Dave Petley wrote a nice article in the AGU’s Landslide blog about a massive landslide in Glacier Bay, Alaska. This huge avalanche of debris was spotted by a local pilot Paul Swanstrom on June 28. When Paul was above it, « dust was still flying ». Later, based on earthquake records in Alaska, the experts figured out that it probably happened at 8:21 am on the same day.


Publiée par Mountain Flying Service sur Mardi 28 juin 2016

Photo of the the Glacier Bay landslide in Alaska by Paul Swanstrom – MountainFlyingService (click on the image to see the Facebook photo album)

 The landslide was estimated to be 10 km long by Paul, but it is not easy to assess the dimensions of a big landslide from plane. Last week @RemotePixel tweeted a beautiful Sentinel-2A image of the landslide.

2016-07-11 Sentinel-2 image over Glacier Bay by @RemotePixel

We could probably use this single image to determine the area of this landslide based on an image segmentation algorithm, however a better option is to take advantage of the high revisit capability of Sentinel-2 to apply a detection change method.

Luckily the Sentinel-2A image of 2016-07-11 was already available in the Google Earth Engine.

Sentinel-2A top-of-atmosphere image acquired on 2016-07-11.

I searched for the most recent image before the landslide. Too bad, it was quite cloudy on June 21st…

Sentinel-2A image acquited on 2016-06-21
Sentinel-2A top-of-atmosphere image acquired on 2016-06-21.

Don’t worry! The observation frequency is high in Alaska because the overlap between the adjacent imaging swaths increases near the poles. Actually there is a clear image taken on June 14.

Color composite view of the Sentinel-2A images. Here I used a false color composite of bands green, red and SWIR1, which highlights the snow cover (in blue) and the vegetation (in red).

Since the debris layer is darker than the snow in the visible part of the spectra, we can compute the difference between the green bands for example.

Grayscale image of the difference between the green bands (after the landslide minus before)

The landslide extent is now even more visible. Yet the time span between both acquisition (28 days) is quite long and some areas in the east appear in dark because the snow had melted over that period… Let’s see if we can reduce this time window with Sentinel-1! Since Sentinel-1 is a radar imaging satellite, we do not need to bother about the clouds and just query the nearest observations after and before the landslide date. However, it is preferable to select similar combination of polarization (VV vs. HH) and orbit (ascending vs. descending). There is an image that was acquired just two days after the presumed landslide date, and another one with similar geometry that was acquired three weeks before.

Sentinel-1 images (VV co-polar band). The S1 images in GEE were pre-processed to backscatter coefficient in decibels after thermal noise removal, radiometric calibration and terrain correction.

The landslide is evident due to an increase in the backscatter coefficient. To determine its extent one can also compute the difference between both images. But before that I applied a refined Lee filter to eliminate the remaining speckle noise as kindly suggested M. Lee himself in my previous post.

Grayscale image of the backscatter difference between the smoothed VV bands (after the landslide minus before)

Now we can compare both Sentinel-1 and Sentinel-2 views of the landslides.

Changes in the Glacier Bay area as seen by Sentinel-1 and Sentinel-2

Then I simply thresholded the images to mask out the areas with little change:

Difference images after thresholding

Then I reduced each blue region to a polygon based on an eight-pixel connect. Yesterday night the Earth Engine was a bit capricious and I could only make the vectorization at a scale of 100 m. The area of the landslide polygon is 18.3 km² with Sentinel-1 and 20.4 km² with Sentinel-2. Today I could run the area computation at a finer scale of 20 m and the results were similar (18.6 km² and 20.2 km²).

Polygons showing the landslide extent from Sentinel-1 and Sentinel-2

Before Sentinel-1 and Sentinel-2 researchers often had to develop detection methods based on post-event data only to study rapid land surface processes. The systematic availability of Sentinel products facilitates multi-temporal analyses.   If you’re not afraid of the Mrs-Armitage-on-Wheels Syndrom, the script to reproduce this post in GEE is here: http://tully.ups-tlse.fr/simon/glacier-bay-landslide

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