Characterisation of Massive Sulphide Deposits in the Iberian Pyrite Belt Based on the Integration of Digital Outcrops and Multi-Scale, Multi-Source Hyperspectral Data

Geological mapping in difficult-to-access terrain such as open pit mines often relies on remotely sensed data. Hyperspectral data yield valuable geological information, especially when spectral ranges of multiple sensors are used in conjunction. In this contribution we project a number of hyperspectral datasets of an open pit mine covering the visible to near-infrared (VNIR), short-wave infrared (SWIR), and long-wave infrared (LWIR) range from airborne, drone-borne and ground-based acquisitions into a photogrammetric point cloud. The resulting hyperspectral digital outcrop is then used as a basis for data integration in a 3D environment. To discriminate geologic materials in the pit we apply a Gaussian deconvolution to identify the position of diagnostic absorption features in the SWIR and LWIR, and then apply a support vector machine-based classification. Our results agree with known lithologic units and alteration patterns and can be used to guide exploration targeting and mine planning.