Abstract
The transition towards a new sustainable energy model—replacing fossil fuels with renewable sources—presents a multidisciplinary challenge. One of the major decarbonization issues is the question of to optimize energy transport networks for renewable energy sources. Within the range of renewable energies, the location and evaluation of geothermal energy is associated with costly processes, such as drilling, which limit its use. Therefore, the present research is aimed at applying different geomatic techniques for the detection of geothermal resources. The workflow is based on free/open access geospatial data. More specifically, remote sensing information (Sentinel-2A and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)), geological information, distribution of gravimetric anomalies, and geographic information systems have been used to detect areas of shallow geothermal potential in the northwest of the province of Orense, Spain. Due to the variety of parameters involved, and the complexity of the classification, a random forest classifier was employed, since this algorithm works well with large sets of data and can be used with categorical and numerical data. The results obtained allowed identifying a susceptible area to be operated on with a geothermal potential of 80 W·m−1 or higher.
Highlights
Fossil fuels encompassed 81% of the total primary energy supply in 2016 [1]
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The Sentinel-2A images allowed the creation of a land cover map in a detailed spatial resolution and with zero cost
Summary
Fossil fuels (coal, petroleum, and natural gas) encompassed 81% of the total primary energy supply in 2016 [1]. These energy sources are characterized by their limited reserves and for producing greenhouse gases (GHG), which cause, as consequences, the increase of the average temperature and extreme changes in the climate, among others. Among the different types of geothermal energy: very low, low, high, and very high enthalpy, the present research is focused in low or very-low enthalpy types, known as shallow types [5] This energy is characterized by being partially renewable, having high availability, reducing GHG emissions [6], and producing less waste than other energy sources
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