Availability of large-scale geospatial datasets, developments of effective algorithms, and access to powerful computing resources have resulted in the unprecedented quantities of data generated in recent years. This vast volume of available Earth observation data has triggered the need to find new ways to exploit its full potential. The GOLDENAI platform was developed to maximise geospatial data potential specifically for mineral exploration and mining. The platform's innovative component-based architecture consists of a back end for data acquisition, processing, and AI-driven analysis, and a user-friendly front-end for interactive data exploration. Uniquely tailored for the mining sector, the platform integrates automated Artificial Intelligence Knowledge Packs (AIKPs) to streamline processes such as soil moisture time-series analysis, Principal Component Analysis (PCA) for mineral mapping, spectral indices, RGB composites, and unsupervised clustering for geospatial analysis. Throughout the lifecycle of the GoldenEye project and through real-world field trials in the Golden Eye project, we demonstrate how GOLDENAI significantly enhances processing efficiency. This robust and scalable platform, accessible via a web-based interface, simplifies complex data workflows, making it a comprehensive and valuable tool for industry and academic stakeholders in mineral resource management.
Building similarity graph...
Analyzing shared references across papers
Loading...
Barbara Štimac Tumara
Taras Matselyukh
Francisco Gutierres
Geological Society London Special Publications
Environmental Systems Research Institute (United States)
GGZ Noord-Holland-Noord
Building similarity graph...
Analyzing shared references across papers
Loading...
Tumara et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69f154c0879cb923c4944eff — DOI: https://doi.org/10.1144/gslspecpub2024-91