By Tim Sinnott, Interaction Designer / Senior Cartographer, GreenInfo Network
For the past couple of years, cartographers and developers at GreenInfo Network have been working closely with the Google Earth team to design and build data layers for users to explore in the Voyager feature. These layers take advantage of the global canvas available in Earth, allowing us to visualize timely, compelling, even beautiful datasets, and provide educational context to users who want to dive into scientific topics.
We’ve visualized Seafloor Age, Seafloor Depth, Sea Surface Temperature, and Global Volcanoes. In late 2018, we began to work on a layer showing tsunamis around the world over the past several centuries. This is one of the most complex data layers we’ve yet built for Google Earth, and you can explore it today. We’re thrilled with the results — even if they took a lot of trial and error to get right. Here’s how we tackled the creation of the tsunamis layer.
One of the most challenging aspects of tsunamis is that there are two very different aspects to each event:
- The cause: this is most often an earthquake but sometimes a landslide or even a human-caused event like an explosion. Causes of tsunamis are relatively easy to pinpoint and map, just like earthquakes.
- The impact: the dozens, hundreds, or even thousands of places where the wave energy of the tsunami hit a shoreline. These “run-up locations” can be very near the event or half a world away across the ocean. So the impacts are much harder to map and visualize. It’s almost like trying to map all the buildings that fall in an earthquake compared to just mapping the epicenter.
Without the cause, there’s no tsunami, but the run-up points are where we as humans experience tsunamis, so we had to map both. And ideally show how they are connected.
Their website provides two separate TXT files for download, one for tsunami source event locations and one for tsunami run-up locations. Event sources include locations of earthquake epicenters, landslides, meteorological events, explosions and astronomical tides.
Earthquakes represent 82% of the overall source events, so there’s a lot of overlap between an earthquake’s layer and a tsunami’s layer. Since we didn’t just want to publish an earthquake’s layer, we began looking for additional datasets to tell a more thorough and compelling story about the global impacts of tsunamis.
For all data layers in Google Earth, the team likes to highlight key locations within the dataset to help convey certain concepts or themes, and allow a user to go deeper. With tsunamis, for example, we identified 20 events from the historical tsunami database that represented different types of source events over a span of hundreds of years and at different locations around the globe. They also connected us with two oceanographers at the Pacific Tsunami Warning Center: Nathan Becker, Ph.D., and Dailin Wang, Ph.D. Nathan and Dailin provided us with the corresponding wave amplitude models as GIS data to build out our visualizations.
In addition to the wave models from NOAA, we compiled both event points and run-up points for the 20 events we’d be highlighting in the new layer.
Each event would be a single point. The run-up data (again, those are the locations of tsunami effects along the coastline) ranged from a few points to thousands of points per event. To help make the large number of points more meaningful, we scaled the points by the maximum run-up water height along the coast. In the final layer, the largest run-up points are located near the higher wave amplitude values in the underlying models.
So now we have a single event and thousands of impact locations. But how are the two datasets connected?
That’s where the wave amplitude grids from NOAA come into play.
While the event and run-up points could be easily converted to point KML files, the wave amplitude grids were a different story. These came to us as NetCDF files between 5mb and 60mb in size. We needed to symbolize these rasters in a way that users would quickly understand the wave height data, and then we had to cut these large global images into tiles to efficiently display in Google Earth.
To begin, we used QGIS to export two separate rendered GeoTIFFs, one that applied a color gradient to represent wave amplitude, and one grayscale shaded relief image based on the same model.
We used GIMP to combine the two images into one in which we made the medium grays of the shaded relief transparent, keeping the highlights and shadows. We made the entire shaded relief layer 50% translucent to make sure the shading was present but did not overpower the wave amplitude color gradient.
Areas of no amplitude data, including all land areas, were made fully transparent so the imagery of Google Earth would show through. We loaded each of the rendered images into TileMill to export as MBTiles, then used MBUtil to export to a directory of files. We uploaded each directory to a Google Cloud Storage bucket and built a KML to point to these stored tiles. At this point, each of the wave amplitude grids was ready to pull into our layer along with the event and run-up points.
Google Earth’s dark blue ocean gave us the opportunity to experiment with bright colors for the wave amplitude grids, to have them leap out of the screen and show the paths and heights of waves across open water.
The three tests below work great on a small 2D map where a viewer can see the full extent of the model in a single image. Overlaid on a 3D globe, the single-color or even three-color symbologies end up looking like amorphous blobs of color, and the small changes in data values remain invisible. After applying a nine-color gradient to each of the grids, those small changes become visible when wrapped around the globe, and it becomes easier for the viewer to connect wave amplitude heights with the white points showing water heights at the tsunami runup locations.
It is only by combining the three layers — the simplest one of origins, the more numerous run-up locations, and the complex wave grids — that we tell the full story of tsunamis.
Select any origin point and a story unfolds visually of a massive torrent of energy pulsing outward in complex patterns and colliding with shorelines nearby or around the world. We hope this tsunamis visualization we’ve developed helps Earth users — from those curious users interested in science to kids in the classroom learning about tsunamis for the first time — use this layer to learn more about these global phenomena.