Google Earth Blog

The amazing things about Google Earth


landsat 8

Animating Landsat imagery in Google Earth

[ Update: We have updated the KML file with more stable animations and the ability to zoom in and out and pan. See this post for more details. ]

Last week we created a KML file to easily preview the latest Landsat imagery. The data comes from Amazon Web Services (AWS), which hosts a large amount of Landsat 8 imagery and also includes some handy thumbnail images. So, we have now created a KML file that automatically creates animations from the thumbnail images.

Yesterday we had a look at the coverage of Landsat 8 imagery, but we focused on how recent the imagery is. Today’s KML file instead colour codes tiles based on how many images are available. As we noted yesterday, the AWS archive is Landsat 8 imagery only and does not include all the imagery. It turns out that most of the world includes a fairly comprehensive set of imagery from 2015 onward, whereas the US (excluding Alaska) has imagery going back to 2013. The result is that most locations outside the US have about 44 scenes whereas the US typically has nearly twice as many, at about 77 scenes. Note that these figures increase with time as the data is live and a new scene is added to each tile approximately every 16 days.

To see the animations, download this KML file. Click on any coloured tile for an animation of that location. Depending on your internet speed, it may take a short while to load all the images. If you have slow internet or just want to get a quick preview of the animation, then download this KML file which uses smaller, much lower resolution thumbnails.

There are three sliders. The first slider shows the progress of the animation and allows you to manually switch between images. Doing so stops the animation, which you can restart with a button. The second slider lets you adjust the speed of the animation. The third slider allows you to filter the images by removing any with over a specified level of cloud cover.

AWS provides two thumbnails for each scene, one quite small one that we used for our ‘recent images’ KML and one much larger. We have used the larger one even though it is too large to comfortably show at full resolution in Google Earth. To see the animation running at full size, click the link at the top right of the animation window.

Remember that Landsat imagery is very low resolution (about 30m per pixel) and these are just thumbnails, which are even lower resolution than that. So expect to only see very large scale changes. Look for changes in seasons, ice cover changes near the poles, lakes shrinking or growing, and even sand dunes moving.

A major problem is the large amount of cloud cover in the images. If you select only scenes with minimal cloud cover you end up with only a few images to work with. This highlights just how difficult it is for commercial providers to get good imagery.

One problem we had was that the images are not captured from exactly the same angle, so there was a significant amount of shaking in the animations. We have tried to fix this by reading the latitude and longitude metadata included with the scenes and moving the individual images appropriately. It is still not perfect as a browser cannot position an image at sub-pixel resolution.

Let us know in the comments if you find anything particularly interesting. Ideally tell us the path and row.

Here is an interesting tile in Chad that shows some fire scars.

Landsat imagery coverage

Last week we looked at Sentinel imagery coverage and today we are doing the same for Landsat imagery.

First, note that we are discussing Landsat 8 imagery only, as Landsat 7 imagery is not currently available on Amazon Web Services (AWS), which is the source of our information. In addition, we have excluded Landsat imagery captured at night as we do not have the appropriate Row/Path data for night time imagery – although the imagery itself is available on AWS. Also, this page says that although all scenes from 2015 onwards are available, only a selection of cloud-free scenes from 2013 and 2014 are included.

You can see the colour coded coverage map in Google Earth with this KML file. Click on any square to see the date the last image was captured and how old that image is in days. Note that this KML is not dynamic and is based on the data as it was on AWS on August 20th, 2016.

For imagery captured in the last 20 days, we have used this colour range: with red for the most recent imagery and green as the oldest. Anything older than 20 days we have coloured white.

Having a look at the order in which strips are captured, we get a pattern like this:
1   10   3   12   5   14   7   16   9   2   11   4   13   6   15   8
which then repeats after the 16th day. See this post to see an animation of the Landsat orbit.

The imagery of Antarctica is mostly several months old, because it is too dark to capture good imagery over the winter months. There is also a horizontal stripe in the Atlantic and Pacific from February/March 2015 and a vertical stripe from May 2015. We do not know why they were captured, or why the oceans in general have never been captured.

Also of note is that some scenes are recorded with a slightly different scene identifier. Most of the scene identifiers start with the letters LC8, whereas these images start with either LO8 or LT8. There are only a few scenes with these different identifiers. According to this page this means that they include only data from the Operational Land Imager (OLI) or only from the Thermal Infrared Sensor (TIRS), whereas most Landsat imagery includes data from both sensors. We have included separate folders in the KML to show the coverage for the different cases. This page explains what each letter in a Landsat scene identifier means.

Our next project with this data is to create animations with the thumbnails.

Scour marks in the Caspian Sea

We recently came across this story about scour marks on the floor of the Caspian Sea. It is believed the scour marks are caused by ice that forms in the winter months and is then broken up and blown around scratching the bottom of the shallow sea.

The article states that the featured imagery is from Landsat 8. Landsat 8 imagery is freely available and we have featured it a number of times in the past. We thought it would be interesting to download the images and have a look for ourselves. However, when we used our usual source, the USGS’s Earth Explorer to download a quick preview image, the scratch marks are not visible at all.


Low resolution Landsat 8 image.

So, we decided to download the high quality Landsat imagery, 670 MB download. This includes a number of separate images representing different wavelengths which need to be processed to get a high quality full colour image. Previously, we have used an excellent tool from GeoSage, which at the time was free for non-commercial use. However, that is no-longer the case. So, we decided to see whether or not we could process the imagery with GIMP, an open-source image editing program. We are still learning the best way to do it, so we will not give details at this time, but we were successful and the result is seen below:


High resolution Landsat image processed with GIMP.

We then had a look at ASTER imagery for the same location. ASTER imagery has recently been made freely available and can be easily obtained here. The ASTER imagery looks about the same resolution as the high resolution Landsat imagery, but the ASTER website provides it through a handy KML file and it requires no pre-processing at all. The only disadvantage of ASTER imagery is that there appear to be fewer images of any given location than for Landsat imagery.


ASTER imagery.

The Landsat 8 image is from March 21st, 2016, while the ASTER image is from September 28th, 2015. If you look carefully you can see that the Landsat 8 image has a lot of new scratch marks. There is also an ASTER image available from April 23rd, 2016 which shows almost identical scratch-marks to the Landsat 8 image. So it would appear that the scratch-marks last over multiple seasons.

To see the different images in Google Earth download this KML file. Note that we have cropped the Landsat imagery to make the file size smaller. The ASTER imagery will automatically download from the ASTER site when you view it.

Landsat coverage

The Landsat 8 satellite circles the earth in a near polar orbit. See this YouTube video to see an animation of the orbit of Landsat 7 which is identical to Landsat 8 but offset by 8 days. The resulting images are captured in specific spots on the surface of the earth laid out in rows and slightly diagonal columns, which the USGS has numbered and calls the Worldwide Reference System 2 (WRS-2). WRS-2 has been used for Landsats 4,5,6 and 7. Landsats 1,2 and 3 used WRS-1. You can download a KML file here showing the outlines in Google Earth.

Because the Landsat orbit is slightly tilted with respect to Earth’s axis of rotation, the poles are not covered. Strangely, there is also a gap at the antimeridian (the 180th meridian). We don’t know what the reason for the gap is, as the satellite clearly does fly over the anti-meridian. This becomes very noticeable if you turn on ‘historical imagery’ and look at the South Pole:


You can see in brighter white the area not covered by Landsat imagery as well as the odd gap at the antimeridian.

As we have mentioned before, Google Earth has an imperfect join at the antimeridian and if you follow it you will notice a number of glitches in the imagery and there is even a noticeable line in the ocean floor data.


Noticeable glitches in imagery at the antimeridian.

Seeing a tornado track with Landsat imagery

We have looked at the paths of destruction caused by tornadoes in Google Earth imagery a number of times before. Nearly every one of the tornadoes we have looked at in the US occurred in the months of April or May, which appears to be peak tornado season in the US. Tornadoes can, however, occur at any time of year and due to the unseasonably warm weather the US has been having recently there were several tornadoes just before Christmas.

We came across this story, which says that one of the tornadoes had a record long track for the month of December. Google has not yet released any December imagery so we wondered if it would be visible in Landsat imagery. We used the technique described in this post to get a relatively low resolution Landsat image of the area captured on December 24th, the day after the tornado struck and found we were able to just make out the path of the tornado. We also downloaded the higher resolution version of the Landsat data and processed it with software from GeoSage as described in this post.

We were able to trace out the path of the tornado a distance of around 92 km (57 miles). News reports, however, mention damage to property quite some distance from both ends of the visible track (from Clarksdale, Mississippi to Lutts, Arkansas) reaching at least double that distance.


A section of the track as seen in Landsat 8 imagery. Can you see it?

Keep in mind that Landsat imagery has a resolution of about 30m per pixel. The visible track of the tornado is over a kilometre wide in places.

Shown above is only a part of the visible track. For the full track and two different versions of the Landsat imagery (cropped and compressed to keep the file sizes down) download this KML file. The KML also includes markers relating to some news stories and links to YouTube videos of the tornado or other tornadoes in the vicinity.