Case Studies

This is only a small selection of the countless applications of ground penetrating radar





Show-mine Leogang

The show mine Leogang is located in the Schwarzleo valley and was once part of a major mining area in the Austrian Alps. Due to its great diversity in minerals the area was already known in the bronze age. From 1400 on, mining was operated over 500 years in four different mining areas (Nöckelberh, Inschlagalpe, Vogelhalte and Schwarzleo).

The oldest part of the mining area is Schwarzleo. Between 1400 and 1833 ores containing silver, copper, mercury, nickel, cobalt, and lead were mined. Several tunnels were dug into the rock, creating an underground network of about 20 kilometres. Today, the Barbara tunnel and the Daniel tunnel are accessible as show mine today. The size of further tunnels as the Erasmusstollen or Johannisstolllen, can only be estimated from historical maps, as parts of the tunnels and galleries are collapsed. Further, some gallery entrances are buried and therefore, a large part of the mining area is not accessible anymore. 

Mining buildings in the Schwarzleo valley are also not preserved and are mainly known from historical maps only. Vegetation, maintenance of roads and agricultural activities additionally hamper the localization of historical buildings and mines. 

The “Knappschaft Leogang” is interested in the preservation and investigation of the cultural heritage. Therefore, cavity exploration was carried out using a ground-penetrating radar to localise foundations of historical buildings, tunnel entrances and cavities. As non-invasive geophysical method, the ground-penetrating radar works without leaving traces in the nature. 

The GPR or ground-penetrating radar method uses high-frequency electromagnetic waves, which are emitted into the subsurface and reflected at boundary layers or cavities. Depending on the geological conditions, this enables to build a high-resolution image of the shallow subsoil in two-dimensional sections or as a three-dimensional model. Since electromagnetic waves are strongly absorbed, the penetration depth is limited to a maximum of 5-10 m.

Various questions were successfully answered in the area of the Leogang show mine. Among other things, the foundations of former mine buildings and broken tunnel entrances were located. Measurements were also carried out in the mine gallery, which indicate possible cavities under the existing tunnels. 



GPR indoor

With GPR measurements it was possible to locate thickness of concrete, screet, reinforcements and underfloor heating in great detail 


Utility Detection Part II

Again looking for a line! This time found: gas, water and sewer under the asphalt surface.

Would be interesting to compare that with the official plans ... surprises not excluded!

There I stand looking at my English lawn not knowing where the water lines are

After some time I knew where they where, and I even could show them in AR. Apart from the expected green water pipe and red electricity cable I found even another unknown pipe...


Water pipe detection on private property

For a long time I was wondering where pipes go under the lawn of my garden. I knew that at the time of construction the excavators laid out the pipe somewhere in the area shown on the left... but where I could not say. 

This changed after two hours of GPR measurements and interpretation.  Now I know exactly where my pipes are in case I have to do excavation again (for whatever reason) or the water pipe is broken.

Apart from that it is really cool to see the pipes under my garden in augmented reality! 

I guess I have to dig to see what the blue thing is... might be another power line


Asphalt Quality/Thickness
Base Gravel Fill

A few days ago I took out my GPR to see what's going on beneath my driveway.  The quality of the resulting data was quite good especially in the shallow section. So I decided to acquire a dense grid of GPR data and to test a few seismic interpretation methods on the data.

So after importing the data I applied some basic processing to highlight things I wanted to interpret.

Then with the dense grid of a pseudo 3D measurement I could interpret the two features I was interested in.


First data showed good resolution in the very first centimeters of asphalt and a prominent boundary which can only be the base of the gravel fill used as road foundation

Data imported into seismic interpretation system and applied some basic processing

Dense pseudo 3D data

Two horizons picked on GPR data

Displaying the asphalt thickness map in augmented reality shows where the asphalt quality is better (green is thicker asphalt, blue is thinner).

Extracted amplitudes on interpreted base asphalt and base gravel