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NOAA post Hurricane Matthew imagery in Google Earth

ven 14-10-2016

Yesterday we talked about how the NOAA aerial imagery of the eastern US coast in the wake of Hurricane Matthew is available as map tiles. We investigated how to display map tiles in Google Earth and concluded that doing it with a single KMZ file would not be feasible. We also said it wouldn’t be worth setting up a server to serve the necessary KML files, but after some consideration we decided to give it a go.

Rather than generating the hundreds of thousands of KML files necessary to make it work, we realised that we could simply generate KML files dynamically as they are requested. It actually worked a lot better than we expected. We implemented it in JavaScript, initially testing it out with a local instance of Node.js running on a PC which worked very well. We then put the code on a Node.js server running in the cloud (Openshift) and it still works remarkably well.

So, to view the NOAA imagery in Google Earth, simply download this KML file. You should immediately be able to see the thin strip of imagery along the eastern coast of the US. Also note that there are a number of new patches of aerial imagery inland.

As you zoom in, it automatically loads higher resolution imagery almost as seamlessly as native Google Earth imagery. The imagery is arranged in separate layers for batches of imagery captured on different dates. Occasionally there is a problem with layers overlapping, in which case you may see grey squares mixed in with imagery. If you experience this, try turning off some of the layers until you identify which layer has the grey squares, then keep that particular layer off while viewing that location. There are also some locations such as Rocky Mount, North Carolina for example, with multiple sets of imagery captured on different days, so again, try turning off some layers to see the different sets.

The flooding is still ongoing at the time of writing, and NOAA is adding new imagery over time. We will try to keep the server up-to-date over the next few days, so try refreshing the main network-link to see if there are new layers.

Nichols, South Carolina.

Boardman, North Carolina.

Near Galivants Ferry, South Carolina.

A flooded water treatment plant near Smithfield, North Carolina.

Rocky Mount, North Carolina.

Goldsboro, Georgia.

This is just an experiment to learn about the best way to access map tiles in Google Earth. We make no guarantees about how long we will keep the server running.

If you know of any other maps available as map tiles that do not have restrictive licence agreements, let us know in the comments.

The post NOAA post Hurricane Matthew imagery in Google Earth appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Getting tiled maps into Google Earth

jeu 13-10-2016

[ Update: See this post for a KML to view to see the NOAA imagery in Google Earth. ]

Yesterday we had a look at some aerial imagery of the eastern coast of the US after Hurricane Matthew. The imagery comes from NOAA. We wondered what it would take to get the imagery into Google Earth. The NOAA has made the imagery available for viewing on this map and also offers the option to download it. However, the total size of all the imagery is over 24 GB. Also provided is the option to view the imagery as tiled data.

Most modern online maps use a fairly standardised method of tiling the map imagery. It is a relatively simple system that involves using the Mercator map projection and cutting off above 85.0511°N and below 85.0511°S, resulting in a map of the globe that is square. This is then divided into four squares, each of which is divided into four squares and so on. Each division is a zoom level. For the full technical details see this page.

Google Earth has a mechanism for presenting tiled data that is very similar to the above process. You can take a large image overlay and break it up into tiles in such a way that Google Earth only loads the tiles that are within the view and at a suitable resolution. The result is called a ‘Super-Overlay’. Google Earth Pro even has a built-in tool for creating these automatically which you can read more about here.

We already had some basic JavaScript code for working with map tiles that we created to work with Mapzen altitude data, which is available as map tiles. We combined this with information from the KML Developers Guide and technical information about the NOAA tiles and were able to create a Super-Overlay for a small portion of the NOAA data. And it works quite well. The problem is that it doesn’t scale.

You can download our sample here. It covers a short stretch of coast near Charleston, North Carolina. A Google Earth Super-Overlay actually consists of many KML files all network-linked to each other in a hierarchical fashion. Our sample file is actually in the compressed KMZ format and includes over 10,000 files which uncompressed are over 10 Mb. Keep in mind that the KML file does not contain any imagery at all, that is all coming directly from NOAA. When we tried to create larger Super-Overlays it crashed our JavaScript as the browser ran out of memory. We could probably find ways to generate larger Super-Overlays, but there is no getting around the file size, so it is practically impossible to do a single KML file for all the NOAA imagery.

The only real alternative would be to set up a server with all the Super-Overlay files. This would probably work quite well, but running a server in this particular instance is not worth it. What would be ideal would be for Google Earth to natively support map tiles such that you could give it the details of the tile server and it would handle it from there.

NOAA imagery as seen in Google Earth. Some flooding near Charleston, North Carolina.

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Catégories: Sites Anglophones

More post-Hurricane Matthews imagery

mer 12-10-2016

[ Update: See this post for a KML to view to see the NOAA imagery in Google Earth. ]

On Monday we had a look at some imagery via Google Crisis Response of the devastation caused by Hurricane Matthews.

Google has since added quite a lot of new imagery to the KML file that we linked to on Monday. The KML file uses a network link, so if you still have it you should automatically see any new imagery that is added.

In addition, Google has made available on this map a large amount of aerial imagery provided by NOAA. To access it, go to the layers and select ‘Aerial Photos’. Then zoom to the eastern coast of the US and you will see a thin strip of aerial imagery all along the coast.

The NOAA imagery can also be viewed on this NOAA map, which also offers the option to download the imagery. Unfortunately, the imagery is not currently in a format easily viewed in Google Earth and Google does not currently have plans to add it to the above KML file.
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Before and After of Flagler Beach, Florida showing damage to the coastal road.

Before and After of a new inlet formed along the Florida coast. To find it on the map search for ‘Rattlesnake Island’.

Some flooded roads in Charleston, South Carolina.

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As a bonus, we get a look at Space Launch Complex 40 where SpaceX AMOS-6 mission spectacularly blew up in September.

See this article for a number of aerial and ground level photos of the damage caused by Hurricane Matthews.

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Catégories: Sites Anglophones

Panoramio shutdown date set

mar 11-10-2016

Google has been planning to shut down panoramic photo sharing site Panoramio since September 2014. The initial plan was to merge it with Google Views which was a similar product. However, due to feedback from the Panoramio community they held off that move. Frank did an in depth post about this in June 2015. Since then Google Views itself was merged into Street View. Google has now announced that they are finally shutting down Panoramio for good. As of November 4th, 2016, they will stop allowing new photos to be uploaded or new signups. Users will still be able to access their photos for one year (until November, 2017) at which point the service will be taken offline completely. Users have the option of transferring their photos to their Google Album, and they can optionally also be shared via Google Maps.

GEB reader ‘Hiking Mike’ has written a blog post about the change and some of his concerns about the move. His three main concerns with moving to Google Maps appear to be a lack of community, poor attribution, and the fact that Google Earth doesn’t support user contributed photos.

At the current point in time, there are significantly more photos available in the Panoramio layer in Google Earth than user contributed photos in Google Maps. For areas that do not have Street View, this is quite significant. For example, we chose a location on Hainan Island, China and found just one photo in Google Maps, but a large number of photos in Google Earth’s Panoramio layer:

Hainan, China. Just one photo sphere in Google Maps.

Hainan, China. There are a lot more photos than are shown here. More icons are displayed as you zoom in.

Although Google Earth does sometimes show blue circles indicating the availability of user contributed photos in Google Maps, it is not actually possible to view them in Google Earth. Hopefully, this is something Google will address before turning off the Panoramio layer. It is likely that the Panoramio layer will continue to function in Google Earth for as long as the Panoramio servers are on, so it will probably continue to be there until November, 2017. This is just a guess, not a guarantee.

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Catégories: Sites Anglophones

Hurricane Matthew imagery via Google Crisis Response

lun 10-10-2016

Hurricane Matthew is an extra-tropical cyclone that impacted Haiti, Jamaica, Cuba, Dominican Republic and The Bahamas and as of this writing is moving along the coast of the southeastern United States causing heavy rains and consequent flooding.

The NOAA’s National Hurricane Centre provides this KML file showing the path of Hurricane Matthew.

The path of Hurricane Matthew as of October 9th, 2016.

Google Crisis response has released two maps. There is this Florida emergency preparedness map, which actually contains a variety of related information for the whole east coast of the US. Then there is this ‘Haiti Hurricane’ map, which has imagery from DigitalGlobe and Google’s Terra Bella of various parts of Haiti.

Google Crisis Response also kindly provided this KML file , which includes imagery of Haiti and the Bahamas. It is a network link so it will update as they add new imagery. As of this writing it does not include the Terra Bella imagery but they have stated that they will be adding that shortly.

As is normal for imagery gathered after natural disasters, the imagery is not the best quality but we can see that many houses have lost their roofs or worse.

Port Salut, Haiti.

Port Salut, Haiti.

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Before and after of Tiburon, Haiti.

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Catégories: Sites Anglophones

Floods around the world as seen in Google Earth

ven 07-10-2016

Flooding is a remarkably common phenomenon around the globe. Satellite imaging companies often try to capture imagery of the floods as such imagery is useful for governments and emergency services. DigitalGlobe, for example, has its First Look program through which it captures imagery and distributes it to emergency responders. Today we are looking at a few locations that we know about via the FirstLook program and where the imagery has since made its way into Google Earth. However, none of the imagery in today’s locations really captures the full scale of the events. This is due to a number of reasons:

  • There is often no warning for floods. There may be warning for particular types of well-known weather systems such as cyclones and typhoons, or when there are heavy rains in a region the rivers downstream may be expected to flood. But even so, the severity of the flood is hard to predict.
  • Floods follow rain and there are often cloudy conditions during and shortly after a flood, so it may take some time before there are suitable conditions for capturing imagery.
  • In the case of flash floods the event is typically over before the location can be imaged, so all we can expect to see is the damage caused, such as houses or roads washed away.
  • Google only puts high quality imagery in the default layer (more on this at the end of the post).

Eastern Sudan – July / August 2016
In late July and early August there were heavy rains and subsequent flooding in eastern Sudan. According to this article tens of thousands of people were affected and thousands of homes damaged or destroyed. There is a DigitalGlobe image of the town of Sennar and surrounding areas that was captured in response to the floods. Although there is a lot of standing water in the image, we could not find any flooded houses or evidence of houses washed away.

Skopje, Macedonia – August, 2016
In early August, 2016, Skopje Macedonia experienced severe flash flooding, killing at least 21 people. See this article for photos. In this case the imagery in Google Earth comes from CNES / Astrium. We can see some flooded areas, but the imagery does not quite cover the worst affected area (the northern parts of Chento).

Chetwynd, Canada – June, 2016
Chetwynd, Canada, experienced severe flooding in June, 2016 prompting a state of emergency to be declared. There is a DigitalGlobe image of Chetwynd captured after the event. Although we can see wet areas we could not find any washed away roads or bridges. We believe that the worst damage took place in areas not covered by the image.

Wuhan, China – July, 2016
The city of Wuhan was just one of many locations in China that experienced severe flooding in July. There is a CNES / Astrium image captured after the worst of the floods had already subsided, but the river is still very full, flooding some of the buildings along its banks.

In all the above locations we are looking at the imagery in the default layer. There is almost certainly more imagery hidden in ‘historical imagery’ that Google has chosen not to put in the default layer. However, Google has not updated ‘historical imagery’ since early June so we can’t see it. We should also mention Pekalongan City, Indonesia which experienced flooding in June, 2016. We can see bits of a Digital Globe image, but the parts we can see do not cover the affected area.

To see the locations above in Google Earth, download this KML file. We have marked out the extent of the relevant imagery in each location.

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Catégories: Sites Anglophones

Wikipedia data for US Tornadoes in Google Earth

jeu 06-10-2016

Wikipedia has lists of notable tornadoes and tornado outbreaks worldwide for each year. For example, here is the list for 2016. There are also more detailed lists, such as this one for US Tornadoes from January to March 2016. The detailed lists give geographic coordinates and Enhanced Fujita Rating (EF rating).

We thought it would be interesting to see the locations in Google Earth. So, we imported the data for US tornadoes from Wikipedia going back to 2009. The pages for years prior to 2009 are organised differently so we could not easily import the data. We then used a variation of the tool we created earlier this year to check whether there is relevant imagery. This can take quite a long time, so we only did it for the stronger tornadoes – those with an EF rating of 2 or greater.

To see the results download this KML file. We provide the data either sorted by EF rating or by year. For the placemarks sorted by EF rating and EF rating 2 or greater, we have used a donut icon if there is imagery available within six months after the event.

Wikipedia states that the data comes from the US National Weather Service. The data does not show the paths of the tornadoes and there are often multiple placemarks for a given tornado. We also found the placemarks are not very accurate.

For examples of actual Google Earth imagery of the devastation caused by tornadoes see these posts.

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Catégories: Sites Anglophones

Landsat and Sentinel-2 data now on Google Cloud

mer 05-10-2016

Google has just announced the release of Landsat and Sentinel-2 data on the Google Cloud. Landsat and Sentinel-2 data are public datasets of satellite imagery from earth observation satellites. The Landsat data is from a joint program between US Geological Society (USGS) and NASA and the Sentinel-2 data is from the European Space Agency’s Copernicus program.

Google has long had the datasets in Google Earth Engine, but accessing it required a Google Earth Engine account, which had certain restrictions on usage. The Google cloud version appears to be without restrictions. The data itself is public data and you can do almost anything you like with it although proper attribution may be required.

More about the individual datasets and how to access them can be found here: General instructions, Landsat, Sentinel-2.

The imagery is provided as unprocessed tiles for each of the optical bands that each satellite provides. To see the images in colour requires processing. The easiest way to do this is with commercial tools from GeoSage. Alternatively, see this post for instructions on how to process Sentinel-2 imagery using GIMP. Landsat data can be processed in a similar way, although it an some extra steps are required to get the best resolution.

The resolution of Sentinel-2 imagery is 10 m per pixel and Landsat-8 is 15 m per pixel after pan-sharpening. Do not expect to see the kind of detail we are used to in Google Earth.

Sadly, Google has not provided thumbnails with the data.

Amazon provided Landsat data via its cloud infrastructure Amazon Web Services (AWS) in 2015 and more recently added Sentinel-2 data. We did a series of posts featuring KML tools to allow you to preview the latest images and make animations from provided thumbnails. The Landsat data on AWS is somewhat limited compared to the Google Cloud offering. Google is providing all Landsat images from Landsats 4,5,6,7 and 8 from 1982 to present. AWS only has Landsat 8 data and even that is only complete data for 2015 and select images from 2013 and 2014.

The image below is a Sentinel-2 image downloaded from the Google Cloud and processed with GIMP. It shows a small part of the Soberanes Fire, California, on September 12th, 2016. To see it in Google Earth (and covering a larger area) download this KML file

Copernicus Sentinel data, 2016.

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Catégories: Sites Anglophones

Antipode Earth – turning Google Earth inside out

mar 04-10-2016

We were recently thinking about antipodes (pairs of points on opposite sides of the earth). We have previously seen side by side maps that sync so that you can find what is on the other side of any given point. But we thought it might be interesting to see what the world map looks like when every point is translated to the other side of the world.

We tried two versions. For the first, we used a KML map of country outlines that we have used before, that we got from and converted all the coordinates to their antipodes.

Australia is opposite the Atlantic Ocean.

The second version uses one of NASA’s Blue Marble images as an image overlay.

North America is opposite the southern Indian Ocean.

Almost all land has water opposite it with the main exception being South America and East Asia which are opposite each other, but even in that case, a lot of water is involved.

To see the above in Google Earth download this KML file. We suggest editing the properties of the image overlay and try adjusting the transparency.

And finally, for a different way to look at the world, try switching to ‘Sky’ mode. The image overlay does not appear to work in sky mode, but if you turn off all the Sky layers (including ‘imagery’) then the world map KML works and you get a sort of inside out view of the earth.

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Catégories: Sites Anglophones

Google Earth weather layers being dropped

lun 03-10-2016

The Google Earth weather layers “Conditions and Forecast” and “Ocean Observations” have been broken for some time. We did a post on it in July this year, but at that time it had already been broken for several months. Google has now announced that it will be dropping the layers from Google Earth on October 10th, 2016.

Dropping the layers is certainly better than leaving them broken in Google Earth, as there is currently no indication that they are not displaying the correct information. What do our readers think of this move? Was the layer useful to you? Would a KML file with similar functionality be useful? Let us know what you think in the comments.

The Google Earth “Conditions and Forecast” and “Ocean Observations” weather layers.

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Catégories: Sites Anglophones

The best of Google Earth for September 2016

ven 30-09-2016

Although Google has been adding new imagery to Google Earth, they have not been updating historical imagery since June, so we cannot make a map of the latest imagery. We did, however, look at a few locations this month which have recent imagery, including the damage caused by the Erskine Fire in California and the trail of destruction left by the Jiangsu Tornado in China. We also discussed an image of Itu Aba Island in the South China Sea that Taiwan apparently wants censored.

Google added quite a lot of interesting 3D imagery this month, including two new countries, Malaysia and Tunisia. The imagery of Tunis has since been removed but that is probably only temporary. The imagery of Sfax, Tunisia remains and a second location, Ipoh, has been added in Malaysia. The city of Kumamoto of Japan was also updated with 3D imagery captured after the 2016 Kumamoto earthquake and we had a look at the signs of earthquake damage, most notably a lot of blue tarpaulins used to patch the roofs. Last month marked the 100th anniversary of the US National Parks Service and in honour of the occasion Google released 3D imagery of a number of US Parks. We created some Google Earth tours showing off the imagery. We also had a look at some volcanoes as featured in 3D imagery, including Mount Fuji in Japan, Mount Vesuvius in Italy and Mount Saint Helens in the USA.

DigitalGlobe’s latest satellite WorldView-4 was supposed to be launched this month. However, the launch was postponed till October. Terra Bella successfully launched several new SkySat satellites in a joint launch with Peruvian earth observation satellite PerúSAT-1.

We had a look at a number of interesting rotating islands around the world prompted by a story about one found in Argentina. If you haven’t already, be sure to also check out some further examples from the Google Earth Community.

We had a look at some circular geoglyphs that were recently studied in Peru.

We discussed two issues with modern facial recognition technology. Google’s automatic facial recognition as used in Street View often blurs objects that should not be blurred, including a cow. At the same time, a recent study suggests that blurring imagery does not fool facial recognition software.

A partnership between Google, Oceana and SkyTruth released a program called Global Fishing Watch that monitors fishing activity around the world.

We released a KML file that catalogues ships that appear in Google Earth’s 3D imagery. The focus is on cruise ships, but ferries and a few other classes of ship are included as well.

We discussed the difficulty of trying to gather good satellite imagery in locations that have year round cloud cover.

We had a look at a study of land lost vs land gained done using Google Earth Engine.

In memory of 9/11 we created an animation using Street View imagery showing the new World Trade Center buildings.

We had a look at some weird altitude effects related to 3D imagery and Google Earth tours.

We had a look at imagery from Terra Bella of the damage caused by an earthquake in Italy and also looked at the Copernicus Emergency Management Service, which also gathered imagery of the event.

We had a look at declassified imagery from US spy satellites and were impressed by the resolution, although it is not quite as good as what is currently available in Google Earth.

We updated our contour drawing script to use Mapzen image tiles rather than their API and found that it works much faster, which allows for much higher resolution contours.

Google released a bug fix update to Google Earth which resolves many of the installation issues as well as fixing an annoying crash when moving placemarks around.

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Catégories: Sites Anglophones

3D volcanoes and 3D data corruption

jeu 29-09-2016

Google recently released 3D imagery for Mount Fuji in Japan. However, we discovered that there are a number of squares of the imagery that appear only in low resolution. We have come across this problem before and interestingly another location with a similar problem is Mount Vesuvius in Italy.

Mount Fuji, Japan.

Mount Vesuvius, Italy.

A third volcano, Mount Saint Helens in Washington State, USA, also has 3D imagery, but does not have any problems with it:

Mount Saint Helens, Washington State, USA.

The problem with squares of blurred 3D is not restricted to volcanoes. We know of a number of other places around the world where the same issue occurs. For the ones we know about, download this KML file. If our readers know of any others, please let us know in the comments.

Thank you to GEB reader Samppa for letting us know about this one in Rio de Janeiro, Brazil.

One location that had a similar problem a couple of years ago was Oslo, Norway. Oddly enough, that seemed to get fixed when the Google Earth client was updated.

Another type of 3D imagery anomaly is this one near Austin, Texas:

The above volcanoes are not the only areas where Google has captured 3D imagery outside urban areas. For a number of US parks see this post and for a number of other non-urban areas see this post.

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Catégories: Sites Anglophones

Ring-shaped geoglyphs in Peru

mer 28-09-2016

A recent story in the news is about some ring-shaped geoglyphs in Peru. It took a while to find the correct location in Google Earth, as the given location ‘Quilcapampa, in the Sihuas Valley’ was not recognised by Google Earth.

Once we tracked down the location, we were able to find quite a number of rings. We have marked the ones we found and a few other possibly related structures and also one or two locations that may be unrelated.
To see them in Google Earth, download this KML file.

Below are the clearest circles that we found:

We also found the structures below. There are some circles and a dashed line. We believe they are modern structures.

Other ancient structures in Peru include:

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Catégories: Sites Anglophones

Post-earthquake Kumamoto in Google Earth 3D

mar 27-09-2016

In April this year, the city of Kumamoto, Japan, suffered a series of large earthquakes. Google managed to capture aerial imagery of the city essentially during the event, after the first major event but before the largest shock and then captured another set of imagery from after the event. We had a look at what damage could be seen in the imagery, including a large number of landslides, collapsed buildings and a derailed train. From the overhead imagery it wasn’t easy to see the extent of the damage to buildings, even though we knew, based on ground level imagery, that there was severe damage in some locations. Now Google has updated the 3D imagery for part of Kumamoto with imagery captured after the event, and the extent of the damage to buildings is much clearer, especially because the roofs have been patched with light blue tarpaulin that is highly visible.

The suburb of Mashiki was the worst hit, and many houses are damaged beyond repair.

A historical building known as Janes’ Residence was completely destroyed. The rubble has been covered in the light blue tarpaulins

The Janes’ Residence was the first western-style house built in Kumamoto dating from 1871. It used to be in the grounds of Kumamoto Castle, but has been moved a number of times. Read more about it here.

Kumamoto Castle was badly damaged by the earthquake.

We have also created a Google Earth tour of the area showing all the light blue roofs, which you can view in Google Earth with this KML file or see in the YouTube video below.

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Catégories: Sites Anglophones

Taiwan wants Google to censor satellite imagery

lun 26-09-2016

A recent story in the news says that Taiwan’s Defense Ministry has asked Google to blur imagery of some military structures on Itu Aba Island (also known as Taiping Island) in the South China Sea.

The South China Sea is a hotly contested area with several countries, most notabley China, building structures on the reefs of the Spratleys. We had a look at the progress last year and had a look at the latest imagery of Fiery Cross Reef in June this year.

As we have discussed before, censoring satellite imagery is more difficult than censoring other data. A number of countries censor aerial data, mapping data and 3D imagery and because those are often gathered within the countries in question, Google must comply with local laws. But satellite imagery is more difficult to censor. I has been done. It is illegal in the US to publish high resolution imagery of Israel, and Google is a US company so Israel appears in relatively low resolution in Google Maps and Google Earth. Also, imagery updates were stopped for Iraq, Afghanistan, the Ukraine and Syria although we do not know exactly how that was accomplished.

Back to this particular case, if the story is correct and if that was the only facility that Taiwan asked Google to censor, then it would appear they made a serious error. The result has been that many news outlets have published the imagery and it is now not only practically impossible to get rid of all those images, but it has become an object of attention. In addition, Google will be very unlikely to agree to censor it unless legal pressure can be brought to bear. If they were to censor it, a lot of people will notice, and it will become another news story, and then a lot of other countries will want their censorship requests to be honoured as well.

Another question would be who Taiwan wishes to hide the imagery from. Even if Google removed the image, it could still be purchased from the supplier Digital Globe, or imagery of the location could be ordered from various other commercial suppliers. A number of states also have their own spy satellites and the countries most interested in the region could probably capture aerial imagery of it if they wished.

The image that Taiwan wants censored is dated July 8th, 2016 and can only be seen in the default layer as it has not yet (as of this writing) been put in historical imagery.

The military structure in question can be seen below:

We have also created an animation showing that the airport was built since 2006 and the harbour is also being expanded.

Speed in milliseconds per image:


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Catégories: Sites Anglophones

Damage by the Erskine Fire, California as seen in Google Earth

ven 23-09-2016

The Erskine Fire was a wildfire near Lake Isabella, California. It was only one of many wild-fires that occur in the California region every year (there are an average of around 8,000 fires per year). According to Wikipedia, the Erskine fire cost US$ 19.3 million, destroyed 309 buildings and caused two fatalities.

We noticed a reddish brown strip that appears to largely match the edge of the region that was affected by fire. We cannot tell whether it is a natural geological feature (that for some reason stalled the fire), a result of the fire itself or a result of fire-fighting efforts. If any of our readers knows what it is, please let us know in the comments.

From the aerial imagery the region appears to have very little vegetation, but it appears to have been more than enough to create an uncontrollable inferno.

Here are some ‘before and afters’ of the damage caused by the fire:
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This was the worst affected area, a suburb of a small town called South Lake.

This KML file has placemarks showing the locations of the damaged buildings we were able to find as well as an image overlay from the map shown on Wikipedia showing the approximate extent of the fire.

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Catégories: Sites Anglophones

AI facial recognition is too good, in two different ways!

jeu 22-09-2016

Artificial intelligence based facial recognition is improving over time. However, it is a bit too good at recognising faces as two recent stories illustrate. The first problem is Google’s automatic facial recognition as used to blur faces in Street View imagery, tends to err on the over eager side and ends up blurring faces of statues, people in paintings, and now even a cow. Read more about it here (expect a lot of bovine puns).

A cow in Cambridge, England, has its face blurred for privacy reasons. See in Street View

The second story found here and here says that artificial intelligence based facial recognition can still identify faces fairly accurately even with face blurring. This would suggest that Google’s efforts to blur people’s faces in Street View may soon be thwarted and they will need to redo it all with a more secure method. The easiest reliable method is to completely cover faces with a square of solid colour. Another sightlier alternative would be to subtly warp faces in addition to blurring them so as to fool facial recognition algorithms. This should work until reliable body recognition becomes common place (yes that’s a real thing and probably works even better on cows than facial recognition does).

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Catégories: Sites Anglophones

The Jiangsu tornado

mer 21-09-2016

Although Google has neglected to update ‘historical imagery’ in Google Earth since early June, they have been adding fresh imagery, and when it is reasonably good quality, it goes into the default layer and we can see it. One such instance is a region in Jiangsu Province, China which was struck by a deadly tornado on June 23, 2016. According to Wikipedia, the tornado killed at least 99 people and injured 846 others (152 critically).

We found a number of articles showing various photos of the destruction, such as here, here, here and here. But, actually locating the event proved more difficult. We first mapped out the area that had new imagery and started searching through it for signs of damaged buildings, but with an area of nearly 4,000 square kilometres we were not successful. We did find a raised railway under construction, and a long trail of destroyed houses that turned out to be planned road construction. The articles either mention major nearby cities or small villages that aren’t marked on the map and couldn’t be found through search. Eventually we found mention of “Danping Village of Chenliang Township” and we were able to find Chenliang. From there, the path of destruction was easy to trace over a distance of around 30 km.

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

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Although the latest imagery is not very high quality, near total destruction of houses all along the path of the tornado is clear, especially when comparing it with older imagery.

Some damaged factories.

A factory roof ripped to shreds.

See a higher resolution aerial image of this factory in this article

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Catégories: Sites Anglophones

Malaysia and Tunisia get 3D

mar 20-09-2016

Malaysia and Tunisia have recently received their first 3D imagery. Tunis and Sfax in Tunisia and Sungai Petani in Malaysia.

The interesting upside down triangle architecture of the Hôtel du Lac, Tunis.

Constructions sites are the easiest way to work out the date of 3D imagery. This construction site in Sungai Petani, Malaysia, tells us the 3D imagery was captured since the most recent satellite image from January 2016.

As we have previously mentioned Google appears to be slowing down in terms of new area covered by 3D. However, they are doing a significant amount of updates of existing areas.

Note that a few of the most recent finds for this month are not included in the above chart, as we have not yet finished drawing the outlines.

To see the full coverage of 3D imagery in Google Earth and find out what other recent additions there are, download this KML file.

York Minster in York, England.

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Catégories: Sites Anglophones

Global Fishing Watch

lun 19-09-2016

Although it is not directly related to Google Earth, Global Fishing Watch does use geographic ‘big data’, so we thought it would be worth covering. Global Fishing Watch is a partnership between Google, Oceana and SkyTruth, which aims to track the world’s fishing fleets and monitor where they fish. This will help to identify illegal fishing as well as assist in the management of fisheries. Read more about it on Google’s Lat Long blog.

To use it, start here. It requires you to sign up to use it, but the signup process is fast and free. We believe the signup is required because of the sensitivity of the data and they require you to acknowledge that you realise the data may be inaccurate, among other things. Learn what you can do and how to use it from the tutorial here.

They do not provide an API nor any way to export data to Google Earth. The data can be accessed by their research partners via Google Earth Engine. They state, however, that the underlying ship tracking data is a commercial data-set, so they cannot distribute it freely. We really wish that shipping data and aircraft data could be made available freely, but Global Fishing Watch states that it downloads 20 million data points per day, so whoever is managing the data collection must have significant costs. There are sites such as MarineTraffic for ships and FlightRadar24 for aircraft that let you see real-time data for a significant proportion of the world’s shipping and aircraft, but if you want any historical data it has to be paid for. We have long wanted to get hold of some historical tracks so we can write algorithms to find ships and aircraft in historical imagery, but we have not managed to find any source that provides such tracks free of charge.

We came across this interesting track that follows lines of longitude (every four degrees). And then another ship takes over and continues the pattern further west. Was it doing some research as well as fishing?

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Catégories: Sites Anglophones