Abstract
The depletion of natural resources implies the need for a constant search for new reserves to satisfy demand. In the mining sector, Unmanned Aerial Vehicles (UAVs) have revolutionised geo-information capture and modelling to allow the use of low-cost sensors for prospecting and exploration for potentially exploitable resources. A very powerful alternative for managing the huge volume of data is the Geographic Information System (GIS), which allows storage, visualisation, analysis, processing and map creation. The research in this paper validates a new quasi-automatic identification of mining resources using GIS thermal-image analysis obtained from UAVs and low-cost sensors. It was tested in a case that differentiated limestone from dolostone with varying iron content, and different thermal behaviour from solar radiation, thereby ensuring that the thermal image recorded these differences. The objective is to discriminate differences in an image in a quasi-automatic way using GIS tools and ultimately to determine outcrops that could contain mineralisation. The comparison between the proposed method with traditional precision alternatives offered differences of only 4.57%, a very small deviation at this early stage of exploration. Hence, it can be considered very suitable.
Highlights
Globalisation and social development imply increased consumption and demand for mineral resources [1], which are finite
Mineral prospecting is a fundamental stage in the search for new resources to satisfy a growing demand, and for this the emergence of Unmanned Aerial Vehicles (UAVs) platforms and low-cost thermal sensors has brought great advantages
The new method proposed for the identification of different lithologies can be considered as an example of these potential contributions because it represents, in the first instance, a simple, economical and fast alternative for their delimitation
Summary
Globalisation and social development imply increased consumption and demand for mineral resources [1], which are finite. Prospecting is classified into two different typologies: indirect and direct. The former is based on the study of properties inferred through geochemical and geophysical methods. Indirect prospecting entails the application of geophysical methods based on specialised sensor measurements of physical anomalies associated with materials that generates a sufficiently strong identifying signal [3]. These activities involve the generation of physical models of the terrain and its behaviour according to various stimuli, but allowing for the identification of surface anomalies associated with possible mineral deposits. Geophysics, plays a fundamental role in the location and exploration of mineral resources [5] and can be divided into ground-based and airborne, the latter of which reduces the time required to scan large surface areas
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