Carrak Consulting has worked with Cornwall Consultants Ltd and Camborne School of Mines (University of Exeter) to secure and develop a collaborative research project, funded by Aerospace Cornwall. The project has investigated ways to use airborne LiDAR with Earth Observation signatures to map previously unknown mining subsidence hazards.

Metal mining was widespread across South West England for many centuries and has left a legacy of unrecorded hidden shafts and workings that present a risk of surface subsidence today. The assessment of mining related ground instability risks are a material planning consideration for new developments in Cornwall and a typical requirement by most mortgage lenders when properties change hands in former mining areas.

Desk top mining searches are a standard part of the planning and conveyancing processes and is one of the services offered by Cornwall Consultants Ltd. These reports involve the assessment of a huge number of historical maps and plans to define recorded mine workings and predict the likelihood of unrecorded shallow mine workings. This prediction relies heavily on manual extrapolation from these plans by experienced mining geologists.  In recent years, the digitisation of historical records for use in a GIS with modern datasets has transformed this service. It has also enabled new technologies to be applied to the interpretation of historical resources, to help reveal the location and state of mining features. Two such technologies are LiDAR and Earth Observation (EO) data.

LiDAR is an acronym for Light Detection and Ranging and is a remote sensing technique used to measure the shape of terrain by timing how long a laser pulse takes to reflect back from an object. The primary available LiDAR dataset of the region is from the Tellus South West project, with a resolution of approximately 1 point per meter and a vertical accuracy of 25cm. This data is freely available under Open Licence, but is of medium resolution and the filtering used is rather aggressive, making features under vegetation invisible from smoothing.

Raw LiDAR data in point cloud format has been processed by the University using novel interpolation techniques and less aggressive filtering in order to create higher quality Digital Terrain Models from the low resolution source. When combined with expert knowledge of the mine workings themselves, reprocessing the raw data affords the ability to adapt the technique to maximise exposure of otherwise obscured mining features. Multiple advanced visualisation reprocessing algorithms were tested on a target areas provided, where known and predicted mine workings are present but cannot be distinguished by EO data alone. The combination yielded very promising results and the use of LiDAR by Cornwall Consultants Ltd for mining subsidence risk assessments is on-going.