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Friday, 09 February 2018 01:00

Damage Assessment by Laser Could Focus Post-Earthquake Response

Airborne lidar surveys taken before and after a powerful 2016 earthquake in Japan revealed the potential for such surveys to identify hard-hit buildings quickly.

On 14 April 2016, a magnitude 6.2 earthquake struck Kumamoto Prefecture on the island of Kyushu in Japan. A second quake of magnitude 7 struck 28 hours later. Researchers in Japan took advantage of the unusual occurrence of two strong earthquakes hitting about a day apart, to investigate the prospects for using airborne lidar surveys to hasten rescues from compromised buildings.

Lidar is an acronym for light detection and ranging. The technology uses pulsed laser light to measure distances to a target. When a laser mounted on an aircraft scans terrain below, the resulting data can feed the construction of high-resolution, three-dimensional digital maps. These maps include accurate renderings of the elevations of structures and topographic features within the scanned area.

Most remote sensing data are collected only after an event, but because the M6.2 foreshock was initially assumed to be the main event, an airplane surveyed the area on 15 April using lidar. In this unusual case, however, the airborne survey was repeated 8 days later, after the M7 main shock had occurred, ultimately providing the researchers an unexpected chance to test lidar's usefulness for earthquake damage assessment.

The new study indicates that if there are prequake and postquake lidar surveys of a stricken city, lidar may outperform aerial photography in providing accurate detection of damaged buildings, and the comparison could be automated.

The results suggest that earthquake-prone cities may benefit from regular lidar surveys that would enable them to have an up-to-date basis for comparison when the next temblor strikes. If lidar methods can automatically detect collapsed buildings after an extreme event, they can better inform responders where people might be trapped under rubble or where supplies are needed, said Luis Moya, an engineer at Tohoku University in Japan. He is the lead author of a Natural Hazards and Earth System Sciences paper on the research published last month.

The Kumamoto main shock permanently shifted the ground in some areas. To make certain that they could still compare identical points on each building despite the shifting of entire structures, the researchers corrected the postquake data set using a method that they describe in a 2017 paper. With the surveys realigned and using building footprint data from the Geospatial Information Authority of Japan, Moya and his coauthors examined horizontal and vertical changes between the surveys for buildings with a variety of damage patterns. After analyzing simple parameters that could be used for automatic detection, the research team found that one parameter—the average height difference between the two surveys within the building footprint—had detection accuracy similar to that of all the parameters combined.

When Moya's team evaluated aerial lidar's success at collapsed building detection, it determined that the technique achieved its greatest accuracy (93%) for structures that had lost 0.5 meter or more in height. To come up with that accuracy, the researchers compared their lidar results with the findings from a field assessment of damage conducted by another research group in Japan that was studying the impacts of the same pair of quakes.

Decision makers in earthquake-prone communities should take note of the potential of the lidar methods demonstrated in this study, stated Chris Renschler, a geographer and investigator with the Multidisciplinary Center for Earthquake Engineering Research at the University at Buffalo in New York, when asked about the study. "With the technology getting cheaper, communities may want to do this assessment on a continuous basis, so that they are updated," he said.

In the meantime, Moya isn't waiting for decision makers. His next step is to try to combine lidar data with other sources of data to explore the possibility of identifying damaged structures with only postevent information.

Source: eos.org

Read 286 times Last modified on Friday, 09 February 2018 14:58

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