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Snapsat Beta for Landsat imagery

mer 04-05-2016

We have previously had a look at how to get Landsat imagery into Google Earth. We have used a number of different techniques over time, but in all cases, obtaining high quality Landsat imagery required a large download (typically over 700 Mb) and several stages of image processing to combine multiple bands into a full colour image.

We recently discovered Snapsat, a website dedicated to making it easier to obtain processed Landsat imagery. In March last year, Amazon announced the availability of Landsat data on Amazon Web Services (AWS). Snapsat builds on the AWS, offering to provide easy access and processing of the Landsat data. It appears to have been set up mid last year not long after the Landsat data was made available on AWS but not much work appears to have been done on it since then. However, it still works well and makes obtaining processed Landsat imagery remarkably easy. Learn how to use it here.

As we mentioned in this post there was a Tornado which struck Dallas, Texas in December last year. There is no imagery yet in Google Earth showing the main path of destruction. So we tried out Snapsat by downloading a Landsat image of Dallas from January 12th. The process was straight forward and only required a download of 107 Mb as opposed to the 772 Mb required to download the same imagery from Earth Explorer. And we can see the track of the tornado.


Tornado track, Dallas, Texas, as seen in Landsat imagery. Ends of the track marked with arrows.

There are, however, a few disadvantages to using Snapsat. The website does not do pansharpening, a process whereby a higher resolution grey-scale image is used in combination with the three colour bands to create a higher resolution image overall. This means that the imagery obtained via Snapsat is not the highest quality possible. Another issue is that the downloaded file does not include Geo-coding information so it cannot be automatically imported into Google Earth Pro. However, since we usually have to crop the imagery anyway, manual positioning is often necessary and not very difficult.

We got the same image from Earth Explorer and used GIMP to process the imagery (very inexpertly) and the result is noticeably sharper because of the pansharpening.


Tornado track, Dallas, Texas, as seen in Landsat imagery, with basic pansharpening via GIMP

To see the two overlays in Google Earth download this KML file.

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Catégories: Sites Anglophones

What’s that image: Earthquake and floods

mar 03-05-2016

Yesterday we mentioned that Google had pushed out an imagery update towards the end of April. Today we are having a look at some of the sights we have found so far.
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On April 16th, 2016, Ecuador experienced an earthquake of magnitude 7.8. Google Earth has three satellite images captured the day after. All three images seem to have a bug where you cannot see the previous image in historical imagery but have to go back two dates to see prior imagery. Perdenales, Ecuador was not far from the epicentre of the earthquake and a number of buildings collapsed. The satellite imagery is not very high quality, but the devastation is visible if you look closely. To identify collapsed buildings, look for rubble in the streets rather than at the buildings, then compare with older imagery. See the fourth image in the slideshow in this story to see an aerial view.

Collapsed buildings in Perdenales, Ecuador.

Further south, in the town of Portoviejo we found a collapsed building as well as signs of minor flooding.

Collapsed building in Portoviejo, Ecuador.

The southern United States seems to have experienced a lot of flooding lately. Earlier this month we had a look at the flooding of the Mississippi River, which took place in January this year. There are now a number of images captured in mid March that show flooding in Texas and Louisiana.


The Sabine River floods Deweyville, Texas.


The Red River in flood near Coushatta, Louisiana.


The Ouachita River, Louisiana.

There are also satellite images of Austin and Houston, Texas, captured on March 12th. We are not sure if they relate to flooding and have not yet identified anything unusual in the images.

There has been further flooding in April, but there is not yet any relevant imagery.

For the locations featured in this post download this KML file. We have included in the KML some data from the USGS showing the epicentre of the quake and the area of impact.

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Catégories: Sites Anglophones

A year of imagery updates in Google Earth

lun 02-05-2016

As we mentioned last week, Google did at least four imagery updates in the month of April. It takes long time to do imagery update maps and since imagery updates include imagery over a number of different months it could take up to a week to do maps for the last few months. So we thought of changing our algorithm to do them all at once. This is faster overall but still takes days to complete. We also decided to do the last twelve months, since it wasn’t too much extra trouble to do so. We are not yet done with the high resolution maps, but we can give a good idea of where updates were done over the past year.


Imagery updates over the past year – May 2015 to April 2016

The above animation uses NASA’s Blue Marble images taken from the animation that Frank did back in 2006. We did not include the poles in our imagery update maps, so there may have been some imagery updates for Antarctica and northern Greenland that we have missed.

Notice how the imagery avoids the snow line in the northern hemisphere. The pattern in the tropics is not as clear as the map we did last week showing how seasonal Google Earth imagery is.

You can also see the animation in Google Earth using this KML file.

For best results:

  • adjust the timeline control so that the two parts of the slider are snapped together.
  • in the timeline control settings dialog, set the animation speed to maximum, and tick ‘loop animation’.
  • press the ‘play animation button’ on the timeline control.
  • you may have to wait for a few loops of the animation for all the images to load properly.

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Catégories: Sites Anglophones

The best of Google Earth for April 2016

ven 29-04-2016

Google has pushed out new imagery at least four times this month. 1, 2, 3, and a very recent update that we haven’t covered yet!

We found quite a lot of interesting sights in Google Earth imagery this month, including:
* Nyssa, a very large painting by Jorge Rodriguez-Gerada.
* Super Bowl celebrations in Denver Colorado.
* Mississippi flooding.
* A collapsed building due to an earthquake in Taiwan.
* A train crash in Germany.
* Flooding in India, Tanzania and Brazil.
* Demolished buildings in Zaria, Nigeria, indicating a possible cover up of mass killings.

We did a series of posts attempting to estimate the size of the Google Earth database and how much space the different types of imagery require. First we looked at 3D imagery, then different types of 2D imagery, moved on to historical imagery and finally put it all together and came up with a very rough estimate of 3 Petabytes!
 

We created a map showing the most popular times of year for capturing imagery in different parts of the world. The resulting pattern was very interesting. In the extreme latitudes, there is a lot less imagery captured in the winter because of snow cover and, as GEB reader Chris pointed out, the shorter days and longer shadow make gathering good quality imagery more difficult. In the lower latitudes the situation is reversed, with more imagery gathered in the winter, most likely because there is typically more cloud cover in the summer months.
 

We had a look at some scratch marks on the floor of the Caspian Sea and compared the view from Landsat imagery and ASTER imagery. We forgot to mention that the area also has DigitalGlobe imagery from 2005, which also shows scratch marks.
 
 

We had a look at the Sentinel missions and hope to cover them more in later posts when we have learned how to process the imagery. Thank you to GEB reader ‘mzuehlkeMarco’ for pointing us to a tool called SNAP for processing the imagery.
 
 
 

We had a look at some examples of land reclamation that can be seen taking place in Google Earth imagery.
 
 
 
 

We had a look at some strange buildings in the desert and decided they are Surface to Air Missile (SAM) sites, which it turns out are remarkably common and easy to identify in imagery once you know what to look for.
 
 

At the end of March, Tesla unveiled the Tesla Model 3 and we had a look at Lithium mines around the world, which may supply the necessary Lithium for the Tesla cars.

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

Catégories: Sites Anglophones

The Sentinel Missions

jeu 28-04-2016

The satellite Sentinel-1B was launched earlier this week. It is the second satellite of the Sentinel-1 mission, the first of which, Sentinel-1A, has been in orbit since April 2014. Together they operate as a team to cover the whole planet every six days. They are not optical satellites but work with radar, which can operate day or night as well as see through clouds. They follow a polar orbit similar to the one used by the Landsat satellites, whose coverage pattern you can see here. We believe this map showing the deformation after a large earthquake in Chile last year was created using data gathered by Sentinel-1A.

The Sentinel Missions are developed by the European Space Agency (ESA) on behalf of the joint ESA/European Commission initiative GMES (Global Monitoring for Environment and Security). They are in many ways similar to the Landsat missions. The Sentinel-2 mission consists of optical satellites with similar orbits and coverage to the Sentinel-1 satellites. Sentinel-2A was launched in June 2015 and Sentinel-2B is expected to be launched sometime this year and there may be more, 2C and 2D, to be launched in 2021 or later. Sentinel-2A has a resolution of about 10 m per pixel, which is better than Landsat 8, which is 30 m per pixel.

Data from the Sentinel missions can be obtained here. It requires registration, but the Terms and Conditions suggest that anyone may use the data for almost any legal purpose, although correct attribution is required. We tried downloading data from Sentinel-1A, but did not know how to process the data, so all we saw was a completely black image. We then decided to get an image from Sentinel-2A of Mt Egon, Indonesia. It is a volcano which erupted on January 19th, 2016. We chose an image dated January 20th, 2016, which was a 4.4 GB download. Again we didn’t know how to process the imagery and could only see it in black and white and could not see anything of interest around the volcano.

So, it would appear that at the present time, Sentinel data is hard to access for the casual user. However, this article suggests that that may change, with a new plan to analyse the data being gathered and open source the results.


The best we have managed to achieve so far. Copernicus Sentinel data 2016.

If any of our readers knows the easiest way to obtain and process Sentinel data please let us know in the comments.

The post The Sentinel Missions appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Scour marks in the Caspian Sea

mer 27-04-2016

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.

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Catégories: Sites Anglophones

Google Earth preferred seasons for gathering imagery

mar 26-04-2016

Whenever we look at imagery update maps we notice certain patterns in the updates. One of the factors that causes these patterns is seasonality. We have long known that Google avoids snow cover in imagery where possible. This means that they largely avoid capturing imagery in winter in high latitudes. We thought it would be interesting to use the Google Earth API to see how strong an effect that was. The results were quite interesting and not what you might expect.

We used the Google Earth API to scan the globe and for a given location check all the dates of available historical imagery then calculate which was the most frequent month. We then colour coded the months with an approximately seasonal colour scheme and created a map. Redder colours indicate northern summer and bluer colours indicate northern winter.

To see the map in Google Earth download this KML file

As initially expected, the far north and far south are dominated by imagery captured in the summer months of the respective regions. However, this trend does not hold throughout and there is a reversal in the tropics. This is because of cloud cover. In the tropics, cloud cover roughly follows the sun, with rain mostly occurring in the summer and clear skies occurring in the winter. There are exceptions, such as along the coasts, where rainfall patterns are affected by the ocean, and deserts where there is low cloud cover year round.

Overall, the patterns are quite distinctive and it is clear that when imagery updates occur is strongly affected by cloud cover and snow cover.

Notes:
A lot of aerial imagery in Google Earth does not have a specific date, but rather a date range. The start date is shown in the status bar and the end date on the ‘historical imagery’ timeline. Our map was using the end date. Some aerial imagery, especially the very old imagery, just has a year and this resulted in our algorithm seeing it as ‘December’. This is the reason for the United Kingdom and parts of Europe showing dark blue (December).

When there was more than one maximum, we picked one at random. This is not ideal, but was sufficient for showing general trends.

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Catégories: Sites Anglophones

Mass killings in Zaria, Nigeria

lun 25-04-2016

In a recent press release by Amnesty International there is a story about a cover up by the Nigerian army of a mass killing of over 350 people in the town of Zaria, Nigeria, in December 2015.
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The article mentions a possible mass grave visible in satellite imagery. However, no coordinates are given so we were unable to identify the location in Google Earth. This article includes a screenshot of the location from Google Earth, but again, does not give coordinates. However, it does include a map of a number of buildings that were completely destroyed. Based on the map we were able to locate them in Google Earth as seen below:

Hussainya

Shrine of Ibrahim Zakzaky’s Mother

Fudiyyah Islamic Centre

Darur-Rahma

IMN Recording Studio Film Village

Ibrahim Zakzaky’s Residential Compound

To see the above locations in Google Earth download this KML file. If any of our readers manages to locate the suspected mass grave site please let us know in the comments. A ground level photo suggests it is near some overhead high voltage power lines.

Although the imagery above does not prove that there was a mass killing, nor directly implicate the Nigerian army in a cover up, it can be used to corroborate witness testimonies. We believe that as satellite imagery becomes more frequent and more readily available, it will become increasingly important in cases like this. We would also like to comment that not enough news outlets include coordinates when showing satellite imagery. It is important to allow readers to be able to confirm imagery for themselves by looking it up in Google Earth or other sources.

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Catégories: Sites Anglophones

Google Earth Imagery update – April 2016

ven 22-04-2016

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.
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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.

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.

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.

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Catégories: Sites Anglophones

Explore Google Earth on Earth Day

jeu 21-04-2016

April 22nd is Earth Day, which we traditionally celebrate by looking back at some of the environment related stories of the past year.

Japan and NASA made the imagery from ASTER available to the public for free. Thank you to GEB reader ‘sanchezpaus’ for letting us know that the ASTER imagery is better resolution than satellite imagery at 15 m per pixel for ASTER imagery vs. 30 m per pixel for Landsat. This means the vast imagery database will be of significant interest to people doing environmental research that requires satellite imagery.

We had a look at the increased frequency of earthquakes in Oklahoma. Google Earth combined with data from the U.S. Geological Survey (USGS) makes an excellent tool for studying the geographic distribution of earthquakes with time.
 
 

We heard about an ice sheet in Antarctica slowly cracking and used Landsat imagery to watch it crack in Google Earth.
 
 
 
 

We had a look at a phenomenon known as ‘fairy circles’ and earlier in the year had a look at the patterns made by ant and termite nests.
 
 
 
 

Google’s Skybox Imaging was renamed Terra Bella to indicate a change of focus from just a satellite imaging company to pioneering the search for patterns of change in the physical world. We expect to see a number of environment related projects come out of Terra Bella in the future.
 

Google updated the Google Earth sea floor map with higher resolution data from a variety of sources, including the Scripps Institution of Oceanography, University of California, San Diego and the Lamont-Doherty Earth Observatory.
 
 

We had a look at a tool called Open Foris that works with Google Earth to make mapping land use and land use change easier.
 
 
 
 

We had a look at a tool that is very similar to Open Foris, but uses the Google Earth API. It was used to map land use in East Africa to aid in the study of African Wild Dogs.
 
 
 

NASA Near Earth Observations (NEO) data is a large collection of multi-year global datasets. We had a look at how to import them into Google Earth and make animations from them.
 
 
 

We had a look at various resources for tracking wild fires in Google Earth and also had a look at the scars left behind by some large wild fires in California using Landsat imagery.
 
 
 

The Catlin Sea View Survey is a project to document the worlds reefs in 360 degree panoramic photography. The results can be seen in Street View. We had a look at it on World Oceans Day last year.
 
 
 

We had a look at some average cloud cover maps from NASA.
 
 
 
 
 

Rebecca Moore, Engineering Director for Google Earth and Earth Engine & Outreach wrote an interesting article about three projects (Global Forest Watch, Project Sunroof and Methane Maps) that Google is doing in collaboration with others using technology to achieve sustainability goals. We discussed the possible reasons why Google Earth was not used in these cases.

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Catégories: Sites Anglophones

Phallic symbols in Google Earth

mer 20-04-2016

A recent story in the news is about a school in Sydney Australia where someone drew some phallic symbols and a rude message on their lawn. They apparently managed to remove the unwanted graffiti within hours, but not before it was captured in aerial imagery, which has since been added to Google Earth.


The offending image in Google Earth. Clancy Catholic College, Sydney Australia

It turns out this sort of thing is quite common and especially common in schools.


Bellemoor School, Southampton.


Harman-Geist Stadium, Hazleton, Pennsylvania.


Yarm School, Teesside, United Kingdom.


Fairfield College, New Zealand.


Koonung Secondary College, Melbourne, Australia.


A field on the Isle of Wight

There are probably many more that we have not come across.

It is not a new idea, with the Cerne Abbas Giant dating from at least the 17th century


Cerne Abbas Giant, Dorset, United Kingdom.

There are also many examples of unintentional phallic symbols.


Newmarket Health Centre, Ontario, Canada.


A park in Des Moines, Iowa.


A housing estate in Hoylake, Wirral, United Kingdom.


A peninsula on New Providence Island, Bahamas


A Church in Dixon, Illinois.

For the locations featured in this post download this KML file.

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Catégories: Sites Anglophones

Watching land reclamation with Google Earth

mar 19-04-2016

Last month we did a couple of posts showing the growth of artificial islands in Google Earth:

Today we are looking at large land reclamation projects. As before, we have only selected projects that show significant change within the range of Google Earth imagery.

South Korea has several land reclamation projects. Songdo International Business District is a ‘smart city’ built on 600 hectares of reclaimed land on Incheon’s waterfront. It is still in development, but already has many sky scrapers, including South Korea’s tallest building, the Northeast Asia Trade Tower.

Songdo International Business District, South Korea.

Saemangeum is an estuarine tidal flat which has been dammed by the Saemangeum Seawall Project, which is now the longest man-made sea barrier in the world. Filling in the land behind the wall is still in ongoing, as construction of the wall and subsequent land reclamation has been slowed by court cases over the environmental impact it is having.

Saemangeum, South Korea.

Next we look at Jakarta, Indonesia. What we are looking at is a tiny part of a much bigger planed project seen here. The project is controversial as can be seen in this article

Jakarta, Indonesia.

Singapore has a lot of reclaimed land. We look at an extension to Coral Island. There is no imagery showing the land itself being reclaimed from the sea, but we can see it being developed.

Coral Island, Singapore.

Next we move to Bohai Bay, China, which is also the site of the Tianjin explosion we have previously featured.

Bohai Bay, China.

Next we look at Colombo harbour, Sri Lanka. Colombo harbour was expanded and now there are plans to add Colombo Port City on reclaimed land adjacent to the harbour.

Colombo harbour, Sri Lanka.

Copenhagen, Denmark, shows some land reclamation taking place:

Copenhagen, Denmark.

The Khazar Islands, Azerbaijan, is a land reclamation project in the Caspian Sea. The Azerbaijan Tower may be built on it, and when completed may be the tallest building in the world.

Khazar Islands, Azerbaijan.

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

animateImages([{id:"ColomboPortCity",qty:14},{id:"Saemangeum",qty:7},{id:"Khazar-Islands",qty:5},{id:"Songdo",qty:6},{id:"BohaiBay",qty:13},{id:"CoralIsland",qty:10},{id:"Copenhagen",qty:7},{id:"Jakarta",qty:13}]);

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Catégories: Sites Anglophones

Google Earth Imagery update – April 2016

lun 18-04-2016

Barely a week after the last imagery update, Google has released some fresh imagery to Google Earth, including imagery up to April 5th, 2016.


April imagery.


Blue: existing March imagery. Red: fresh March imagery.


Blue: existing February imagery. Red: fresh February imagery.

To see the maps of imagery by month in Google Earth download this KML file. As usual, the outlines are larger than the actual imagery. We have also included a map for January imagery that we did last week before this update.

We have not yet found any imagery connected to specific events, so instead we will have a look at a couple of interesting locations we came across as we were looking through the imagery.


Interesting patterns in China. We believe they are rice fields designed so that the water flows from one field to the next down a slope.


Lake Poskin, Wisconsin. Aerial imagery is usually gathered in summer, so we don’t often see frozen lakes at this resolution.

Download this KML file for the above locations.

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Catégories: Sites Anglophones

Technology and sustainability

ven 15-04-2016

Rebecca Moore, Engineering Director for Google Earth and Earth Engine & Outreach recently posted this interesting article on the Google Maps Blog.

The article covers three very different projects that Google is involved in that use technology and maps to achieve sustainability goals. Our first thought when we see maps of this nature is always – can we get the data in Google Earth? In all three cases it appears that the data has not been published in a Google Earth friendly format. We thought it would be worth asking – why not?

Global Forest Watch

Global Forest Watch has a wealth of data and much of it is open data that you are free to download. We looked up one of the datasets which is provided here by the University of Maryland. It turns out that the data is in four different bands, each totalling about 600 GB. Just downloading a 10 degree square of one band can be as large as 600 MB. So although it would certainly be possible to publish a very low resolution version for Google Earth, it would not really be feasible to provide the full data as a single KMZ file. It is possible to serve such large data sources to Google Earth, but it is not a trivial exercise.

Project Sunroof

Project Sunroof uses Google’s 3D imagery to calculate the orientation and area of you house’s roof and combine that information with the typical amount of sunlight in your area, your average monthly electricity bill and state and federal incentives to give you a set of quotes for different financing options for your solar installation. It is currently only available in certain parts of the US and only where there is 3D imagery. Although Google’s 3D imagery plays a part and mapping data is a critical part of the application, it is ultimately more of an application than a map. It would certainly be possible to implement it with Google Earth rather than a website, but there would be no significant benefits to doing so. It would be nice to see maps of the data, such as average sunlight, state subsidies, etc, but these could presumably be obtained from other sources.

It would also have been nice to see the 3D imagery in Google Earth with the roofs painted different shades of gold to indicate the amount of sunlight they receive, but as we saw last week, Google’s 3D imagery is not a small amount of data and adding an extra layer for it to Google Earth would not be a trivial exercise.

Methane Maps

This is a project Google is doing in collaboration with the Environmental Defence Fund (EDF) using the Street View cars to gather data on methane levels in the air. This makes it possible to identify leaks in natural gas pipes. In this case the presented data is fairly straightforward map data and could easily be presented in KML format. Sadly a KML option is not offered. It is possible to obtain the raw data by requesting it on this page but we were unable to find any source of the processed data available for download.

So in conclusion, we believe that having a KML download option should always be considered when you have mapping data you wish to provide to the public, but there are clearly projects where it is not a trivial exercise. We do hope that the EDF or Google consider presenting the methane data in KML format.

We applaud Google’s work in using their technology and resources in the above sustainability efforts, and if you haven’t already, we highly recommend reading the article about the three projects.

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Catégories: Sites Anglophones

Strange buildings in the sand

jeu 14-04-2016

Recently there have been a number of stories, such as this one, about a strange looking structure that can be seen in the Egyptian desert with Google Earth. We thought it was interesting enough to investigate.


The strange structure in the Egyptian desert.

The story was largely started by this YouTube video. There are some rather wild speculations about what it might be, but the most rational explanation is that it is a military structure. Going through the comments we discover that there are a number of other similar looking sites in Egypt, including the one shown below:


A similar structure, but this time we can clearly see missiles mounted in the circles around the site.

Once we were sure it is a military site, we found this article which talks about the typical layout of Russian-made Surface to Air Missile (SAM) sites. The standard layout is to have a central radar, usually on a raised platform, with a bunker below it and a number of SAMs arranged in a circle around it. And it turns out that there are a lot of them around the world. We could not find a single collection showing all sites around the world, but we have put together this KML file from a few collections that we were able to find. Links to the sources are in the KML. It also includes the various locations featured in this post. If you are interested in other military collections, see the Google Earth Community.

One of the collections we found features sites for the American made Patriot missile, such as the one below:


Patriot SAM battery in Kuwait. Note the central command structure with the dual ramps similar to the Egyptian sites.

While looking around Egypt we also came across a couple of single raised platforms with ramps. There is no sign of doors, nearby missile batteries or other structures.


Our guess is that this is a platform prepared for mounting military equipment (probably radar) in time of war.

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Catégories: Sites Anglophones

What’s that image: Earthquake, train crash and floods

mer 13-04-2016

Yesterday we had a look at some of the interesting imagery of the United States from the latest Google Earth imagery update. Today we are having a look around the rest of the world to see what we can find. Most of the locations were found with the assistance of DigitalGlobe’s ‘first look’ map.

On February 6, 2016, an earthquake of magnitude 6.4 struck the south-west of Taiwan causing widespread damage and 117 deaths. Most of the deaths were caused by the collapse of a 17 floor apartment block in Tainan. Read more about it and see drone footage in this article. One possible cause of the collapse is poor construction, including, believe it or not, the use of cooking oil cans as a building material.
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Before and after: collapsed apartment block in Tainan, Taiwan.

On 9 February 2016 there was a head on collision between two trains near the town of Bad Aibling, Germany. The photo below was captured three days later. Based on the Wikipedia page, it would appear that both trains involved were blue and the emergency engineering train for carrying out repairs is red, so what we can see on the tracks may be one or more emergency engineering trains. The crash may have been caused by a controller making an error because he was distracted by a game he was playing on his phone.


Train crash, Bad Aibling, Germany.

In December, 2015, we showed you some imagery of flooding in southern India via the Google Crisis response page. Now, that imagery and more has made its way into Google Earth. Read more about the floods on Wikipedia.


Flooding in Chennai, India. The area has a lot of swamps and lakes so be sure to compare with historical imagery before concluding that a body of water is part of the flood.

January saw heavy flooding in Tanzania and there is some related imagery in Google Earth. We didn’t find any serious flooding in built up areas, but we did find these flooded fields:


It is a river delta onto Lake Sulunga, so its flooding may be a common event.

We also came across Benjamin Constant, Brazil. At first sight it looks like a disastrous flood, but closer inspection reveals raised walkways between the houses, indicating that flooding is common and preparations have been made. A look through the historical imagery also shows that the flood waters are not higher than previous events.


Benjamin Constant, Brazil.

For the locations featured in this post, download this KML file. We have also included some other locations where imagery has clearly been captured for a specific event, but we were unable to find anything related to the event in the imagery.

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What’s that image: United States

mar 12-04-2016

Yesterday we had a look at the most recent Google Earth imagery update. Today, we are having a look at what interesting sights can be found in the imagery, specifically in the United States. In a later post we will look at other parts of the world.

We have looked at the work of Jorge Rodriguez-Gerada before. Another of his works is now visible in the Google Earth imagery of San Antonio, Texas. It is called Nyssa, after its subject, Nyssa Gomez. As of this writing the artist’s website is down, but you can read more about the artwork here.


Nyssa, by Jorge Rodriguez-Gerada.

We have already had a look at Super Bowl 50 in Google Earth. The Super Bowl title was won by the Denver Broncos, and when they got back home to Denver, Colorado, they held a victory parade. See ground level photos of the event here.


Crowds gathered for the Denver Broncos victory parade.

Heavy rains in December 2015 resulted in the flooding of the Mississippi River. We mentioned it at the time and had a look at previous Mississippi flooding events. Now, there is quite a lot of imagery in Google Earth relating to the event. St. Louis, Missouri, is at the confluence of three large rivers, the Mississippi River, the Missouri River and the Illinois River. There are a number of satellite images of the region captured in early January showing the flooding. There was more flooding in March but no related imagery as yet.
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Flooding in St. Louis, Missouri.

Flooding in St. Louis, Missouri.

There are also images further down the Mississippi as the water travelled south.

Flooding of the Mississippi near Osceola, Arkansas.

Flooding of the Mississippi near Arkansas City, Arkansas.

There was a Tornado in Dallas, Texas, which was part of the same group of Tornadoes as the one we featured yesterday. See some aerial images here. There is an image of Dallas in Google Earth that was captured a few days after the Tornado in response to the event. But, based on this map we believe the main path of the tornado started just north of the image. There is also this funny story relating to the event. A demolition company charged with demolishing one of the houses damaged by the tornado relied a bit too heavily on Google Maps and demolished the wrong house!

For all the locations featured in this post, including outlines for some of the relevant imagery, download this KML file. Remember that much of the imagery can only be seen by switching to ‘historical imagery’.

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Google Earth Imagery update – March 2016

lun 11-04-2016

Google has recently pushed the latest imagery updates into ‘historical imagery’, which means we can make a map of the updates. As always, the outlines are larger than the actual images. The map below shows imagery that is dated March 2016. Google has also added quite a lot of older imagery, but there is no easy way to tell just how much. There have certainly been quite a lot of additions for February 2016 and January 2016.


March 2016 imagery.


February 2016 imagery. Red: new imagery, Blue: existing areas as per our previous map.

To see the maps in Google Earth download this KML file.

We are still going through the imagery. One of the places we have found so far is the Tornado that passed near Holly Springs, Mississippi on December 23rd, 2015. We have featured it twice before, showing Landsat imagery and ASTER imagery. Those were both very low resolution images and you can just make out the path of the tornado. Now, there is high resolution aerial imagery for part of the track and you can see damaged buildings and uprooted trees over a distance of over 30 km. The Tornado actually caused damage over a much greater distance, but it is outside the area covered by the new imagery.

The imagery is dated February 5th, 2016, over a month after the tornado, so some clean-up has probably already been done.


The blue on the roofs are probably tarpaulins to cover damaged roofing.


All along the track you can see trees knocked down in various patterns and you can often see the clump at the base of each tree where its roots have been ripped out of the ground.

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Before and after. Drag the slider to compare the two images. Some houses were completely swept away while others require major repairs.

To see the approximate track of the tornado in Google Earth download this KML file.

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How big is the Google Earth database?

ven 08-04-2016

This is the fourth and final in a series of posts about the size of the data in Google Earth. We already looked at:

Today we are putting it all together and trying to come up with an estimate for just how large the Google Earth database really is.

3D Imagery: 1024 TB

The total area of 3D imagery currently in Google Earth is approximately 524,000 sq km. We re-ran our tests for 3D imagery a number of times trying closer and closer views and every time we got closer, the figure got bigger. We eventually settled on an estimate of 2 GB to 1 sq km of 3D imagery although we believe it is an underestimate. This gives us a total of 1024 TB for 3D imagery.

Default Layer Aerial Imagery: 179 TB

For areas of countries we mostly relied upon this list on Wikipedia.

The continental US has more or less complete aerial imagery coverage. Total area approx: 7,663,000 sq km.

Based on our maps from this post, we estimate that the European countries Portugal, Spain, Italy, France, United Kingdom, Germany, Netherlands, Czech Republic, Austria, Montenegro, Greece, Denmark, Switzerland and Belgium have about 50% aerial imagery, as does Japan. Total area covered 1,506,000 sq km.

The US has approximately five times as much aerial imagery as the rest of the world combined.

Based on our previous results, we estimate aerial imagery requires approximately 2 GB per 100 sq km. This gives us a total of 179 TB for aerial imagery.

Satellite Imagery: 196 TB

Excluding Antarctica, the rest of the world’s land mass is approximately half covered with good quality satellite imagery. This is a total area of 63,638,000 sq km. Based on previous results, good quality satellite imagery requires about 0.3 GB per 100 sq km. Low quality satellite imagery requires significantly less space at about 18 MB per 100 sq km.
This gives us totals of 186 TB for good quality satellite imagery and only 10 TB for low quality satellite imagery.

Historical Imagery: 1,618 TB

This is the hardest to estimate. We will exclude the default layer in our calculations. The continental US has on average about seven aerial images for any location. This gives us a total of about 898 TB. Europe and Japan have approximately 50% coverage with five layers of aerial imagery. This comes to 118 TB. About a third of the world’s land area has five layers of good quality satellite imagery. This comes to 527 TB. About one percent of the world’s land area has twenty or more good quality satellite images. This comes to 75 TB.

So our final estimate for the total size of the Google Earth database is 3,017 TB or approximately 3 Petabytes!

Compare that to this post from 2006 at which time the estimate stood at 150 TB.

How accurate is our estimate? Given that the bulk of the size comes from historical imagery for which we simply do not have very accurate data, our estimate could easily be a long way from the true figure. In addition, the method used for determining how much data each imagery type requires was not particularly accurate. We have also completely ignored the old type of 3D buildings, and all the street and mapping data or layers. We have considered Street View to not be part of Google Earth as it should really be considered more of a Google Maps product or a product in its own right. We believe that overall it is a significant underestimate and the database is actually quite a bit bigger.

A significant proportion of the Google Earth database is US aerial imagery, both current and historical. For this we can largely thank the USGS and the USDA Farm Service Agency, although much of the most recent imagery is gathered by Google itself.

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Catégories: Sites Anglophones

How much historical imagery is there in Google Earth?

jeu 07-04-2016

This is the third post in a series looking at how much data is in Google Earth. We have already looked at how much data per unit area 3D imagery requires and how much data different types of 2D imagery require. Today we are looking at historical imagery.

Our first test was to pick a location that we know has a lot of historical imagery. We chose Rio de Janeiro, Brazil. We prepared the view we were interested in and cleared the Google Earth cache then allowed the default layer to load. Just the default layer, without moving the view at all, filled the cache to 4 MB. We then switched to historical imagery and cycled through all the historical imagery, again without moving the view. The cache was now at 580 MB. The reason for the enormous size is that Rio has approximately 220 unique images for the location we chose. On average, each image added about 2.6 MB to the cache. This is less than the default view takes, because many of the historical images do not cover the full area in the view, with some of them being only barely visible at the edge of the screen.


The area we chose in Rio de Janeiro, Brazil.

So how much historical imagery is there globally? We have tried to answer that question before with our historical imagery density map. Since then, we have created a higher resolution version, although it is not quite complete.

In the standard heat map, we used a logarithmic scale to help make the patterns in the historical imagery stand out. To get a better idea of just how much historical imagery there is overall, we have a simplified version shown below. It shows areas with 10 to 24 images in green, areas with 25 to 49 images in yellow and areas with 50 and over images in red. Most of the world has less than 10 images in a given location and in fact most of the oceans and much of the polar regions and deserts have no historical imagery whatsoever. There is also a bug in the way Google Earth shows historical imagery on the timeline that causes it to incorrectly report the number of images along coastlines or other regions that have no historical imagery, but are near to areas with a lot of historical imagery. This is what causes all the large patches around the edges of the continents in the screenshot below. This makes it impossible to directly do calculations on the data. However, by rough approximation we believe that historical imagery, if uniformly distributed, could cover the worlds land masses at least 5 times over.

To see the historical imagery density map in Google Earth download this KML file.

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Catégories: Sites Anglophones