Virtual Hiking in Open Data

I was recently hiking in the Northern Finland and Norway. When standing at the Gorsa Bridge in the Kåfjorddalen valley of the Northern Norway, I was mindblown by the mountaineous landscape and the 150 meter waterfall!

After the trip I begun to wonder how that kind of an experience could be stored, or saved in a more tangible way than just in photographs. Of course, the sensation of the actual presence of the terrain is still unsaveable, but you can get quite close with something in 3D – at least in terms of memory refreshment.

Up-to-date satellite imagery provides a birds-eye view of any location, and is freely available in 10 meter resolution. The European Space Agency has now two orbiting high resolution land observation satellites, Sentinel 2A and Sentinel 2B, which constantly produce free and open data downloadable by anyone from the SciHub platform. The data is designed for scientific purposes, so it will need some processing until you get an image out. For Finland, you can get pre-processed imagery from the Finnish Environment Institute (I work there).

To replicate, or “replicate”, the experience of standing at the Gorsa Bridge, satellite imagery provides only a birds-eye view into the Kåfjorddalen valley. It’s good, but we can get more than just the static images. Fortunately, also the digital terrain model (i.e. the elevation from the sea level) is freely available for large parts of the globe (ArcticDEM). Using the digital terrain model, or DEM, one can build a 3D-model from any place in just a few mouse clicks using QuantumGIS and the qgis2three-plugin. The plugin generates a web-ready package, so you can even “hike” through these 3D-models in your modern WebGL-enabled web-browser.

Here is the Kåfjorddalen valley modelled by the Sentinel 2 image (2017-09-07) and the digital elevation model (click the image):

And here is another model from the Kilpisjärvi, showing the Saana and Halti mountains, and the Arctic Trail as the white line (click the image to open the web-app):

(The models contain elevation data from the ArcticDEM, and satellite imagery from ESA Copernicus Sentinel 2 -satellite.)

Relying on these simple open source tools (QGIS+plugin) limits the size and resolution of the model, so you can’t get much larger models than these. But it’s easy to regenerate them with fresh satellite imagery. To push the limits further, one could use the open and free game development platforms, e.g. Unreal Engine. UE provides a well-made and flexible terrain generator, which supports on-demand loading of the terrain model and textures, allowing to split the model in pieces for faster and lighter loading to scale the model practically with no size limits. Wouldn’t it be cool to have an up-to-date hiking simulator for the whole globe? (Well, Google has already done that in a way…)

Algae blooms from satellite imagery (Landsat 8)

I’ve been lately tinkering with Libra, a free service to browse and download satellite imagery from Landsat 8 satellite.

This is an image from Landsat 8 satellite (2014-07-23) showing massive algal blooms at Archipelago Sea.

landsat_2014_07_23_web

You really should check this huge high resolution image to get a sense of scale.

Those tiny dots are large ships cutting through the algae mush:

landsat_closeup_1

Mining open source GIS data for Urban Snowboarding locations

Now something different.

Off-piste snowboarding in urban or rural areas is a time-consuming hobby especially outside the mountain areas, because the best spots are neither marked nor listed in city maps. A lazy snowboarder wants to find a nice, open hillside with decent slope and sparse treeline, but finding even a few spots requires numerous trips to countless would-be locations. But hey, we have open source GIS tools and Open Data to mine for just that!

So I opened up Quantum GIS and the Raster Calculator.

Continue reading Mining open source GIS data for Urban Snowboarding locations