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Google Earth Blog
Thank you to GEB reader Clare for pointing us to this story about the Jefferson Grid. The Jefferson Grid refers to the Public Land Survey System (PLSS) or the Rectangular Survey System used in many parts of the United States to plat, or divide, real property for sale and settling.
Anyone who has looked around the US has noticed that large parts of it are divided up into squares, one mile to a side, often highly visible in satellite imagery and often sporting irrigation circles. The article linked above explains why that is and some of the history behind it.
The state of Iowa is just a sea of squares.
Irrigation circles in Idaho, one in each square.
As you can see above this is not the most efficient use of the land and in some cases farmers have inserted smaller circles in between the larger ones. The most efficient layout of identical sized circles is the honeycomb pattern seen below:
This honeycomb irrigation pattern found near Boardman, Oregon, is actually quite rare.
You might think at first that the Jefferson Grid is a universal uniform grid covering the whole of the US, but as you can see on Wikipedia there are actually a number of different regions, each with its on reference lines and the different regions do not necessarily line up with each other. Also, due to the fact that there were no GPS’s at the time the original surveying was done, there are quite a lot of errors in the grids and it is not uncommon to see an area like the image below where things are not quite straight:
The use of a grid is also not unique to the USA. Here is an area in Mexico that also uses a neat squared grid, except they use the metric system, so each square is two kilometres to a side.
A grid system in Mexico.
Many parts of the world such as Zambia, above, do not use a grid system.
For the locations featured in this post download this KML file.
Many cities around the world also have grid patterns highly visible from above, but perhaps that is a topic for another post.
As we have mentioned in the past new additions to Google Maps are almost immediately available in Google Earth search. However, the information shown in Google Earth placemarks and street maps is not refreshed very often – sometimes it takes over a year between updates.
This is because Google Earth search does not access the Google Earth database, but rather the Google Maps database. The advantage of this was recently made clear by the recent renaming of Mount McKinley in Alaska, which on August 28, 2015 was officially renamed Denali. If you search for ‘Denali’ in Google Earth you will be taken to the correct location, even though the mountain symbol in Google Earth still names it Mount McKinley and probably will do for some time to come. The name is correct in Google Maps because it was changed in Map Maker on August 31 just 3 days after the official name change.
Denali, Alaska, the highest mountain peak in North America.
The same effect applies to addresses and street names. When you search for an address it is the data in Google Maps that is used.
Also of note is the fact that the Google Earth weather layer is out of date again.Thank you to GEB reader Dee for letting us know. It is, as of this writing stuck at 2015-08-14 17:00 UTC.
The post Google Earth search vs Google Earth placemarks and street data appeared first on Google Earth Blog.
We recently came across two stories in the news about people creating art from Google Earth imagery. The first is this one about Mishka Henner. His work appears to consist of unaltered screen shots from Google Earth, either of aesthetically pleasing locations or collections of places of particular interest, such as “51 U.S. Military Outposts”. The article also mentions that to make high resolution images he takes hundreds of screen shots and laboriously stitches them together to make a final image. There are actually ways to automate this sort of thing, however, as we will discuss further on, doing so may violate Google Earth’s licence agreement.
The second story is this one about Meike Nixdorf, who creates stunning landscapes from Google Earth’s imagery. Unlike Mishka Henner’s work, which is mostly unaltered satellite / aerial imagery, Meike takes advantage of Google Earth’s 3D terrain and also retouches the screen-shots in Photoshop.
We have looked at similar art work in the past, including artist Federico Winer, who creates images from satellite imagery with adjusted colour and luminosity, Roosmarijn Pallandt, who creates carpets based on Google Earth imagery and a website dedicated to collecting artistic images from Google Earth imagery (sadly it appears to no longer be active). The USGS has an “Earth as Art” collection collected from landsat imagery and Google themselves have released the “Earth View” chrome plugin that shows selected satellite imagery in new Tabs in Chrome and has its own layer in Google Earth.
So, are these artists in violation of the Google Earth licence agreement? First of all, artists that use Landsat imagery obtained from the USGS have nothing to worry about, as there appears to be no restrictions on its use. To find out what uses of Google Earth and Maps are permissible read through the geoguidelines here. There are some clauses that some of the artists we mention above may be violating.
Firstly, whenever you use imagery from Google Earth or Google Maps you must always include full attribution for both Google and the supplier of any imagery or mapping data that appears in your image. Generally, whatever copyright notices appear at the bottom centre in Google Earth must be included either in your screen shot or added to the image caption. It is not clear whether the artists mentioned above are including proper attribution in their artwork, but certainly the images have been presented in the news articles without proper attribution.
Secondly, the geoguidelines forbid making changes to the imagery. The intention seems to be to ensure that you do not misrepresent what Google Earth or Google Maps look like to the detriment of the products’ reputation so it is not clear whether adding artistic touches would concern Google, but it does appear to violate the Terms of Service (TOS).
Thirdly, the sale of artwork based on Google Earth or Google Maps imagery appears to be explicitly forbidden in the case of physical items such as T-shirts or mugs. This suggests that a physical ‘painting’ would also be forbidden. The restriction doesn’t apply to books (with the exception of books with navigational content such as guide books) but it is likely that selling a book consisting mostly of Google Earth / Google Maps imagery is in violation of the copyrights unless permission is explicitly granted by both Google and the imagery providers.
Mariveles Reef, Spratley Islands. Whenever you use a screen shot from Google Earth as above, make sure that the Google Earth logo and the copyright notices at the bottom centre are clearly visible, or include them in the image caption.
The post Art from Google Earth imagery and the Google Maps/Earth TOS appeared first on Google Earth Blog.
After creating a global map of historical imagery density last week, we have been experimenting with higher resolution versions for a small area.
High resolution historical imagery density Latitude 0°-15° Longitude 0°-20°.
As you can see above, there is a curious pattern of vertical and horizontal lines. At first we thought this was an artifact of the way the Google Earth plugin reports historical imagery, as is the case over the oceans, but on further investigation we found it has to do with the way satellite imagery is collected. We were aware of this, but don’t think we have talked about it before.
Satellite imagery appears as either squares of imagery (or rather parallelograms, depending on the angle they were captured) or strips. The strips almost always run in the North-South direction, but occasionally are in the East-West direction and very rarely at some other angle. All of the above are typically 17-20 km on the shortest side. The interesting feature we are looking at today is the fact that the majority of the strips are lined up with lines of latitude and longitude with strips starting and ending on exact degrees.
The best way to see this is to turn on the Grid (found in the ‘View’ menu) and then zoom until the grid shown matches single degrees.
The effect is very noticeable in sparsely populated regions, such as the Sahara desert above, where most of the imagery is in strips.
The pattern can be seen at all latitudes. In Canada, above, even horizontal strips can be seen to line up with whole degrees of longitude even though the distance on the ground is about half that for a degree of latitude in this location.
The pattern seems to be followed by both DigitalGlobe imagery and CNES / Astrium imagery, although the later is rarer and so harder to check. We do not know whether this has something to do with the way the satellites capture the imagery, or whether it has to do with the way satellite imaging companies catalogue and sell imagery. If any of our readers knows more about it, please let us know in the comments.
The post Satellite imagery strips and degrees of latitude and longitude appeared first on Google Earth Blog.
Google has not released any ‘satellite imagery update maps’ since the introduction of the ‘Voyager layer’ at the end of June. Google has, however, been pushing out satellite imagery and there are images captured in August in Google Earth, but without the ‘imagery update’ maps, it can be hard to find.
Google took an unusual two week break from releasing 3D imagery in the first half of August, but has been releasing more since then. We are a little behind on updating our KML, but we haven’t forgotten it, so bear with us. We have added quite a lot of areas today so be sure to refresh the network link if you are not seeing up to August 22nd. As always, a big thank you to GEB reader Anton Rudolfsson who draws the outlines.
We have been using the Google Earth plugin to try and map out the density of historical imagery in Google Earth Part 1, part 2, part 3. In the process, we learned how Google Earth handles KML polygons that cross the antimeridian.
George of MyReadingMapped was kind enough to share his enormous collection of KMLs. If you haven’t seen them yet be sure to check them out.
GEB reader Chris pointed us to an issue with the blue Street View layer, so we investigated further and found issues with it showing different areas at different zoom levels. For comparison, we also created an image overlay of the Google Maps version of the blue layer.
Earlier this week we showed you our historical imagery density map. Looking at the map a number of hotspots are immediately apparent. However, many of these hotspots result from anomalies in the way the Google Earth plugin reports the information, as well as the settings we used when collecting the data.
There are, however, some genuine hotspots that we were not previously aware of. Today we will look at just two of them.
The first is Maiduguri, Nigeria. A seemingly unremarkable spot when first looked at in Google Earth, it is estimated to have a population of over a million and is a key economic and education centre in the region. It has also experienced religious violence committed by Islamist group, Boko Haram – which is the main reason why it has so much imagery. For example, there was a bomb attack on one of its markets (known as ‘Monday Market’) on January 10, 2015, and Google Earth has an image captured two days later. Similarly, there were a number of other events relating to Boko Haram listed on the Wikipedia page and again there is imagery that was almost certainly captured in response to the events. However, we were not able to find anything in the imagery relating to the violence – partly because it is a large city and we didn’t know where to look and partly because the resolution is not very high and it is possible the events are not visible.
Monday Market is quite distinctive from above.
The second location is Calama, Chile. We do not know why it is of interest, but it has multiple images per month throughout the past two years. Both Maiduguri and Calama are in dry, largely cloud-free and snow free locations, which makes capturing imagery of them particularly easy. So what can we do with a location that has so much imagery? Animated historical imagery Tours of course! There is an open pit copper mine just to the north of Calama that would have made an interesting target, but it is just off the edge of most of the imagery. So we decided to have a look at the airport. You can download the tour as a KML here, but you may find it rather slow and boring. Speeding up the Tour in Google Earth results in it skipping some images, so instead, we recorded it and sped it up to create the YouTube video below.
Watch the main building roof being completed in the early part of the video.
When creating the heatmap for yesterdays post we discovered some things that we think are worth sharing.
Every point on Earth’s surface can be located with a latitude and longitude. In decimal format these range from -90° to 90° latitude and -180° to 180° longitude. We needed to draw a polygon that goes across the antimeridian (the line at -180° / 180° longitude). We did think ahead and included in our code appropriate conversion to ensure that the coordinates stayed within the correct range. We were surprised to discover that Google Earth drew the polygons wrapped all the way around the globe.
Left: What we wanted. Right: What we got.
After some experimentation in Google Earth, saving what we drew to KML and inspecting the contents we found that Google Earth does handle coordinates less than -180° or greater than 180° longitude. If you want your rectangle to go over the antimeridian rather than all the way around the world, then simply keep the longitudes all positive or all negative and use numbers larger than 180 for some of the points. So, if for example, your rectangle goes from 170° to 190°, then Google Earth will draw it across the antimeridian.
We also found that if you draw a large filled polygon that does wrap around the globe, it is not allowed to cross all lines of longitude.
Achieving this effect with a single filled polygon is not possible. The above screen shot is actually two separate polygons.
It is also impossible to draw a filled polygon that includes the North Pole in its enclosed area. This is actually a direct consequence of how Google Earth draws ‘straight lines’, which we previously discussed in this post. As we noted in that post, unfilled polygons behave quite differently and can wrap around the globe as well as encircle the North Pole. They, however, have a different restriction: the line between any two points always takes the shortest section of a great circle, so to wrap around the globe you need at least one point on the far side of the globe.
The rules for unfilled polygons are different.
There is a ridge in the ocean floor data along the antimeridian.
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.
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.
The post Historical imagery density in Google Earth: Part 2 appeared first on Google Earth Blog.
This week marks the 10th anniversary of Hurricane Katrina. It occurred just months after Google Earth was first released. Although Google Earth had existed as Keyhole Viewer prior to that, Google’s acquisition really helped to popularize it. Katrina was an early test for Google Earth’s capabilities in assisting with rescue efforts and reporting natural disasters. Within days of the disaster, Digital Globe imagery was put into image overlays by users and Google released image overlays with imagery from NOAA. Later the Digital Globe imagery was put into Google Earth’s database.
The Google Earth team was later recognized for their contributions to the hurricane relief efforts.
Two years after Katrina, there was a bit of controversy when people noticed that Google had replaced the post Katrina imagery with older higher resolution imagery from before the hurricane. Google responded to the ensuing media outcry by releasing new post Katrina imagery. At the time many Google Earth enthusiasts suggested a new feature to allow the viewing of alternative imagery sets. This was later added to Google Earth in 2009 as the now familiar and extremely useful ‘historical imagery’ feature.
So, images of a flooded New Orleans are still available in Google Earth today. In addition, the city has been given the 3D treatment, so you can have a look at some of the new flood defences built in response to Katrina.
We can also watch the construction of new defences in ‘historical imagery’:
According to this article over 100,000 houses were destroyed. However, the accompanying video says ‘damaged or destroyed’ and that 30,000 were restored. That still leaves 60,000 homes needing to be pulled down or rebuilt, which should cover a fairly large area. However, they must have been scattered in amongst undamaged houses, as we were unable to find much evidence of large scale rebuilding, except for the location shown below:
Thank you to GEB reader Chris Davis for letting us know of a map he has put together for Google Earth visualizing the relationships between coal mines and power plants in the United States. Grab the KML file here.
Relationship between coal mines and power plants in the US.
The map is in response to the Clean Power Plan, which was finalized by the U.S. Environmental Protection Agency on August 3, 2015. The map makes use of public data sources. The data is not live, but Chris has provided the code he used to generate the map. Find the code and more about why the map was created and what it shows on GitHub.
We especially liked the way the points on the maps are connected by arcs rather than simple straight lines. There are no features in KML to do that automatically, but it turns out to be relatively easy to do in code.
The post Visualizing Shipments from Coal Mines to US Power Plants appeared first on Google Earth Blog.
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.
The post Historical imagery density in Google Earth: Part 1 appeared first on Google Earth Blog.
We have looked at maps created by George of MyReadingMapped many times in the past. However, due to technical issues he shut the site down earlier this year.
He has kindly provided us with some of the KMLs from his vast collection and allowed us to make them available here on GEB. You can download all 155 individual KML files as a ZIP file here. In addition, we have combined them into a single KMZ file and attempted to organize them into folders to make it easier to find what you are interested in. Download the combined KMZ file here.
So what sort of maps can you expect to find?
- Maps of explorers and famous travels including ocean voyages, overland exploration and polar expeditions.
- Maps of ancient civilizations, ruins, lost cities, ghost towns, castles and more.
- Science and the environment:
- Maps for use in teaching geology, ecology and geography.
- Maps relating to the oceans.
- Maps relating to climate change.
- Maps of fossil sites.
- Maps about pollution.
- Maps of disease outbreaks.
- Maps of historic train wrecks, plane crashes and shipwrecks many of which can be seen in Google Earth imagery.
- Maps of wars and historic battles.
- Maps of current events, such as the Trayvon Martin murder case and Boston Marathon Manhunt.
- Maps relating to famous artists.
And many more.
So which are our favourites? To be honest we have not had time to go through them all yet, but they all look interesting and worth a look. Probably the most useful are the ones that can be used in the science classroom, such as the topography of Plate Tectonics or Terrestrial Biomes, amongst others.
Expect to be overwhelmed by the wealth of data.
Thank you to GEB reader Kevin Thuot for letting us know about his Google Earth based World Power Map.
According to the website:
The WorldPower Map provides an interactive view of the global connections between geopolitics, energy infrastructure, and natural resources. The map is free, viewable in Google Earth, and automatically updates with new events.”
To view it in Google Earth download the KML from the website.
We have not verified how accurate or comprehensive the map is, but are rather featuring it because of its excellent use of Google Earth features – and the fact that it is designed for Google Earth in the first place. If you do find inaccuracies or have suggestions for improvements, the website says he welcomes feedback and already has plans to add a lot more to it.
In the past, we have seen a lot of excellent Google Earth based maps, such a this one, that makes good use of Google Earth’s 3D capabilities, sophisticated tours, such as those by Colin Hazlehurst and even whole games, such as those from PlanetInAction. However, with the imminent demise of the Google Earth plugin and many alternative mapping technologies being available, we are seeing a lot fewer maps designed specifically for Google Earth. Google Maps Mania, for example, is able to feature multiple excellent maps per day but the vast majority of them are not provided in KML format.
Google Earth however remains a remarkably good tool for creating maps with easy to use features that other platforms cannot match. The World Power Map makes use of a number of Google Earth features such as 3D models, popups with links to further information and more. It also takes advantage of a feature in KML that allows it to adjust the size of the models depending on view distance – although the implementation in this case has room for improvement. He would also do well to add an introductory Google Earth tour.
Yesterday we talked about how the Street Maps of China are offset from the satellite imagery because of their laws requiring the use of the GCJ-02 datum. The GCJ-02 datum moves the map by different amounts in different places. You can typically work out correct coordinates by a simple addition or subtraction to latitude and longitude for a given area, but the amount to be added or subtracted varies across the country. So for a given city in China a particular set of offsets unique to that city would suffice for most purposes, but for countrywide mapping it is a lot more complicated.
The first thing we did was to create this KML file that shows the relative magnitudes and directions of the offsets.
The smallest offsets are near Haixi (just left of centre), and the largest offsets are in the northeast of China.
Note that the magnitudes displayed above are relative. Actual magnitudes vary from a few metres to a few hundred metres and would not be visible at that scale.
WGS-84 to GCJ-02 KML converter:Convert to GCJ-02
We have also discovered that Baidu Maps uses yet another coordinate system called BD-09 that is based on GCJ-02 but adds further encryption. Baidu provides a converter to BD-09 as part of their API.
While investigating the recent explosions in Tianjin, China, we noticed that the street map of China is out of alignment in both Google Earth and Google Maps. It is tempting to think that the explosions were so large that they shook the street map out of place (the largest, according to Wikipedia, has been estimated as equivalent to 21 tonnes of TNT). However, after a bit of research we have discovered that the street map offset is not new and is actually a result of old Chinese regulations from the cold war era.
It turns out that all maps that are legally created in China must use the GCJ-02 coordinate system, which according to Wikipedia, uses an encryption algorithm that offsets the map by different amounts for different locations. Google has followed the regulations and partnered with Chinese map provider AutoNavi to obtain the data and always shows the map data using the required GCJ-02 datum.
As we have mentioned in previous posts on censorship, countries can control and censor mapping information such as aerial imagery, 3D imagery and street maps that is gathered within their borders, but have little control over satellite imagery unless the company that supplies it operates from within their borders. As a result, both Google Earth and Google Maps do not show the satellite data using the offset GCJ-02 datum but stick with the standard WGS-84 datum used for the rest of the world. This results in the discrepancy we see between the street map and the satellite imagery. However, the Chinese version of Google Maps intended to be viewed from within China does comply with Chinese laws and uses the GCJ-02 datum for the satellite imagery as well. As a result, the street maps and satellite imagery line up nicely, but GPS coordinates will be offset. This is dealt with by Chinese navigation systems, which must convert between the datums to give the correct location on the map.
The China / Hong Kong border in Google Earth. The streets are out of alignment on the Chinese side, but correct on the Hong Kong side. The satellite imagery matches the latitude and longitude as produced by a standard GPS.
In the Chinese version of Google Maps, the situation is reversed. The streets are aligned with satellite imagery in China, but misaligned in Hong Kong. Both satellite imagery and street maps on the Chinese side do not match latitude and longitude as produced by a standard GPS.
Apparently Bing Maps and Apple Maps also follow Chinese regulations and use the GCJ-02 datum, whereas Open Street Map does not (and is thus illegal in China).
We also mentioned China’s strict mapping regulations back in 2006.
The post Chinese street maps out of alignment in Google Earth and Google Maps appeared first on Google Earth Blog.
Open Location Codes also known as Plus Codes are an initiative by Google to provide addresses to parts of the world that do not have Street Names or other easily traceable or official addresses. Google has recently announced on the LatLong blog that Plus Codes are now searchable on Google and Google Maps. There is, however, no mention of Google Earth, and as of this writing, they do not work in Google Earth search.
Plus Codes come in several formats. To identify a specific location on the Earth (to an accuracy of a few metres) you typically need 10 or 11 characters looking something like this 8PVCQ9VH+4C. If the general location is already known then the code can be shortened. This also means that a code can be given as a combination of a locality in traditional format and a short code. However, we discovered that currently this mixed format doesn’t work correctly in either Google Search or Google Maps, but does on plus.codes that Google has made available to make it easier to look up the Plus Code for a given location.
Plus Code:Convert to KML
Note that our converter only works on standard full length plus codes and cannot handle shortened or mixed versions.
When roads are unnamed and not even marked on the map, you can still have an address. And in this remote part of Mongolia, you can even have Street View.
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.
Yesterday we looked at a problem with the Street View layer of Google Earth. We thought it would be interesting to compare the Street View coverage as shown in Google Earth with that shown in Google Maps. However, it is not very easy to compare them side by side due to the different formats.
So, we decided to finally try out something we have long considered doing but not got around to: get a screenshot of a Google Map into Google Earth. We started by capturing a screenshot of the current coverage of Street View in Google Maps at a resolution of 4096×4096 pixels using this file that uses the Google Maps API. Next, we took a screenshot using this screen capture plugin for Chrome.
Google Maps uses the Web Mercator Projection, but Google Earth overlays need to be in the Equirectangular Projection as we mentioned in this post. We found an open source library called GDAL that can convert between different map projections and using suggestions from this page on GIS StackExchange we were able to get our screen shot into the correct projection. We had to use the free image editing program GIMP to convert our initial screen shot to a tiff image, but apart from that there were no difficulties.
All that was left was to create a global overlay from the image and this is the result:
To try it out for yourself, download this KML file.
Also try adjusting the transparency of the image overlay as seen below:
The post Converting a Google Maps screenshot to Google Earth appeared first on Google Earth Blog.
Thank you to GEB reader Chris for letting us know about a problem with the blue Street View layer. It appears that some locations that have Street View do not show the blue lines that normally appear when you use the ‘yellow man’ and hover it over the map.
The location Chris mentioned is Guam, an island in the Pacific. We did some experimenting and discovered an interesting trick to use with the Street View layer. To see the blue outlines, you need to zoom in until the ‘yellow man’ appears in the Google Earth controls. However, if you hover the ‘yellow man’ above the map, and don’t let go of the mouse button, it is possible to zoom back out using the ‘-‘ key and you will still see the blue outlines. We use a Space Navigator which makes it even easier. If you do have a Space Navigator or other controller you can trick Google Earth into keeping the Street View layer on by switching to another program (Alt-Tab in Windows, Command-Tab on Mac) while hovering the ‘yellow man’ over the map. When you switch back, as long as you don’t click anywhere on the map you can move around with the controller without the Street View layer turning off – although we have found this trick is a bit inconsistent and doesn’t always work.
We have seen in the past (Different Zoom – Different Imagery, Historical imagery and zoom) Google Earth shows different imagery depending on the zoom level. It turns out that the Street View layer is no exception and goes through distinct levels of detail as you zoom, very similar to the way it does in Google Maps.
We found that for the islands of Guam and neighbouring Northern Mariana Islands when zoomed in there is are no indications that they have Street View, but when you zoom nearly all the way out, they do show a patch of blue.
Guam and the Northern Mariana Islands (red arrow) do indicate the existence of Street View when zoomed nearly all the way out.
Zoom in a bit and the Daitō Islands(1) and the Ogasawara Islands(2) indicate they have Street View, but similarly sized Guam and the Northern Mariana Islands(3) do not.
We found a number of other places where the blue outlines do not show except when zoomed nearly all the way out, even though there is Street View available. These include areas in Madagascar, Tanzania, South Georgia and India.
India is particularly interesting, as the blue pattern changes quite significantly at different zoom levels.
We also found that at higher zoom levels the blue was out of alignment – most noticeable if you zoom all the way out as far as possible, as seen above.
It would be useful if Google were to make the blue outlines a proper layer that could be turned on in the ‘layers’ panel, as that would generally make it easier to find Street View in Google Earth.
Also, we forgot to mention in our last Street View update post that the US territory of American Samoa got Street View imagery in May. Thank you to GEB reader Kyle for alerting us to it.
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:
- The Amtrak train derailment in Philadelphia and a landslide in Salgar, Columbia.
- Flooding in Georgia and Texas.
- Flooding in Brazil.
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.