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historical imagery

Historical imagery density in Google Earth: Part 2

Last week we started on a project to try and map out the density of historical imagery in Google Earth using the Google Earth plugin.

We created a short piece of JavaScript that queries the Google Earth plugin for the number of images available at a given latitude and longitude. We did this every half degree latitude and longitude between 60° N and 60° S and cut it down to every degree longitude between 60° and 80° towards the poles, pausing one second between each one to give Google Earth time to retrieve the data. The result is just over 200,000 points of data, which took several days to generate, running 24 hours a day.

This really gave us a new appreciation of just how big the earth is. DigitalGlobe images cover about a ninth of the size of each square we generated, so at a rough estimate capturing one image per second, would take three weeks to photograph the whole globe. Landsat 8 actually manages to image the whole globe in just 16 days, but takes much lower resolution images, which cover a larger area for each image.

We had discovered with our ‘Chinese map offsets’ map that Google Earth cannot handle very large numbers of icons. However, it seems to have no great difficult with Placemarks that have no icons. You can load the whole dataset without significantly affecting Google Earth’s performance. Download the data here as a KMZ file. You have to zoom in a bit before you see the numbers – which probably helps the performance. If it looks too clustered try changing Google Earth label size to ‘Small’ in Tools->Options->3D View.

The next step was to try and make a heatmap effect. Google Fusion Tables that we used last week has a limit of 1000 points. So we decided to try and create our own in KML. You can download the result here. Again, we are quite impressed by Google Earth’s performance. We did have to optimize it a bit, as our initial attempts did make Google Earth very sluggish. If you have a slow computer you may find even the optimized version is a bit too much when zoomed out. However, performance should improve when you zoom in.


You can make out US state boundaries where aerial imagery sets overlap, and see the Amazon river.

As we noted last week, there are some odd effects in the data, such as high counts just off the coast in many places and some interesting bands in the data. There are also remarkably large numbers in some places. These could be related to how we collected the data or how the Google Earth plugin reports the data.

Historical imagery density in Google Earth: Part 1

Earlier this week when creating the map of Chinese map offsets it reminded us of a project we have long wanted to work on – mapping the density of historical imagery in Google Earth.

When you are in historical imagery and you look at the timeline, you can tell roughly how many historical images there are for the region you are viewing by the number of light blue bands on the timeline.


This location (Rio de Janeiro, Brazil) has a lot of historical imagery.


This location in rural Brazil, has very little historical imagery.

The only way we know of for automating the counting process is with the Google Earth API, and with the deadline for its end of life coming up this December we had better make use of it while we still can.

It will take a while to get the whole world done and decide on the best way to collect the data and the best format to show the results in, but we thought we would share some of our preliminary findings.

We have created a historical imagery density map for Spain and Portugal as seen below.

Strangely, over the oceans Google Earth sometimes reports no historical imagery but in other locations reports unusually high numbers. We are not entirely sure why this is, but it appears to be a bug in the way Google Earth reports historical imagery on the timeline. You can download the above KML file here.

We discovered that Google Fusion Tables has a remarkably easy way to create a heat map from a suitable KML file, as seen above. However the problem with high figures over the oceans drowns out the differences over the land. Nevertheless, there is a clearly more imagery over centres of population.

North Korea – Statues and Uranium

We have looked at censorship of aerial imagery in Google Earth and even noted censorship of 3D imagery. However, censorship rarely extends to satellite imagery, as only the country in which the satellite imaging company is based really has much control over what is released. We believe Israel has their satellite imagery down-sampled to a lower resolution before it gets into Google Earth and Iraq and Afghanistan simply have not had any satellite imagery updates in the last few years. But most of the rest of the world gets uncensored satellite imagery and they can’t do a lot about it. In 2011, for example, we brought you a story about how Sweden was displeased that their censorship of their own mapping products was proving ineffective because of satellite imagery being uncensored.

Today we are looking at a couple of stories about North Korea. It is one of the most secretive regimes in the world, but there is little it can do about satellite imagery and the fact that it is freely available to much of the world via Google Earth.

The first story is this article from 38 North. The article makes good use of Google Earth imagery to monitor key sites related to Uranium mining and refining in North Korea. Google Earth has imagery from 2003 to 2014 for one location and 2004 to 2015 for the other. The article also features an image for one of the locations from Airbus Defence and Space that is not currently in Google Earth. Interestingly, one of the locations has an image from July 8th, 2015 that has been recently added to Google Earth. It is not yet in ‘historical imagery’ so it was likely added in the last week or so.

The second story is this one, which is about the replacement of statues of Kim Il Sung with statues featuring both Kim Il Sung and his son Kim Jong Il. Again, satellite imagery from Google Earth is used to good effect.

To find the locations mentioned in both stories download this KML file .

Although Google hasn’t updated any of its ‘imagery update’ maps since early June it is relatively easy to find updates using the historical imagery feature. You can spot changes visually as you move the timeslider or you can take screenshots of different dates and then compare them using an image editor. As you can see below, North Korea gets quite good coverage, with many locations having more frequent updates than many parts of Europe or the US. Europe and the US do have higher resolution aerial imagery, which we will not be seeing any time soon over North Korea.


Imagery updates for North Korea in Google Earth from May 2015 to date.

Note that there is some new imagery that is not yet in ‘historical imagery’ that is not shown in the above map.

Historical imagery captured on the same day

We have recently spent quite a lot of time looking through historical imagery and reported some of the most interesting finds from recent imagery, including:

However, one thing we noticed and found quite frustrating is that if two or more images are captured on the same day of the same area, Google Earth displays them on top of each other and it is impossible to see the ones that are ‘behind’.

In October 2014, Bermuda was hit by hurricane Gonzalo. Google Earth has four images captured on the same day, October 19th, 2014, soon after the hurricane hit. However, the uppermost image is in black and white and there is no way to see the three colour images apart from where they are not overlapped by the ones above them, which for the most part is over the sea. There are two more images on the 20th which also overlap each other, but that is less of a concern as they are of similar quality. We could not identify any evidence of storm damage in any of the images


The four overlapping images of the aftermath of hurricane Gonzalo.

In May, 2014, there was a large wildfire near Lake McClure in California, USA. Google Earth has some imagery of the region captured soon after the fire including, three images all captured on May 31st, 2014. Two of the images are black and white and one is in false colour. False colour imagery is particularly useful for identifying vegetation differences and would probably have been quite helpful in identifying the extent of the fire. Sadly, the false colour image is mostly covered by the two black and white images.


Overlapping images captured soon after the Hunters Fire.

There is also a black and white image from May 30th, and two overlapping images, one black and white and one false colour from June 1st. We think we have identified the extent of the fire by comparing more recent imagery with imagery from before the fire, as well as a bluish patch in the false colour image.

In February 2015, Australia was hit by tropical cyclone Marcia, causing flooding in many places. The Northern Territory towns of Galiwinku and Ramingining have imagery captured soon after the cyclone and again there are overlaps. However, in this case it is not so serious as the quality of the overlapped imagery is similar to the images we can see. The images are not very high resolution, but we can see clear signs of storm damage in both locations.


Ramingining, Australia. You can see trees flattened and on the roofs of houses and some water still on the ground in some places.

The reason why there is a problem with overlapping imagery is because Google dates their imagery to the nearest day. Although the Google Earth timeline is capable of distinguishing dates and times down to a minute, because the images’ date stamps are identical, Google Earth must show both at the same time. The solution would be for Google to add different times to any overlapping images that occur on the same day. It is likely that the actual time the images were captured is known by Google, but if not, a dummy time such as a few minutes after midnight could be used.

To find the locations mentioned in this post in Google Earth use this KML file.

2015 Brazil floods in Google Earth

Earlier this week we looked a flood damage in Georgia and Texas. Thank you to GEB reader for pointing us to imagery of flooding in Magdeburg, Germany in 2013. Find it in Google Earth with this KML file .

We have been aware for some time that there was major flooding in Brazil earlier this year, but have not until recently been able to find relevant imagery. We felt the need to include the year in our post title as a quick internet search revealed the fact that Brazil appears to have had severe floods nearly every year in recent history.


A small settlement near the town of Benjamin Constant, Brazil. Although it is certainly flooded, closer inspection reveals that there are raised walkways between the houses and high water levels are probably common. It is hard to tell from the satellite imagery whether the flooding was severe enough to have caused damage.


Coari, Brazil. Yet again, clearly flooded, but walkways exist in the flooded streets that can be seen in older imagery, suggesting flooding is common and prepared for.

Despite the flooding affecting a very large area (over 2000 km of river) we were only able to find a few relevant recent satellite images. However, we did discover the International Charter “Space and Major Disasters” and they have a number of recent satellite images of the area and before and after comparisons of the imagery – usually using Google Earth imagery for the “before” image.

To put them in context we have created a set of Placemarks for Google Earth with links to the relevant “before and after” comparisons. Download this KML file to view them in Google Earth.