My Google Map Blog

Google has not updated ‘historical imagery’ for nearly two months, so we have not been able to monitor imagery updates. Just yesterday, a number of new 3D areas were discovered and reported in the comments of this post. We haven’t yet had time to look through them all, but Monument Valley, Arizona / Utah is fantastic. Other than yesterday’s finds, there haven’t been many significant 3D imagery releases in August except for Rio de Janerio, which got an update to the key Olympics locations. We also had a look at Washington D.C. 3D imagery, which was released at the end of July, but it appears to have been removed again. That is probably only temporary.

Monument Valley, Arizona / Utah.

The only major Street View addition this month was a significant expansion to the coverage in Indonesia, including Komodo Island, home to Komodo dragons.

We had a look at the major flooding that struck Louisiana earlier this month. Although Sentinel imagery is relatively low resolution (10 m per pixel) we could clearly see large neighbourhoods had severe floods.
 
 

We did a series of posts on the Sentinel and Landsat imagery available on Amazon Web Services (AWS). We created KML files to allow you to see thumbnails of the most recent images as well as animations automatically created from the thumbnails. In addition, we had a look at the coverage of the two sets of imagery, both by most recent image and quantity of images.

We did a post on how to simulate lakes in Google Earth and GEB reader ‘DJ’ suggested creating a contour line draw-er, so we did.
 
 
 

We had a look at an animation of the Maokong Gondola, a cable car system in Taipei. The animation was created by Steven Ho.
 
 
 

We had a look at various landslide dams around the world. These are dams that are formed when a landslide blocks a river, forming a dam with a lake behind it, often with catastrophic consequences if the dam collapses.
 

We had a look at the India-Bangladesh enclaves and wondered whether we should try to update Google Maps to reflect the fact that India and Bangladesh swapped most of the enclaves so they no-longer exist.
 

We had a go at seeing Antarctic seals in the Google Earth imagery and believe we were successful.
 
 
 

We had a look at DigtialGlobe’s new satellite WorldView-4, that is expected to be launched mid-September. It is similar in capabilities to WorldView-3, so don’t expect improvements in imagery resolution, but rather a greater quantity of good imagery, as DigitalGlobe will have more opportunities to photograph a particular location. Whether this will have a noticeable effect on what we see in Google Earth remains to be seen.

The post The best of Google Earth for August 2016 appeared first on Google Earth Blog.

We have recently been doing a series of posts about Sentinel and Landsat imagery on Amazon Web Services (AWS), including releasing a KML file that automatically retrieves thumbnails of Landsat 8 imagery from AWS and creates animations with them.

We mentioned at the time that the Landsat images are not all perfectly aligned with each other and we had adjusted each image slightly to try and create smoother animations. To do this we used a simplified model that assumed that the imagery squares were all aligned with latitude and longitude, with up being North. It turns out that our assumptions were not valid and there was still significant ‘shake’ visible in ground features in many animations, especially those of Antarctica.

After some investigation we discovered that not only do the Landsat tiles tilt to the right as per the satellite’s orbit, but the images are placed into the thumbnails at an angle, results in further rotations overall.

The imagery on AWS is provided with a file whose name ends with MTL that contains a variety of metadata for the image. This includes the coordinates of the corners of the thumbnails (this is the whole thumbnail including the black areas). If we have two thumbnails offset from each other as shown as the red and green squares in the image below left, then in our animation we need to adjust the top of one of the images by the amount shown as the ‘top offset’. Thinking of it as purely Cartesian coordinates, to work it out in latitude and longitude it involves a series of rotations and translations, which gets rather complicated. However, we realised that instead, we could stick to proper geographic calculations, for which we already have the key routines that we worked out when working on our post on drawing circles in Google Earth. It mostly relies on an open source package called GeographicLib by Charles Karney, with a few additions also by him but not included in the main library.

Above right we see the mid-point (red circle) of the top of the red square, the mid-point (green circle) of the top of the green square, and what is known as the ‘cross track intercept’ for the green point to the thin red line. The cross track intercept is the closest point on a great circle to a location not on the circle. The distance we were looking for is from the red circle to the cross track intercept. Although this all sounds complicated, it is actually only a few lines of code, because all the hard work is done by GeographicLib. We simply repeated this for all for sides and for every frame in the animation and it worked! The animations are now much more stable even over Antarctica.

Our conclusion overall, is that although geographic coordinates can be very complicated, sometimes it is actually easier to work with them than trying to simplify things, as the heavy lifting can be done by ready-made libraries of code.

Because the thumbnails are actually higher resolution than what you can see in the popup, we have also added the ability to zoom and pan the animation. Just use the mouse scroll wheel to zoom in and out and drag the image with the mouse to pan. I am afraid we don’t have a Mac to test on, so we are not sure if this works on Mac. Let us know in the comments if it doesn’t and we will try adding keyboard controls. Remember, these are only thumbnails so don’t expect great resolution when zoomed in.

You can download the updated KML file here. We have widened the size of the popup in the standard version, but if you find it too wide for your screen, then the narrower version can be found here.

The post ‘Stabilizing’ our Landsat imagery animations appeared first on Google Earth Blog.

We recently came across this humorous take on the complicated border between India and Bangladesh. The video mentions that India and Bangladesh had agreed to swap enclaves in 2015 in an effort to simplify the situation. Wikipedia says the same and states that the agreement was ratified on June 6th 2015 and that the physical exchange of enclaves would be implemented in phases between 31 July 2015 and 30 June 2016. So, we immediately had a look in Google Earth, but found all the enclaves still displayed. Google Earth gets its map data, such as roads and borders from Google Maps, but it can often take some time for changes to get to Google Earth. However, in this case Google Maps also shows all the enclaves.

India–Bangladesh border – Google Maps.

So, we checked various other mapping services and found that:
– MapQuest and Open Street Map show the same borders as each other and we believe they share the same data. They do not show all the enclaves that Google Maps does, but do appear to show two large enclaves named Dahagram and Jote Nijjama (names from Google Maps).
– Bing Maps and Here appear to have identical border data and show no enclaves at all. In addition the borders do not exactly match the other services. They are generally lower resolution but not all the differences can be easily attributed to this.

India–Bangladesh border – Bing Maps.

India–Bangladesh border – Here.

India–Bangladesh border – Map Quest.

India–Bangladesh border – Open Street Map.

So which are correct, and where does one get the official border data from? It must be noted that the enclaves along the India-Bangladesh border were not disputed borders, just very complicated ones (prior to the enclave swap). If the border was disputed then it would get even more complicated as there would be at least two ‘official’ versions of the border. In fact, India recently considered enacting a law to control how maps of India, including its borders are shown, with possible fines of up to 15 million dollars for violators.

Do any of our readers know whether all or some of the enclaves no-longer officially exist? It would appear the border can be edited in Google Map Maker, so we could fairly easily get the enclaves removed from Google Maps (and hence Google Earth) if we can find reliable information about which ones no-longer exist.

Another location with complicated borders is Baarle-Hertog, a municipality of Belgium, which consists of 24 separate exclaves inside the Netherlands. Baarle-Hertog has embraced the situation and made it into something of a tourist attraction.

The post India–Bangladesh enclaves appeared first on Google Earth Blog.

We have recently been doing a series of posts about Sentinel and Landsat imagery on Amazon Web Services (AWS). We created tools to let you quickly preview the latest Sentinel and Landsat imagery in Google Earth. We also looked at the coverage pattern for the Sentinel and Landsat imagery and created a way to animate the Landsat imagery. Today we are releasing similar animations for the Sentinel imagery.

To see the animations, simply download this KML file, open it in Google Earth and click on any tile.

There are several differences between this one and the Landsat animations. The sentinel thumbnails are much lower resolution than the Landsat thumbnails, so we don’t provide a link to a larger version. Also, the sentinel images often do not cover the complete tile, so we have provided an extra slider to allow you to filter out tiles based on how much of the tile they cover.

The KML file also shows with colour coding how much sentinel imagery there is, with a range from green to red for 1 to 120 images per tile and white for tiles that have over 120 images. The highest numbers can be found over Europe, which is understandable given that it is a European satellite. The amount of imagery also increases towards the north of Europe, we believe this is because the paths the satellite takes overlap more near the poles, allowing more imagery to be captured. There are also hotspots over deserts suggesting that the images are selected for low cloud cover.

The Sentinel-2A satellite that is gathering the imagery was launched in June 2015. In comparison, Landsat 8 has been around since 2013. However, the Sentinel-2A satellite covers the globe roughly every 10 days, whereas Landsat 8 takes 16 days. In addition, the Landsat 8 archive on AWS only includes selected images from 2013 and 2014 (with significantly more of the US than other parts of the world) and only has the complete set of images from 2015 onwards.

We also find the clouds look whiter and obstruct the picture more in the Sentinel imagery than they do in the Landsat imagery. This may relate to how the imagery was processed for the thumbnail or it could reflect differences in the exact wavelengths the respective satellites use to capture the colour bands.

We came across a few errors in the data, such as mislabelled tiles or missing thumbnails, but they were not significant enough to seriously affect the operation of the animations.

As with the Landsat imagery, it is important to note that this is very low resolution imagery, so expect to only see very large scale phenomena. Also, with only a year’s worth of data there is not a lot of change to see. However, it is a continuously updated service and with the expected launch of Sentinel-2B sometime next year doubling the frequency of imagery, we can expect some spectacular animations in years to come.

The post Animating Sentinel-2 imagery in Google Earth appeared first on Google Earth Blog.