The expected outputs of the DroneSOM project are a combination of drone services and software products that are suitable for geophysical measurements and data interpretation for commercial use making.

A drone geophysical service for gravity field mapping
Ideal for mineral exploration but can be useful in numerous other applications such as oil and gas exploration, geodetic surveys, and environmental monitoring and climate studies. The technology is based on a presently developed system for airborne gravity in close cooperation with German navigation company iMAR Gmbh, and drone service company UAVE, UK.

A drone electromagnetic geophysical service
Ideal for mineral exploration targeting 100-500 meters depth penetration. Service will be based on a ready-to-market drone electromagnetic measurement system with superior resolution due to the use of a stationary loop on the ground as a transmitter.

SOM cluster map of the Ezgebirge area based on input data from stream sediment geochemistry, aeromagnetics and aero gamma spectrometry. Image source: Beak Consultants GmbH.

“GisSOM” software for integrating information from geospatial data
A market-ready software product focusing on mineral exploration. After further adaption it can also be useful in numerous other types of geoscientific applications like environmental monitoring.

Advangeo® 3D Prediction software
A market-ready software product for 3D integration of 3D geophysical data volumes or 3D geophysical models. Targeted for mineral exploration but also useful in more general geological data integration problems and application fields of the 3D potential modelling like geo risk analyses, hydrogeological or geothermal analyses.

3D geophysical inversion software
An adapted and tested software solution for generating 3D models from processed drone geophysical data. Includes 3D density models from drone gravity data, 3D electrical conductivity models from drone EM data, 3D magnetic models from drone geomagnetic data. Suited to the pitfalls and particular issues caused by these types of data sets.