the way the world studies coral reefs, reports The New York Times. The team equipped the aircraft with a hyper spectral sensor to map the conditions of the Great Barrier Reef from 28,000 feet and produce a real-time picture of how much sand, coral, and algae make up large stretches of the reef. Scientists also want to know how rising sea temperatures, water acidity, pollution, sediment, and overfishing affect reefs over time. According to the article, collecting data from the sky will be more efficient than deploying scuba divers to study a reef that is more than 1,400 miles long and in some places stretches more than 180 miles out to sea. The scientists hope the flights will prove the sensor’s worth and it can later be deployed on a satellite.

LiDAR is also proving useful in helping scientists learn more about reef systems. According to a Forbes article, scientists from Queensland University of Technology used LiDAR data collected by the Australian navy to learn a system of bioherms—mounds of ancient calcified algae scattered outside the Great Barrier Reef—was much larger than previously believed. Scientists who documented the bioherms in the ’80s using acoustic sound waves thought the bioherm network covered an area of about 800 square miles, but the new map showed a network covering more than 2,300 square miles. The team published their findings in the journal Coral Reefs, positing the bioherm network’s vast size and volume may “rival that of the northern Great Barrier Reef coral reefs.”

Photo Credit: Tchami/CreativeCommons

Posted in: got geoint?   Tagged in: Civil, LiDAR, Remote Sensing

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