July 08, 2016

As farmers in Nepal prepare for a fruitful monsoon season, NASA scientist Dalia Kirschbaum anticipates a different impact of the torrential rains— the loosening of earth on steep slopes that lead to landslides.

Kirschbaum oversees a team of scientists who are using data from NASA satellites to design an automated system to quickly identify landslides that often go undetected and unreported. The system scans satellite imagery for signs that a landslide may have occurred very recently. The software is now open source and available to the public.

“We know a high number of landslides occur around this time in Nepal so documenting them is really important, especially to better characterize when these events happen and what impact they have,” said Kirschbaum, a landslide expert at NASA’s Goddard Space Flight Center in Greenbelt, Maryland.

In Nepal, 60 to 80 percent of the annual total precipitation occurs during the monsoon season— as do about 90 percent of landslide fatalities, according to a 2015 report from the United Nations Office for the Coordination of Humanitarian Affairs.

“We’re interested in rapidly and precisely identifying unreported landslides to better understand landslide triggering conditions. This information can improve maps that show which areas are susceptible to landslides, and promote responsible management of resources,” said Aakash Ahamed, who worked on the project at Goddard as part of the NASA DEVELOP Program under NASA’s Applied Sciences Program.

The Sudden Landslide Identification Product, or SLIP, combs through Earth imagery taken from the Landsat 8 satellite, a joint mission by NASA and the U.S. Geological Survey. SLIP analyzes consecutive images of the same location for changes soil moisture and other characteristics, such as muddiness, to identify locations where landslides may have occurred. To mask out areas where false positives could be inadvertently detected, the software also uses topographic information such as hill slope derived from the Shuttle Radar Topography Mission (SRTM) and the Advanced Spaceborne Thermal Emissions and Reflection Radiometer (ASTER) elevation models.

“While the Global Landslide Catalog has already provided some really interesting insight into where and when landslides are occurring, being able to capture

information from satellite-based sources provides a potentially more robust way of figuring out the true frequency and impact landslides can have,” said Kirschbaum, a member of the SERVIR Applied Sciences Team. She also hopes to include citizen science reports of landslides in the catalog as a way to learn about new landslides and validate reported landslides from the SLIP-DRIP products.

The SLIP-DRIP products could also help with predicting landslides, said Ahamed. Scientists can learn how much precipitation it takes to cause a landslide for a certain slope or a certain soil type or how landslide occurrences change during events such as El Niño.

“Most landslides in remote areas go unreported,” said Ahamed. “By detecting these landslides and the conditions that cause them, we hope to improve our ability to predict where and when landslides may occur.”

Other contributors to this DEVELOP project include Justin Roberts-Pierel, Jessica Fayne, and Amanda Rumsey and scientists from ICIMOD.

To access the SLIP-DRIP software, visit https://github.com/NASA-DEVELOP/DRIP-SLIP

Source

http://www.nasa.gov/feature/goddard/2016/using-nasa-data-to-detect-potential-landslides