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landslide

Google Earth Imagery – Tailings Dam Collapse

March 6, 2017

On 8th August, 2016, a containing dam failed at the Xiangjiang Wanji Aluminium plant in Luoyang, Henan Province in China. About 2 million cubic meters of red mud was released, spreading out over 2 kilometres and burying parts of a village in the process. Luckily, according to this article, no one was killed or injured.

before
after

Before and after of the mudslide.

before
after

Before and after closeup of some of the houses that were buried .

Find the location in Google Earth with this KML file.

We learned about the above disaster via the Landslide Blog.

Similar stories we have covered in the past include another tailings dam failure in Brazil – the Bento Rodrigues disaster, the collapse of a dam containing construction waste in Shenzhen, China, and a major landslide in the Bingham Canyon mine in the US.

Filed Under: Site News Tagged With: landslide

The Kaikoura Earthquake Landslides

November 21, 2016

On November 14, 2016, the South Island of New Zealand experienced a 7.8 magnitude earthquake named the Kaikoura Earthquake after the town of Kaikoura near the quake’s epicentre. The affected region is mountainous with steep slopes and the earthquake resulted in a large number of landslides, including creating some landslide dams (a topic we have covered in the past).

The Landslide Blog has done a number of posts on the Kaikoura landslides (1, 2, 3 and 4). It also mentions this article, which shows a map of the locations of the landslides so far identified using Sentinel 2 imagery.

We thought it would be interesting to examine the sentinel 2 Imagery in Google Earth. The image in question has quite a lot of cloud cover, but in the gaps between the clouds we can see the scars of a large number of landslides. It must be noted that landslides appear to be common in the region, with many landslide scars being visible in older imagery, too. Here are a couple of ‘before and afters’ showing just how many landslides there were in some places.

before
after

After image: Copernicus Sentinel data, 2016.

before
after

After image: Copernicus Sentinel data, 2016.

We processed the Sentinel 2 imagery using GeoSage’s Spectral Discovery.

To explore the Sentinel 2 imagery for yourself using Google Earth download this KML file

Filed Under: Site News Tagged With: earthquake, landslide, sentinel

Processing Sentinel imagery with GIMP

July 13, 2016

Sentinel imagery can be thought of as Europe’s equivalent of Landsat imagery. It is freely available just like Landsat imagery, but higher resolution. Today we are having a look at how to process it in order to view it in Google Earth with the help of GIMP.

Before we begin, if you intend to work with Sentinel imagery a lot, then first have a look at GeoSage’s Spectral Transformer for Sentinel-2 Imagery, as that makes the process extremely easy and adds some additional features that we simply cannot accomplish with GIMP. The only downside is it is not a free product.

In addition, the European Space Agency (ESA), provides a free tool called SNAP for processing Sentinel imagery, but we have not yet managed to figure out how to use it to get imagery into Google Earth.

Obtaining the imagery
The best way we have found for getting Sentinel imagery is from Amazon Web Services (AWS). The first step is to find out what the tile code is for the area you are interested in. To do this, download this KML file, which shows the tiles and tile codes. In our case we were interested in a landslide that occurred near Glacier Bay, Alaska on 28th June, 2016. This turned out to be tile 08VLL. The next step is to go to this page on AWS and find the data for your chosen tile. So in our case, select ‘8’ which represents the ’08’ in the tile name, next select ‘V’ and finally ‘LL’. Then you choose the date you are interested in, in year – month – day order. Imagery is captured about once a week, but it can vary by location. In our case, the only image so far captured after the event of interest was captured on July 11th, 2016. Finally click on the ‘0’ as there is typically only one image for a given day. You should now see a list of files available, and for a standard colour image you only need B02.jp2, B03.jp2 and B04.jp2. Download them by clicking on the links. Each one is about 85 MB.

The imagery can also be obtained here, which provides the imagery in a format suitable for use with SNAP, but the downloads are typically 5 to 6 GB as they include a large area and all the colour bands.

Converting to jpg
The Sentinel imagery is provided in a format known as JPEG 2000 with file extension “.jp2”. Although the JPEG 2000 standard was created in 2000, it hasn’t been very popular and not many programs support it. We believe GIMP has partial support, but it was not able to open the Sentinel imagery. So, we used a free image viewing program called Irfanview to do the conversion. Simply open the files in Irfanview then save them again as “.jpg”. Other free converters exist such as OpenJPEG and ImageMagick, both of which are command line converters.

Combining the colour bands
The next step is to open all three images in GIMP – open one first, then add the others as layers by dragging them into the ‘layers’ pane. To combine them into a single image, select Colors->Components->Compose. Choose RGB as the colour model and select B04 as the red channel, B03 as the green channel and B02 as the blue channel. This will open a new GIMP window with the three layers combined into a single image. It may still look a bit colourless at this stage. Now select Colors->Levels. In the popup window click the ‘auto’ button, then click ‘OK’. The colours should now look a lot better.

At this point our image looked like this:

Glacier Bay, Alaska, Copernicus Sentinel data, 2016.

Note that the image doesn’t fill the whole square and it is actually only part of a much larger image. However, even this piece is larger than we actually want. So, we cropped the image to the area we were interested in, then exported it as a “.jpg”.

Importing into Google Earth
When you use GeoSage’s Spectral Transformer for Sentinel-2 Imagery, as mentioned earlier, the resulting image contains the geographical coordinates and it can simply be drag and dropped into Google Earth Pro. However, our method above does not include any geolocation information, so it must be manually positioned. Open Google Earth, navigate to the approximate location the image was captured then add an image overlay. In the image overlay properties select the file previously created with GIMP. Now adjust the transparency slider (found just below where you selected the image) to about half way, so you can see both the image you are adding and the Google Earth imagery behind it. The default settings allow you to rotate and adjust the size of the image overlay, but force it to remain a rectangle. However, our Sentinel image is typically not exactly rectangular, so go to the ‘location’ tab in the overlay’s properties window and click ‘Convert to LatLngQuad’. This changes the way you adjust the overlay so that you can now move each corner individually. It can be a little difficult to get it just right, but patience usually pays off in the end. Moving each corner adjusts the whole image and puts out of alignment parts that had already been aligned. You need to look for easily recognisable features as close as possible to each corner then match up the overlay with the Google Earth imagery at each corner in turn and repeat several times until they all match. Once you are done positioning it, put the transparency slider back to the right, so that the overlay is no-longer see-through.

Once aligned, this is what our image looked like in Google Earth:


Glacier Bay, Alaska, Copernicus Sentinel data, 2016.

Zooming in to the location of the Landslide:


Landslide near Glacier Bay, Alaska, Copernicus Sentinel data, 2016.

We can also use Google Earth’s measuring tools to find that the area affect by the landslide is about 10 km in length.

To see the above image in Google Earth download this KML file. To get an idea of the size of the event, look at the northern edge of the overlay. There are two cruise ships visible, one in the Google Earth imagery and one in the Sentinel image. They look tiny in comparison to the landslide. If the landslide had gone into the water it could have caused a catastrophic tsunami.

[ Update: Also see this post for more on processing sentinel imagery. ]

Filed Under: Site News Tagged With: alaska, landslide, sentinel

Cylcone Roanu: Landslide and Floods

June 21, 2016

Cyclone Roanu was, according to Wikipedia, a relatively weak tropical cyclone that, nevertheless, caused severe flooding in Sri Lanka and Bangladesh. In addition, it caused a number of large landslides in Sri Lanka. The only imagery of the event so far in Google Earth is two patches of imagery of Sri Lanka: an image of the capital, Colombo, showing flooding and a set of images further inland showing a landslide.

The images were captured soon after the cyclone so they are rather cloudy and the light is poor.


Flooding in Colombo


Flooding in Colombo.


Much of the landslide is covered in cloud.

before
after

 
Before and after of the tail end of the landslide.

To find the locations shown above in Google Earth, download this KML file.

Filed Under: Sightseeing Tagged With: flood, hurricane, landslide, sri lanka

Google Earth Imagery update – April 2016

April 22, 2016

Google has pushed out yet another imagery update, the third this month. The last one included imagery up to April 5th, 2016 and the one before that included up to March 2016. The current one has imagery up to April 11th, 2016, but it also includes a lot of imagery from previous months.


Blue: existing April imagery. Red: fresh April imagery.

To see the map of April imagery in Google Earth download this KML file.

We have only created a map for April imagery so far. It takes up to 24 hours to create a map for a given month, especially when there is a lot of imagery.

On December 20th, 2015, a landslide of construction waste occurred at Shenzhen, China. It toppled and buried a number of buildings, including some workers’ living quarters. The Google Earth image is from February 4th, 2015, so it doesn’t show the immediate aftermath of the disaster. However, we can get an idea of the scale of the disaster from the imagery. For ground level photos taken soon after the disaster see this article.

before
after

Landslide, Shenzhen, China. Slide the divider to compare before and after images.

On January 7th, 2016, a bush fire raged through the small town of Yarloop, Western Australia, destroying 121 homes and much of the town’s other infrastructure. There are now two images in Google Earth from after the fire, one from February and one from April.

before
after

Bushfire, Yarloop, Western Australia. Slide the divider to compare before and after images.

For much higher resolution before and after imagery not found in Google Earth see this website.

To see the above locations in Google Earth download this KML file.

Do let us know if you find any other interesting locations in the imagery.

Filed Under: Site News Tagged With: fire, imagery update, landslide, shenzhen, yarloop

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