With the recent advancement of technologies, geoscience data have been accumulated rapidly at different scales in the 21st century and industrial 4.0 era, which has substantially improved the innovation-driven development of geoscience. The methods based on multi-source (geological, geophysical, geochemical, and remote sensing sources) and multi-scale (regional, district, camp, and deposit scales) geoscience data, such as machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation, facilitate a revolutionary path and platform for mineral exploration and engineering geology.
This Research Topic aims to present and disseminate recent advances in various subjects addressing applications of the aforementioned methods in the fields of mineral exploration, engineering geology, geophysical exploration, geochemical exploration, remote sensing, mining industry, and other geosciences.
Schemes of interest for publication include, but are not limited to:
• Applications of machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation in mineral exploration and engineering geology
• Applications of machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation in geophysical studies
• Applications of machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation in geochemical studies
• Applications of machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation in remote sensing studies
• Applications of machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation in real-time mining
With the recent advancement of technologies, geoscience data have been accumulated rapidly at different scales in the 21st century and industrial 4.0 era, which has substantially improved the innovation-driven development of geoscience. The methods based on multi-source (geological, geophysical, geochemical, and remote sensing sources) and multi-scale (regional, district, camp, and deposit scales) geoscience data, such as machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation, facilitate a revolutionary path and platform for mineral exploration and engineering geology.
This Research Topic aims to present and disseminate recent advances in various subjects addressing applications of the aforementioned methods in the fields of mineral exploration, engineering geology, geophysical exploration, geochemical exploration, remote sensing, mining industry, and other geosciences.
Schemes of interest for publication include, but are not limited to:
• Applications of machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation in mineral exploration and engineering geology
• Applications of machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation in geophysical studies
• Applications of machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation in geochemical studies
• Applications of machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation in remote sensing studies
• Applications of machine (deep) learning, geostatistics, 3D geological modeling, and 4D numerical simulation in real-time mining
