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Seeing imperfect orthorectifcation in Google Earth imagery

October 20, 2015

Yesterday we talked about orthorectification and how it is imperfect, especially when using an inaccurate terrain model. We thought we would have a look at the effect using historical imagery. We used a variation on two JavaScript tools we have created in the past for animating historical imagery using the Google Earth plugin and using Google Earth Tours. This enabled us to create tours which animate only a selection of historical imagery and exclude lower quality images. Because Google Earth does not allow us to play the tours at a reasonable speed (it omits images), we recorded the tours and then sped up the recording.

We chose three locations that we know have significant elevation variation as well as a lot of satellite imagery. They are Devil’s Peak, Cape Town, South Africa, Rio de Janeiro, Brazil, and Calama, Chile.

If you look carefully, you can see that some locations move more than others.

The buildings at 1 and the bridge at 2 seem to move much less than the surrounding imagery. This suggests that the terrain model for these locations is closer to the true altitude than for surrounding areas.

You can download the Google Earth tours we used to create the video here.

Filed Under: Site News Tagged With: animation, Google Earth tour, historical imagery, measure

Google Earth measurement and image alignment

October 19, 2015

As we saw last week Google Earth’s measuring tools are actually quite accurate when measuring distances based on latitude and longitude, and can even take altitude into account. However, many people will be measuring distances between objects visible in satellite imagery and will not have the actual latitude and longitude of the objects in question. So, it is important to take into account various issues relating to what we see in satellite imagery, such as alignment issues.

Aligning satellite imagery correctly is complicated. We have created many image overlays (such as this one showing the surface deformation after the Chile earthquake) and we have never managed to get exact alignment between the overlay and the underlying satellite imagery in Google Earth. Even when we are trying to align an image that is already in Google Earth, such as the DigitalGlobe image of Shanghai, China, from this post, exact alignment is not possible. This is because satellite imagery must go through a process known as orthorectification, which uses a model of the terrain and knowledge of the position of the satellite at the time the photo was taken and the angle at which it was taken to adjust the image.

As we can see with the tallest building in the world, the Burj Khalifa, if the satellite takes an image from anywhere other than directly overhead, the top of the building can be quite a long way from the bottom of the building in the resulting image.


The Burj Khalifa is, according to Wikipedia, 829.8m tall. In this image, the top experiences an apparent shift of over half that distance at 482.4m

If you go through historical imagery for the Burj Khalifa, or any city with sky scrapers, you will see that the degree of displacement in the above image due to the satellite not being directly overhead is not that unusual. For sky scrapers or other buildings this is typically left as is and as a user, it is simply a matter of making sure you make your measurements from ground level objects. For mountains and other geographic features, the imagery is orthorectified by moving the top of the mountains the appropriate amount to put it in the right place. For very steep mountains this results in the effect we can see below:


Some steep mountains in the Himalayas show a streaking effect where the slopes of the mountains away from the camera had to be stretched out to get everything in the right place.

The process of orthorectification depends on having an accurate model of the terrain. The accuracy of Google Earth’s terrain model varies from place to place. We also don’t know whether or not the same terrain model is used for orthorectifying the images. What is clear though is that the process is not perfect and some displacement does take place, especially in mountainous regions. Cycling through historical imagery usually shows some movement between images.

Whether caused by this or other alignment issues, a quick check of a location in Cape Town showed differences of up to 30m between historical images. We have not yet done the same test in other locations to see whether there are more extreme variations elsewhere.


We marked the location of a feature on various historical images to see how much the location varies.

So, when making measurements in Google Earth based on objects seen in satellite imagery, keep in mind that the imagery alignment may be off by a significant amount.

Filed Under: Site News Tagged With: measure

How Google Earth measures distances

October 14, 2015

In yesterday’s post we mentioned that Google Earth’s measurements did not match ours, which used the Haversine formula. So we decided to investigate a bit more.

The Haversine formula assumes the earth is a perfect sphere and in our case we assumed the radius to be 6,378,137m. The earth is actually closer to an oblate spheroid (a flattened sphere), with the equator bulging slightly relative to the poles. According to Wikipedia Google Earth uses the WGS84 datum as used by GPS, which uses an oblate spheroid that approximates the real shape of the earth. There is a formula known as Vincenty’s formula that can be used to calculate distances for the WGS84 datum. We found some JavaScript code to do this here. We have incorporated it into yesterday’s post, so you now have the option to use either the Haversine formula or Vincenty’s formula.

So, we used our updated code and again compared it with Google Earth’s measurements, and it still doesn’t quite match. Further investigation was needed. We discovered that Google Earth takes altitude into account when displaying the length of a path. When you draw a polygon in Google Earth, it is by default given an absolute altitude of 0. It is also set as ‘clamped to ground’ which means it is drawn on top of the ground surface or at sea level when over the oceans, but we found that whatever the local ground height, it gave the same distance measurements as an absolute altitude of 0. If you give the path an absolute altitude, you can raise or lower the path, and its measurement will change, getting longer as it gets higher. We discovered that to get a match between the results of Vincenty’s formula and Google Earth’s measurements, we had to set the path to an altitude of 80m. This worked at various latitudes. So does Google Earth have a slightly different sea level from the one used for WGS84 or are we missing something? We would love to hear from any of our readers with more expertise in this area.

If you wish to do some testing for yourself, you can download this test KML file, which has three lines at different latitudes, each of which covers exactly one degree of latitude.

For the above lines we got the following measurements in centimetres:

Google Earth at Altitude 0 Vincenty Haversine
11,057,299 11,057,439 11,131,950
11,085,952 11,086,093 11,131,950
11,141,932 11,142,073 11,131,950

As you can see, the discrepancies we are talking about are only on the 6th significant digit.

See here to learn various ways to measure in Google Earth, and here for some of the extra measurement features found in Google Earth Pro.

Filed Under: Site News Tagged With: measure

Numbering the points on a Path or Polygon with KML

October 13, 2015

We have recently been spending some time improving our JavaScript for combining polygons. In order to debug it, we found it useful to number the points for display in Google Earth. We thought that others may find the feature useful, and just for fun, we added the option to display the distances along the segments. Distance is calculated using the Haversine formula, which, is the same method we believe the Google Maps API uses for calculating distance. We compared our measurements with Google Earth’s measuring tool and they did not match, so it appears Google Earth uses a different formula, which is probably more accurate. Google Earth’s measuring tool is also capable of optionally taking altitude into account.

[ Update: We have added the option to use the Haversine formula for the distance measurements as it is more accurate.]

Polygons or Paths:

Colour for point labels:

Label Size:

Include distances:

Distance formula:

Distance units:

Colour for distance labels:

Filed Under: Site News Tagged With: KML, KML javascript utilities, measure

Measuring in Google Earth Pro

February 24, 2015

Last month Google removed the US$399 a year price tag from Google Earth Pro and released it for free. There is no longer any need to sign up for a licence key, simply login with your email address and the key GEPFREE. Recently, we have been having a look at some of the features unique to Google Earth Pro. Today we will have a look at the measuring tools in Google Earth Pro.

There are two ways to get measurements in Google Earth Pro. If you look at the properties of a path or polygon, there is a ‘measurements’ tab which displays length for paths or perimeter and area for polygons.

Area and perimeter of 3D around Faro
The area and perimeter of the newly released 3D along the southern coast of Portugal.

In addition, the ‘ruler’ tool has several tabs not present in the standard version of Google Earth. They allow you to measure the radius and area of circles, measure the length of 3D paths, and measure the area and perimeter of 3D polygons.

circle measurement
The Plaza de Toros de La Ribera in LogroƱo, Spain, has an area of nearly 10,000 square metres.

3D path
Using Google Earth Pro we could easily measure the height of the spires on Cologne Cathedral to be approximately 155m. Wikipedia says they are approximately 157m.

WTC 1
Measuring the approximate area of glass used on one of the facets of WTC 1 is easy.

Filed Under: Google Earth Tips Tagged With: google earth pro, google earth pro features, measure

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