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Mis à jour : il y a 22 min 18 sec

KML Polygon merger

il y a 1 heure 40 min

We have recently got a bit behind on updating our 3D imagery KML file. Part of the reason for this is the complexity of dealing with new areas that are extensions of already existing imagery.

Columbus, Ohio, got expanded 3D imagery (2). What you see above is what we want to appear in the timeline.

For the ‘Sorted by country’ section, we want to combine the new outline with the old outline removing the shared border.

We already have the outline of the old extent of the 3D imagery (region 1) and we need two new outlines, one of just the newly covered area (region 2) that we use in the timeline and one showing the total area now covered that is used for the ‘Sorted by country’ section. So we want two new Polygons, one using segments 3 and 4 and another using segments 3 and 5.

It is possible to draw one of the new Polygons by starting with the existing polygon (1) and deleting the points in either segment 4 or 5 and then drawing segment 3. However, it still means that at least one segment of an outline needs to be redrawn. What would be ideal is to take a segment of the already existing outline and combine it with segments of the newly covered area outline. However Google Earth has no easy way to do this. So we have written a bit of JavaScript to accomplish the task and we thought that it might be something that other people who work with KML regions might find useful so we decided to share it.

To use our merger utility, first make sure you have two Polygon outlines that share a common border. Remove all points from the common border except the two at the ends of the shared border for each Polygon. Save the two polygons either in two separate KML files or a single KML file. Upload them below, then click the ‘Download merged Polygon’ button. Open the downloaded file in Google Earth.


Download merged Polygon

It has not yet been tested very thoroughly so if you find any bugs please let us know in the comments. One problem that we encountered is that Google Earth Polygons may go clockwise or counter clockwise, so when combining two polygons by simply concatenating the list of points, it is possible to get a figure 8. We have tried to check for this and automatically correct it.

The post KML Polygon merger appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Google Maps API Maximum Zoom – Part 6: Resolution

mar 06-10-2015

We have recently been looking at our map created from the Google Maps API’s Maximum Zoom data:
Google Maps API Maximum Zoom – Part 1: Data collection
Google Maps API Maximum Zoom – Part 2: Overview
Google Maps API Maximum Zoom – Part 3: Starting on a more detailed look
Google Maps API Maximum Zoom – Part 4: Continuing the detailed look
Google Maps API Maximum Zoom – Part 5: A detailed look – the Americas

As we have mentioned before, the maximum zoom available in Google Maps varies between 7 and 22. However, if we correct for the magnification at the poles, the minimum becomes 9. Below you can see samples of imagery at some of the zoom levels. We have skipped over a few levels either due to lack of imagery, or because they are too close to see much difference. Note the scale on each image.

We have corrected for the magnification at the poles and then separated out each zoom level into its own overlay, so if say you want to find all Landsat imagery (Zoom level 16) then you can display just that.

To view the overlays in Google Earth, download this KML file

When looking at the highest zoom level our map only picked up very high resolution imagery in Europe. However, this is partly because our survey was not fine enough to pick up small patches of high resolution, such as:

The post Google Maps API Maximum Zoom – Part 6: Resolution appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Google Maps API Maximum Zoom – Part 5: A detailed look – the Americas

lun 05-10-2015

We have recently been looking at our map created from the Google Maps API’s Maximum Zoom data:
Google Maps API Maximum Zoom – Part 1: Data collection
Google Maps API Maximum Zoom – Part 2: Overview
Google Maps API Maximum Zoom – Part 3: Starting on a more detailed look
Google Maps API Maximum Zoom – Part 4: Continuing the detailed look

Today we are continuing with the detailed look, this time at the Americas.

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South America

     As we have seen with other areas, South America has two sets of background imagery. Low resolution Landsat imagery is used in the northern half of the continent and the southern countries of Central America. There is also a patch of Landsat imagery in the eastern part of Brazil

     The rest of the continent uses Cnes/Spot Image as the background image.

     High resolution satellite imagery largely matches the population density and is sparsest over the Amazon Rain Forest. We had expected to see a lack of imagery over the Andes due to snow cover, but in fact it seems the Andes have relatively good coverage. The approximate line of the Amazon River can also be seen to have better coverage than surrounding areas.

     Spots of aerial imagery can be seen in a number of Brazilian cities and Cordoba, Argentina. In all the areas we checked, the imagery showed no attribution, suggesting it belongs to Google, probably gathered during its 3D imagery collection. Note that 3D imagery is not included in this data and South America does have quite a lot of 3D imagery.

North America

     Landsat imagery is used as the ‘background’ for northern Canada. The Great Lakes also show up as this resolution, but they have sea floor data (supplied by NOAA), not satellite imagery. Lake of the Woods, a lake in Northern Minnesota, has low resolution imagery attributed to Terrametrics, as is Lake Victoria in Africa.

     Mexico and much of Canada use Cnes/Spot Image as the background imagery. Interestingly it seems to have a northernmost limit of about 60.3°N

     High resolution satellite imagery coverage is poor over Canada, especially towards the North. Mexico has reasonably good satellite imagery coverage.

     Canada and Mexico do have some small patches of aerial imagery. The US is notable for being entirely covered with aerial imagery. Even the lighter shades in the US are low resolution aerial imagery. Although a lot of the imagery was actually gathered by Google, the complete coverage can be attributed to government agencies, which gather aerial imagery and Google has obtained it from them.

     The US has a number of extra dark red patches indicating extra high resolution aerial imagery.

Note that the US, Canada and Mexico all have significant 3D imagery that is not included in this data.

The post Google Maps API Maximum Zoom – Part 5: A detailed look – the Americas appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Explore Mars in Google Earth

ven 02-10-2015

This has been a big week for Mars with the new NASA discovery of flowing water on the red planet, and the release of a blockbuster movie “The Martian” based on the New York Times best seller of the same name by Andy Weir and starring Matt Damon. An excellent book by the way! So, this is a good time to remind everyone that Google Earth also can portray Mars just like it does for the Earth. Mars in Google Earth has a fantastic archive of data from NASA (and other sources) from orbital imaging platforms, and Mars landers including 3D terrain, global imagery, high resolution orbital imagery, lander photos, and even lander 360 panoramas. The lander locations and tracks can be viewed, as well as their last known positions. Most of the data is current showing even the latest position of Curiosity and Opportunity. Mars for Google Earth only works in the desktop application (not on Google Earth for mobile).

To get started, you simply look for the little planet icon at the top center of Google Earth and click on it for a list of options including Mars (you’ll see there are also versions for Sky and Moon). Click on Mars, and the Earth globe will turn into Mars. Mars was released in February 2009 (see original Mars review).

See below for my original video review of what Mars for Google Earth is really like:

You can spend hours exploring Mars and the layers Google created to explore the data from the various landers and orbiters. I especially enjoy the panoramas by Opportunity and Curiosity. An important tip if you want to explore the panoramas is that you might need to expand the time slider selectors that appear in the upper left so they show the full time span. Otherwise the panoramas may load up invisible until you find the time when it was taken.

And here’s a cool trick even long-time users of Google Earth might not have discovered. Fans know that Google Earth has a built-in flight simulator (read more), well you can also use the flight simulator on Mars! Kind a fun to fly around the crater at the top of Mons Olympus, or through the huge canyon of Valleris Maneris. Just look for the menu choice “View->Flight Simulator”. I recommend the F-16 for faster flying. You’ll need to learn the flight simulator a bit to fly well. Here’s a view of flying on Mars.

Flying on Mars

I’m planning to see the movie this weekend. Can’t wait to see it!

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Catégories: Sites Anglophones

Google Maps API Maximum Zoom – Part 4: Continuing the detailed look

ven 02-10-2015

We have recently been looking at our map created from the Google Maps API’s Maximum Zoom data:
Google Maps API Maximum Zoom – Part 1: Data collection
Google Maps API Maximum Zoom – Part 2: Overview
Google Maps API Maximum Zoom – Part 3: Starting on a more detailed look
Today we are continuing with the detailed look at specific regions of the world.

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East Asia

     Lake Baikal in Russia, shows up in the data as a yellow streak. It has lake floor data from “Data INTAS Project 99-1669”. As far as we know, this lake and the Great Lakes of North America are the only lakes to have floor data in Google Earth. We had never really noticed this lake before, despite it apparently being the largest freshwater lake (by volume) in the world.

     Landsat imagery can be seen as a ‘background image’ in parts of Tibet, North East China, about half of Mongolia and most of Russia.

     CNES/Spot Image data is used as the ‘background image’ for the remaining parts of East Asia.

     Satellite image coverage is quite good for East Asia and steadily improving. The survey of recent imagery we looked at last month showed significant additions of CNES/Astrum imagery in China and the Koreas.

     Aerial imagery can be found in Taiwan and Japan. As we said in our last post, note that 3D imagery is not shown in this dataset. Japan now has a significant amount of 3D imagery, and in the last few days Hong Kong was added. We are not aware of any aerial imagery in Mainland China or either of the Koreas.

South East Asia

     The tropical forests of the Malay archipelago have very poor satellite imagery coverage. More than half the land is covered by the ‘background’ Landsat imagery.

     The continental countries of South East Asia use CNES/Spot Image as their ‘background imagery’.

     The Malay archipelago has quite a lot of false colour or black and white satellite imagery in ‘historical imagery’, most of which is heavily clouded, suggesting that the reason for the lack of high resolution satellite imagery is due to frequent cloud cover.

     The only aerial imagery in this region seems to be a patch covering Manila in the Philippines.

Australia and New Zealand

     Australia and New Zealand have CNES/Spot Image as their background imagery.

     Australia’s high resolution satellite imagery mostly matches the population density, with rather poor coverage over the interior deserts. New Zealand’s coverage is quite good.

          Both Australia and New Zealand have aerial imagery for major cities and they also have 3D coverage, which is not reflected in this data. The aerial imagery varies slightly in resolution, hence the different shades of red. Our dataset did not pick up the very high resolution patches captured for Australia Day in 2007.

In our next post in this series we will look at the Americas.

The post Google Maps API Maximum Zoom – Part 4: Continuing the detailed look appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Google Maps API Maximum Zoom – Part 3: Starting on a more detailed look

jeu 01-10-2015

We have recently been looking at our map created from the Google Maps API’s Maximum Zoom data:
Google Maps API Maximum Zoom – Part 1: Data collection
Google Maps API Maximum Zoom – Part 2: Overview

Today we are starting to take a more detailed look at specific regions of the world.

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As we have explained in the past, Google Earth has several ‘background imagery’ data sets that it uses when there is no good quality high resolution satellite imagery available. In Africa there are two distinct sets of ‘background imagery’.

     Across the equatorial region of Africa and a curious strip in the east of Libya, the background imagery is low resolution Landsat data, essentially the same as is seen globally when zoomed out. This background imagery shows through most noticeably where there are rain forests. We believe the lack of higher resolution satellite imagery there may be due to the high frequency of cloud cover.

Lake Victoria is an exception and has imagery attributed to TerraMetrics which, according to this page, used to supply the global ‘background image’ for Google Earth.

     For the rest of Africa, the default background imagery is slightly higher resolution satellite imagery from CNES/Spot Image. It is most visible across the Sahara. We believe the absence of higher resolution imagery over the Sahara is a combination of lack of interest due to the low population and difficult photographic conditions. It is notable that much of the high resolution satellite imagery in the region is false colour imagery suggesting that visible light imagery is difficult to capture because of the bright desert sands.

     Most of Africa has reasonably good high resolution satellite imagery coverage supplied by DigitalGlobe and CNES/Astrum. It is fairly easy to visually distinguish between the two in historical imagery, as the CNES/Astrum imagery has a greenish tint to it. Also, the CNES/Astrum imagery tends to be in approximately equal-sided parallelograms, whereas about half the DigitalGlobe imagery is in strips covering one degree of longitude or latitude.

     Only two spots of Aerial imagery were picked up by our map: Bloemfontein and Cape Town, both in South Africa. There is more aerial imagery in South Africa, but our dataset is not high enough resolution to pick it up.


The obvious band at 60° north is explained in this post.

It is important to note here that the data we are looking at is based on maps created using the Google Maps API. See this page as an example. One significant difference between Google Maps created this way is that they do not show 3D imagery. Europe has a significant amount of 3D imagery, so what we see in the Google Maps API generated map may be quite different from what can be seen on the standard Google Maps website or in Google Earth.

     As with Africa, Europe has two sets of ‘background imagery’. Low resolution Landsat data can be seen in Ireland, Austria and the northern parts of Norway, Sweden and Finland.

     The second slightly higher resolution set of ‘background imagery’ comes from CNES/Spot Image.

                 Most of Western Europe is a patchwork of aerial imagery of various resolutions from a wide variety of suppliers, including a significant amount collected by Google itself. There is a distinct transition to satellite imagery over Eastern Europe, more obvious in ‘historical imagery’ than in the ‘maximum zoom’ data. Poland and Romania do have some aerial imagery and the country of Montenegro stands out as having its own patch of aerial imagery almost exactly matching its borders. Northern Scandinavia and Ireland are somewhat lacking in aerial imagery.

The Middle East and Central Asia

     Landsat imagery is used as a ‘background image’ for Saudi Arabia, most of Russia, and parts of Kyrgyzstan

     The rest of this region uses Cnes/Spot Image imagery as the ‘background image’. Iraq and Afghanistan really stand out because they have not had any imagery updates for several years. We believe this is deliberate censorship due to the wars in those countries. The sparsity of high resolution satellite imagery in Saudi Arabia and northern Asia is probably, as with the Sahara, a combination of lack of interest due to the low population and difficult photographic conditions. Saudi Arabia has bright sand, and northern Asia has snow cover and poor light for much of the year.

     Pakistan and India have remarkably good coverage with high resolution satellite imagery. Nepal, Bhutan and Bangladesh are also pretty well covered.

There appears to be no aerial imagery in this region. We believe some countries have not allowed Google to gather aerial imagery and for others there may simply be a lack of local suppliers.

We will continue with further regions of the globe in a later post.

The post Google Maps API Maximum Zoom – Part 3: Starting on a more detailed look appeared first on Google Earth Blog.

Catégories: Sites Anglophones

The best of Google Earth for September 2015

mer 30-09-2015

As far as we are aware there have been no imagery updates in September. The most recent imagery currently available in historical imagery is dated 18th August. We have been waiting for coverage of this year’s Burning Man. We believe DigitalGlobe did capture imagery of it but it is not yet in Google Earth.

Google has continued to release 3D imagery and we apologize for being behind with our KML of 3D areas. It is notable that a significant proportion of 3D updates are updated areas rather than entirely new areas. It is time Google started providing dates with the imagery and possibly a ‘historical 3D imagery’ option.

Street View was added to Kenyan parks and the Philippines, and there were also additions in Argentina and Indonesia.

We had a look at the California wild fires using Landsat imagery. Thank you to GEB reader Christiaan Adams for letting us know in the comments about some false colour Digital Globe imagery available via this KML file from Google Crisis Response. Also thank you to GEB reader Robert Tissell for pointing us to other fire detection resources based on VIIRS data, including this website.

We had a look at a way to find recent imagery using the Google Earth plugin. We mapped out the imagery newer than July 1st, 2015 and classified it by imagery supplier. See the results with this KML file. We also had a look at some interesting sights we found in the imagery while classifying it. Thank you to GEB reader Raul for providing some interesting information in the comments about the demolished houses we found.

We noticed that the country of Moldova has different overview imagery from the rest of the globe. Thank you to GEB reader ‘S. H.’ for letting us know that the change was made circa August 19th, 2015. We still do not know why the change was made.

We experimented with using Google Earth Pro’s bulk geocoding feature for geocoding regions such as suburbs, cities and countries. Although it is clearly a useful feature and is fairly easy to use, there is room for improvement. A feature we would really like to see is a geocoder that can return the outline of an area rather than a simple placemark. If any of our readers knows of any such geocoding service, please let us know.

We had a look at an image released by the European Space Agency showing the surface deformation from the Chile Earthquake.

We have just started a series of posts (Part 1: Data Collection, Part 2: Overview ), having a look at the data we can get from the Google Maps API Maximum Zoom Imagery Service. We will continue to look at the data in October.

The post The best of Google Earth for September 2015 appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Google Maps API Maximum Zoom – Part 2: Overview

mar 29-09-2015

Yesterday we showed you a map of the maximum available zoom level found in Google Maps. If you don’t already have it, download this KML file to view it in Google Earth.

Today we are looking at general features of the data.

First of all, we need to know what the colours mean. The colours represent the various available zoom levels in Google Maps, starting with low resolution at 7 to high resolution at 22. This can be roughly interpreted as follows:

.keyTable tr td:first-child{ width:12px; height:22px; } .keyTable tr td{ padding-left:10px; }   Low resolution ocean floor   High resolution ocean floor   Coastal areas   Very low resolution satellite imagery (Landsat background imagery) Low resolution satellite imagery (CNES/Spot Image background imagery) High resolution satellite imagery (DigitalGlobe or CNES Astrium) Aerial Imagery (higher resolution than satellite imagery) Exceptionally high resolution Aerial Imagery

Google Maps via API
To better understand Google Maps Zoom levels or to explore the data for a given location, you can use this page, which shows a full screen Google Map using the Google Maps API. It behaves a little differently from the standard Google Maps website. The standard Google Maps website restricts how far you can zoom in based on the imagery available, however, it always shows imagery. The above map, obtained via the API, lets you zoom in beyond the maximum prefered amount, and when you do it displays map tiles labelled “Sorry, we have no imagery here”.

You will notice in our map that there are noticeable bands in the data towards the poles at 60° and 75° latitude, both north and south. We believe these are an artifact of the Google Maps projection, which spreads out the poles, thus magnifying any imagery towards the poles and in consequence requiring less zoom in order to see a given resolution of imagery.

In our data collection we only went 80° north and south. Google Maps itself only goes to 85° north and south as a consequence of its map projection.

Google Earth has noticeable bands in the actual imagery at 80° north across Greenland and about 82.6° south in Antarctica. These are actual changes in the imagery datasets. The absence of high resolution near the poles may be due to the orbits of the imaging satellites or ‘sun angle constraints’.

The spider web of tracks across the oceans noticeable in our data reflect the paths of ships equipped with sonar for mapping the ocean floor. The tracks of higher resolution imagery are clearly visible in Google Earth and have in the past been mistaken for Atlantis or an alien base.

In our next post in this series we will be looking in a bit more detail at the various types of imagery found over land.

The post Google Maps API Maximum Zoom – Part 2: Overview appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Google Maps API Maximum Zoom – Part 1: Data collection

lun 28-09-2015

Ever since we did the posts on historical imagery density we have been looking for a way to map parts of the earth that do not yet have historical imagery. Sadly, the Google Earth plugin does not report historical imagery accurately for such areas.

We recently discovered that the Google Maps API provides a service known as the Maximum Zoom Imagery Service, which allows you to find out what the maximum zoom available in Google Maps is for a given latitude and longitude. The maximum zoom available when in ‘Earth’ mode is dependent on what imagery is available in Google Maps. Since the imagery in Google Maps is almost the same as the default layer in Google Earth, this service can tell us a lot about the imagery in Google Earth.

Today we are just looking at how we gathered the data and prepared it for viewing in Google Earth. In later posts we will look at what is actually in the data and what we can learn about Google Maps and Google Earth imagery.

We queried the Maximum Zoom Imagery Service for every 0.1° from -80° to +80° latitude and every 0.1° of longitude. The result is 5.76 million points of data, which results in multiple KMLs totalling over 1Gb. To display it as a heat map we could have created a KML file with each rectangle as a polygon, but that would probably have crashed Google Earth. So instead we used the technique we used when finding imagery updates and converted the data to an image and displayed that using an image overlay.

If you display each data point as a single pixel, then Google Earth tends to blur the image, so we resized the image to have each data point 4 X 4 pixels. The Maximum Zoom available in Google Maps for the locations we collected varies from 7 to 22, 7 being the lowest resolution imagery and 22 being the highest resolution imagery.

To see it for yourself in Google Earth download this KMl file

The post Google Maps API Maximum Zoom – Part 1: Data collection appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Surface deformation after Chile earthquake

ven 25-09-2015

On September 16th, 2015 a magnitude 8.3 earthquake struck just off the coast of Chile. It was more energetic than the Nepal Earthquake earlier this year, but resulted in far less casualties because Chile has more frequent large earthquakes and is better prepared. For the Nepal Earthquake we showed you a map from NASA showing surface deformation resulting from the earthquake.

Now the European Space Agency has released a similar map showing the surface deformation from the Chile Earthquake.

To see it in Google Earth download this KML file

The ‘Earthquakes’ layer in Google Earth does not show the Chilean earthquake yet. However, the USGS provides up to date KML files on this web page

We chose this one, which shows all earthquakes over magnitude 2.5 from the last 30 days.

As you can see below, the main quake (largest circle) was further south than you might have expected it to be based on the deformation pattern. The cluster of aftershocks, however, do seem to centre on the same location as the deformation pattern.

The post Surface deformation after Chile earthquake appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Tracking wild fires in Google Earth

jeu 24-09-2015

It is fire season in the western states of the US and one recent fire in California has been named the fourth most destructive in California’s history. US president Obama has declared it a major disaster.

  • We have looked at a number of resources for tracking wild fires in the past. The best ones include:

  • The US Department of Agriculture Forest Service provides a variety of fire information via KMLs. To get all the data at once download this KML.

  • One of the sources of data used is NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) whose data can be obtained directly from NASA via this web page. NASA provides MODIS data for the whole globe. You can get fire data for a particular region of the earth, or download KMLs with data for the whole globe. Keep in mind that the the global ones are quite big and may cause performance issues in Google Earth.

The Californian government provides a website called CAL FIRE which includes a lot of information about fires, including this map of wild fires in California showing the actual extents of the fires. You can view it in Google Earth with this KML file.

As far as we can tell, the most recent imagery in Google Earth is from August 18th, so we cannot currently see the damage caused by the fires. However, it is possible to download Landsat imagery and view it in Google Earth and actually see some of the land affected by the recent fires. We previously experimented with getting Landsat data into Google Earth. The method we showed you required some rather large downloads. We have since found that if quality is not an issue then the easiest way to quickly check Landsat imagery is as follows:

  • The following instructions require Google Earth Pro (which is free).
  • Start with USGS Earth Explorer. Find the location you are interested in and mark it on the map.
  • On the datasets tab, select Landsat Archive->L8 OLI/TIRS
  • Click the ‘Results’ button.
  • Choose an image closest to the date you are interested in. Ignore any night time images (almost entirely black). In our case we found one covering part of California just north of San Francisco, captured on September 20th.
  • Click the icon next to the image labelled ‘download options’.
  • Download the file labelled “LandsatLook images with Geographic Reference”.
  • Unzip the downloaded files to a folder on your computer.
  • Find the file named with just the Landsat reference number and a .jpg extension. Drag it to Google Earth Pro.
  • Google Earth Pro automatically detects where to place it and creates an image overlay for you. However, it says that the image exceeds the maximum allowed size. You can choose to either crop the image, or scale it. In our case we chose to scale it.

This is what the result looks like in Google Earth:

To view it in Google Earth you can simply download this KML file.

Comparing this with the above mentioned CAL FIRE map, we find that the two large brown patches south-east of Clear Lake almost exactly match the outlines given for Valley Fire, Jerusalem Fire and Rocky Fire.

Getting the outlines to show on top of the image overlay required adjusting their altitude to 1000m above ground.

Fires detected by MODIS in the last 24 hours in central Africa. There are actually far more fires in Africa right now than in California. Hopefully they are less devastating.

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Catégories: Sites Anglophones

Geocoding with Google Earth Pro Import

mer 23-09-2015

When Google Earth Pro was made available for free earlier this year we showed you that it could import addresses to Placemarks. However, what may not have been so obvious is that the geocoding that it does works equally well with locations such as suburbs, cities or even countries.

To demonstrate how it works we chose three lists from Wikipedia.

The first is a list of countries and dependencies by area. The first step was to copy the data into Microsoft Excel and clean it up a bit. We decided to keep only the figures for the total area in square kilometres. We then saved the data as a csv file and imported it into Google Earth. There were 47 countries or dependencies that Google Earth failed to geocode on the first try. We managed to resolve some of the dependencies by removing the country name which was in brackets.

Strangely enough there were still 18 entries that failed:

We also noted that in the resulting KML, many of the Placemarks do not match the exact locations of country names as seen in Google Earth although, the ones we checked were at least in the correct countries.

It is also possible to colour code the Placemarks based on the figures in one of the columns, but we found that it didn’t really work well for this particular dataset, as the large area of Russia in relation to all the others caused the colour scale to be ineffective and the Placemarks are not really large enough to see the effect on the map.

The second is a list of the cities of Japan. We used the English name column as the Japanese characters would have posed some challenges. Google Earth Pro failed to geocode 125 of the 812 cities in the list. We tested some of the failed entries by searching in Google Maps and it was able to find them without any problem.

Japanese Cities according to Wikipedia. The colour of the icon reflects population density, and the height reflects population.

The third is a list of Cape Town Suburbs. To help with the geocoding we added the city and country to a column in Excel. On the first attempt, it failed to geocode 17 of the 125 suburbs. 7 were easily repaired by removing alternate names listed in brackets. However, there were still 10 suburbs that it failed to geocode. We tried searching for them in Google Maps and some were correctly found in Google Maps, while some where not.

Suburbs of Cape Town with Post Codes in the popups.


  • It appears Google Earth Pro is not using Google maps data for geocoding.

  • When Google Earth Pro fails to geocode some location and you proceed without correcting them, they are all given the coordinates 0° latitude 0° longitude. You can then, if you wish, manually relocate them.

  • What we did not do for any of the above lists was to check whether the locations were accurate.

  • The geocoding returns just a Placemark with its latitude and longitude. A search for countries, cities or suburbs in Google Maps outlines the geographic area. Having a geocoding service that similarly returns the region for display in Google Earth would be very useful.

Overall, it looks like a useful service, however, if you find that there are a large number of failures, as we did for Japan, you may wish to search the web for alternative geocoding services and then import the data after the geocoding is already done.

To view the above datasets in Google Earth download this KML file.

The post Geocoding with Google Earth Pro Import appeared first on Google Earth Blog.

Catégories: Sites Anglophones

‘Supermoon’ Lunar Eclipse on September 27

mar 22-09-2015

This Sunday, September 27th, 2015 there will be a total eclipse of the Moon known as a ‘Supermoon’ Lunar Eclipse. We have looked at both solar and lunar eclipses many times in the past. One of the best resources for exploring eclipses is the HeyWhatsThat eclipse page, which uses Google Earth plugin. Chrome stopped supporting the Google Earth plugin from the first of September and the latest versions of Internet Explorer don’t seem to support it either. However, it still works in Firefox, although you have to give it permission and then refresh the page. If you also allow it to use your location then it can give you the local time at which the eclipse will take place.

Another site for eclipses is Xavier Jubier’s, which includes an ‘eclipse visibility’ map.

The Slooh Community Observatory will be broadcasting it live, but it requires membership.

HeyWhatsThat showing the Google Earth plugin still working in Firefox. We believe Safari also still supports it.

The post ‘Supermoon’ Lunar Eclipse on September 27 appeared first on Google Earth Blog.

Catégories: Sites Anglophones

New South Wales Globe

lun 21-09-2015

We have introduced you to NSW Globe in the past, but it is well worth a revisit.

New South Wales is an Australian state. Its local government has made available, via a Google Earth KML file found on this site, a wealth of information. The most recent addition is property price and sale information for the whole state.

The popup includes links to property sales information from the last five years for the property in question or for the street or suburb.

Most interesting is how all the data is served. We believe that they are using Google Earth Enterprise. Note that the KML file does not open in ‘Places’ but rather in the ‘Layers’ section. We have seen this before with links from the Google Maps Gallery. One of the side effects of this is that you cannot save it for later, so you have to reopen the downloaded KML file every time you want to view the data. It also stops you from downloading all the data locally and sharing it – a form of copy protection.

The imagery loads smoothly as if it is just another Google Earth layer. Also interesting is that it comes with its own terrain model (as a selectable layer) that is slightly different from Google Earth’s built in terrain. From what we could tell by looking around Sydney, Google Earth’s terrain model is higher resolution.

The post New South Wales Globe appeared first on Google Earth Blog.

Catégories: Sites Anglophones

Moldova stands out in Google Earth

ven 18-09-2015

As we have discussed before, Google Earth shows different imagery at different zoom levels. When in the default view, the global image used is created from Landsat imagery.

The landsat imagery, however, does not quite cover the whole globe. The oceans are excluded, as well as the poles, but most curiously is the fact that recently the country of Moldova has got its own set of imagery.

The imagery over Moldova stands out, as it has not been blended into the rest of the imagery.

We are not certain when it was changed, but it was apparently after we took the screenshot used in this post in July.

The imagery shows the copyright message Cnes/SPOT Image. We do not know why only Moldova was changed and we can’t think of any reason for it. It is only low resolution imagery and only visible when zoomed out. When you zoom in most of the country has higher resolution satellite imagery supplied by DigitalGlobe and CNES/Astrum.

If any of our readers knows what the reason is, please let us know in the comments.

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Catégories: Sites Anglophones

Street View comes to the Philippines

jeu 17-09-2015

Only a day after Google added Street View to some Kenyan parks they have also added Street View for the Philippines. Read more about it on Google’s Lat Long blog.

As can be seen below, there have also been additions in Indonesia. The red spots in India are most likely not proper Street View but rather user-submitted panoramas.

Street View changes between 15th and 16th September 2015.Changes are marked in Red. World map.

This time most of the blue outlines can be seen in Google Earth, so there is no difficulty locating the Street View. However, we did find some locations that had footage captured with the Trekker that did not have blue outlines. One such location is Mount Pulag, seen below.

Mount Pulag, Philippines. To view it in Google Earth download this KML file

A location known as Dinosaurs Island has animatronic dinosaurs. To view it in Google Earth download this KML file

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Catégories: Sites Anglophones

Street View in Kenyan parks

mer 16-09-2015

Google has released Street View for Samburu National Reserve and Lewa Wildlife Conservancy in Kenya. Read more about it on Google’s Lat Long Blog. Be sure to watch the YouTube video as it shows the Street View camera being put on a vehicle as well as mentioning their use of network links in Google Earth to view live tracking data.

Street View changes from July 25th, 2015 to September 15th, 2015. Changes are marked in red. Large version.

As you can see above, the biggest changes to Street View since we last looked at it have been expansions to the Street View in Argentina.

As we discussed in this post, Google Earth doesn’t always show the blue outlines for Street View and Tanzania is one such location. The Street View is there, however, as can be demonstrated by locating it in Google Maps and then using our Street View to KML converter to open it in Google Earth.

To see the above elephant in Google Earth download this KML file

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Catégories: Sites Anglophones

Fresnel Zones in Google Earth

mar 15-09-2015

A Fresnel Zone is a region of space between a wireless transmitter and receiver within which obstructions may cause interference to the signal. A couple of years ago we showed you a site called EngineMaps that offers to create a KML showing the fresnel zones for a given pair of points. As far as we can tell it is a paid for service.

Thank you to GEB reader Kevin of Loxcel Geomatics for letting us know about their own implementation of a similar idea. Loxcel Geomatics provides maps of cell tower locations in Canada. They have added a new feature to their maps that can generate a KML showing the Fresnel Zone between a given location and a known tower. Read more about it here.

To try it out, they offer this demo map of the cell towers in a region of Ottawa, Canada. Place the cross that is in the centre of the map at the location where you want the receiver to be, then click the button labelled ‘Closest sites interference’. A popup opens where you can select the tower of your choice and adjust the height of the receiver.

Try lowering the antenna height and it will show when there is interference. They must have a 3D map of Ottawa built into the calculations.

If you then click the ‘3D Fresnel Zone’ button, it will download a KML file to show you the Fresnel Zone in Google Earth.

We just might get a signal between the buildings.

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Catégories: Sites Anglophones

The Google Earth cache

lun 14-09-2015

The Google Earth cache not only provides significant performance benefits but also allows Google Earth to be used offline. For more on how to do this, see this post by Frank.

The cache settings can be found in Tools->Options->Cache. A common complaint by Google Earth users is that the maximum sizes have not been increased for a long time and thus seem somewhat small for todays computers. Currently the maximum disk cache size is 2048 MB and the maximum memory cache size is 1024 MB. If you have sufficient memory and hard disk space then set them to their maximum.

The default location of the cache in Windows is in %AppData%\LocalLow\Google\GoogleEarth, but it is possible to move it to the location of your choice by modifying the registry setting HKEY_CURRENT_USER\Software\Google\Google Earth\CachePath for the standard version and HKEY_CURRENT_USER\Software\Google\Google Earth Pro\CachePath for Google Earth Pro. Since mechanical hard disks are often the slowest part of a modern computer you should experience some performance gains by putting the cache on an SSD if you have one or even a USB 3 memory stick.

We found while using the Google Earth plugin to map historical imagery density that the Google Earth cache filled up about 700mb for each 5 x 5 degree square of the earth. That figure is just approximate, as the area covered by 5 degrees of longitude varies considerably by latitude, and how much the cache gets filled varies depending on what zoom you are at in Google Earth. In addition, we were in ‘historical imagery’ mode, which loads significantly more imagery than the default view. Nevertheless, it demonstrates that caching a whole continent at high resolution is impossible within the current 2 GB limit.

We also discovered that the Google Earth plugin creates its own cache rather than reusing the Google Earth cache. In addition, having multiple instances of the Google Earth plugin open results in multiple caches being created. In our case the total cache folder ended up growing to well over 8GB.

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Catégories: Sites Anglophones

Google Earth Community collections: craters

ven 11-09-2015

In April this year, Google retired the old Google Earth Community (GEC) forums that were hosted by Google. The GEC did not die but instead migrated to a new platform, where it continues to be an active community of Google Earth enthusiasts with interesting threads on a variety of topics and some amazing collections for Google Earth.

Today we are showcasing one of those collections: the consolidated impact crater database by GEC member ‘ekafeman’. If you are a long time reader of GEB then you have probably seen similar collections before, as we have looked at impact craters many times in the past.

You have to join the GEC to download KMLs, but it is free and well worth the effort. So head on over and get the KML file from this thread. Be sure to check the key, as many of the marked locations are not confirmed or believed to not be actual impact craters.

Don’t be fooled by near perfect circles. Apparently the large circle in the Hudson Bay, Canada, is most likely not an impact crater, whereas the two smaller circles to the right are.

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Catégories: Sites Anglophones