animation

Moving sand in Landsat animations

December 7, 2016

Last week Google added global mosaics in historical imagery for each year going back to 1985. The mosaics are created from mostly Landsat imagery with a bit of Sentinel 2 imagery for the last couple of years (the Sentinel 2 satellite is new). The mosaics are created by gathering all the Landsat/Sentinel 2 imagery for a given year and looking for cloud-free and snow-free pixels then combining the images to create a single global mosaic for the year. Although it is fantastic for viewing long term change, the overall result is that we actually miss out on short term changes.

Back in July we wrote a post about watching sand dunes move with Google Earth imagery. Today we are looking at a similar concept, but with Landsat imagery instead. In August we created a KML file that automatically creates animations using Landsat imagery with thumbnails from Amazon Web Services. We used that tool to create the two GIF animations below:

Sand blowing in the Sahara (southern Libya). Explore original animation.

Sand blowing and irrigation circles in Oman. Note especially south west of the centre of the animation there are wisps of sand moving north west. Explore original animation.

What we found interesting is that established dunes hardly move at all over the three years covered by the animations, but loose sand can clearly be seen moving. It looks no different than sand being blown on the beach. Yet the scales involved in the animations are tens of kilometres and a three year period.

You will also notice in the second animation the dunes to the north east appear to pulse sharper, then softer again. This is because the angle of the sun affects the shadows during the course of the year.

Animating in Google Earth Part 2 – Importing Models

November 7, 2016

This is the second in a series of posts discussing animating in Google Earth that we started last week. Today we are not looking at animation itself, but how to get a model into Google Earth that you can animate.

3D models can be obtained from a variety of sources. One resource is the SketchUp 3D Warehouse, which has a large number of models, including most of the old style 3D buildings found in the Google Earth 3D buildings layer. When downloading them, they are offered in a variety of formats, sometimes including KMZ ready for Google Earth. If that is not available try ‘Collada file’ if is available. If the only option is SketchUp file format then you will need to the free version of SketchUp to convert it to a Collada file.

There are many other sites with 3D models available such as this one. Where possible you should look for files in Collada format ( .dae file extension). Other formats can be converted but you will need to find the appropriate software first.

We found this 3D model, created by NASA, of the Mars rover Curiosity.

It is in a format used by the open source 3D modelling program Blender. So we installed Blender, opened the model then exported it to Collada format. Unfortunately, it would not immediately open correctly in Google Earth, as Google Earth’s Collada support is somewhat limited. From the KML documentation:

Google Earth supports the COLLADA common profile, with the following exceptions:
* Google Earth supports only triangles and lines as primitive types. The maximum number of triangles allowed is 21845.
* Google Earth does not support animation or skinning.
* Google Earth does not support external geometry references.

The key here is the lack of support of a feature in the Collada format called a polylist. Luckily, in many cases it is simply a matter of editing the Collada file in a text editor and replacing all instances of the word ‘polylist’ with ‘triangles’ (it is also necessary to make sure ‘triangulate’ is ticked in the export options in Blender).

We were then able to simply drag and drop it into Google Earth.

As you can see below, however, it has some purple cubes labelled ‘Don’t render’ from Blender that we don’t want.

We will have to analyse the Collada file and see if we can remove them.

Another problem we encountered is that Google Earth does not automatically zoom in on the model, and if it is very small relative to your view, when you drag the model into Google Earth it can be difficult to find the model.

Animating in Google Earth

November 4, 2016

This is the first in a series of posts on animating in Google Earth. It is generally well known that Google Earth can display 3D models provided in KML files. Less well known is that it is possible to do basic animation in Google Earth. We have looked at a number of amazing Google Earth animations over the years, but relative to the other content for Google Earth, animations are extremely rare. There are a number of reasons for this, including a lack of good information regarding how to create these animations and easy to use tooling.

Today we are exploring the three main types of animation and their pros and cons.

In general, none of the animation methods are trivial, and almost all require some programming knowledge or custom tools to achieve a reasonable animation. Google does not provide any tools for creating animations but they do provide basic documentation for each mechanism.

Tours

Google Earth tours provide a mechanism for animating models. The animations are defined within the KML as documented here. Although KML can be typed out by hand this is completely impractical and it is necessary to have a tool that generates the KML as required.

Pros
– The person creating the tour has near complete control over what the user sees. This can be useful as it is quite easy to loose track of a moving model in Google Earth.
– Smooth animations along a line or constant rotation are handled automatically and need a lot less lines of KML than the time-based method.

Cons
– The complete control by the tour creator comes at the cost of practically no control by the user. The tour can be paused so the user can look around, but the user cannot change the view much while the tour is playing so live animations cannot be fully explored.

When to use
This is best used for models that move over a long distance that the viewer would easily lose track of. It is also ideal when you want to include other information that is best suited to being presented in a tour.

Examples
Steven Ho’s Maokong Gondola of Taipei

To see it in Google Earth, download the KML from Steven’s blog.

Captain James Cook’s exploration of Australia by Colin Hazlehurst. (not working, but you can see them on YouTube).

Time-based animations

This uses the Google Earth time toolbar in conjunction with time stamps in a KML file. The relevant KML documentation can be found here.

Pros
– This technique does not take control of the user’s view point so they are free to move around and look at the animation from different angles.

Cons
– It does not have a smooth animation feature, so smooth animations require a lot of frames, which results in very large KML files for long animations.
– The time toolbar can be confusing and users may not even realise that they must use it to view the animation. In addition, the speed of the animation is set by the user, and achieving a specific speed is difficult.

When to use
This is best suited to short, repeating animations.

Examples
The London Eye animation by Barnabu.
Turn off the Google Earth 3D buildings layer for best results.

This technique is also used for animations that do not involve models, such as the USGS animated KMLs showing earthquakes over time.

Google Earth API

This uses the Google Earth plugin. Animations can be directly controlled via JavaScript in real time.

Pros
This provides the greatest level of control and allows very complex animations.

Cons
The Google Earth API has been deprecated and could be shut down at any time. In addition, it is only supported in a few browsers (Firefox for example).

Examples
The Monster Milktruck consists of a driving simulator in Google Earth.

‘Stabilizing’ our Landsat imagery animations

August 30, 2016

We have recently been doing a series of posts about Sentinel and Landsat imagery on Amazon Web Services (AWS), including releasing a KML file that automatically retrieves thumbnails of Landsat 8 imagery from AWS and creates animations with them.

We mentioned at the time that the Landsat images are not all perfectly aligned with each other and we had adjusted each image slightly to try and create smoother animations. To do this we used a simplified model that assumed that the imagery squares were all aligned with latitude and longitude, with up being North. It turns out that our assumptions were not valid and there was still significant ‘shake’ visible in ground features in many animations, especially those of Antarctica.

After some investigation we discovered that not only do the Landsat tiles tilt to the right as per the satellite’s orbit, but the images are placed into the thumbnails at an angle, results in further rotations overall.

The imagery on AWS is provided with a file whose name ends with MTL that contains a variety of metadata for the image. This includes the coordinates of the corners of the thumbnails (this is the whole thumbnail including the black areas). If we have two thumbnails offset from each other as shown as the red and green squares in the image below left, then in our animation we need to adjust the top of one of the images by the amount shown as the ‘top offset’. Thinking of it as purely Cartesian coordinates, to work it out in latitude and longitude it involves a series of rotations and translations, which gets rather complicated. However, we realised that instead, we could stick to proper geographic calculations, for which we already have the key routines that we worked out when working on our post on drawing circles in Google Earth. It mostly relies on an open source package called GeographicLib by Charles Karney, with a few additions also by him but not included in the main library.

Above right we see the mid-point (red circle) of the top of the red square, the mid-point (green circle) of the top of the green square, and what is known as the ‘cross track intercept’ for the green point to the thin red line. The cross track intercept is the closest point on a great circle to a location not on the circle. The distance we were looking for is from the red circle to the cross track intercept. Although this all sounds complicated, it is actually only a few lines of code, because all the hard work is done by GeographicLib. We simply repeated this for all for sides and for every frame in the animation and it worked! The animations are now much more stable even over Antarctica.

Our conclusion overall, is that although geographic coordinates can be very complicated, sometimes it is actually easier to work with them than trying to simplify things, as the heavy lifting can be done by ready-made libraries of code.

Because the thumbnails are actually higher resolution than what you can see in the popup, we have also added the ability to zoom and pan the animation. Just use the mouse scroll wheel to zoom in and out and drag the image with the mouse to pan. I am afraid we don’t have a Mac to test on, so we are not sure if this works on Mac. Let us know in the comments if it doesn’t and we will try adding keyboard controls. Remember, these are only thumbnails so don’t expect great resolution when zoomed in.

You can download the updated KML file here. We have widened the size of the popup in the standard version, but if you find it too wide for your screen, then the narrower version can be found here.

Animating Sentinel-2 imagery in Google Earth

August 26, 2016

We have recently been doing a series of posts about Sentinel and Landsat imagery on Amazon Web Services (AWS). We created tools to let you quickly preview the latest Sentinel and Landsat imagery in Google Earth. We also looked at the coverage pattern for the Sentinel and Landsat imagery and created a way to animate the Landsat imagery. Today we are releasing similar animations for the Sentinel imagery.

To see the animations, simply download this KML file, open it in Google Earth and click on any tile.

There are several differences between this one and the Landsat animations. The sentinel thumbnails are much lower resolution than the Landsat thumbnails, so we don’t provide a link to a larger version. Also, the sentinel images often do not cover the complete tile, so we have provided an extra slider to allow you to filter out tiles based on how much of the tile they cover.

The KML file also shows with colour coding how much sentinel imagery there is, with a range from green to red for 1 to 120 images per tile and white for tiles that have over 120 images. The highest numbers can be found over Europe, which is understandable given that it is a European satellite. The amount of imagery also increases towards the north of Europe, we believe this is because the paths the satellite takes overlap more near the poles, allowing more imagery to be captured. There are also hotspots over deserts suggesting that the images are selected for low cloud cover.

The Sentinel-2A satellite that is gathering the imagery was launched in June 2015. In comparison, Landsat 8 has been around since 2013. However, the Sentinel-2A satellite covers the globe roughly every 10 days, whereas Landsat 8 takes 16 days. In addition, the Landsat 8 archive on AWS only includes selected images from 2013 and 2014 (with significantly more of the US than other parts of the world) and only has the complete set of images from 2015 onwards.

We also find the clouds look whiter and obstruct the picture more in the Sentinel imagery than they do in the Landsat imagery. This may relate to how the imagery was processed for the thumbnail or it could reflect differences in the exact wavelengths the respective satellites use to capture the colour bands.

We came across a few errors in the data, such as mislabelled tiles or missing thumbnails, but they were not significant enough to seriously affect the operation of the animations.

As with the Landsat imagery, it is important to note that this is very low resolution imagery, so expect to only see very large scale phenomena. Also, with only a year’s worth of data there is not a lot of change to see. However, it is a continuously updated service and with the expected launch of Sentinel-2B sometime next year doubling the frequency of imagery, we can expect some spectacular animations in years to come.