Simplified Physical Stability Assessment of Chilean Mine Waste Storage Facilities Using GIS and AI: Application in the Antofagasta Region
Chile’s mining industry, a global leader in copper production, faces challenges due to increasing volumes of mining waste, particularly Waste Rock Dumps (WRD) and Leaching Waste Dumps (LWD). The National Service of Geology and Mining (SERNAGEOMIN) requires assessment of the physical stabi...
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IEEE
2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10843715/ |
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| author | Gabriel Hermosilla Gabriel Villavicencio Giovanni Cocca-Guardia Vicente Aprigliano Manuel Silva Juan Carlos Quezada Pierre Breul Vinicius Minatogawa Jaime Morales |
| author_facet | Gabriel Hermosilla Gabriel Villavicencio Giovanni Cocca-Guardia Vicente Aprigliano Manuel Silva Juan Carlos Quezada Pierre Breul Vinicius Minatogawa Jaime Morales |
| author_sort | Gabriel Hermosilla |
| collection | DOAJ |
| description | Chile’s mining industry, a global leader in copper production, faces challenges due to increasing volumes of mining waste, particularly Waste Rock Dumps (WRD) and Leaching Waste Dumps (LWD). The National Service of Geology and Mining (SERNAGEOMIN) requires assessment of the physical stability (PS) of these facilities, but current methods are hindered by data scarcity and resource constraints. This study proposes a simplified evaluation methodology using first-order parameters from open-access data. By integrating Geographic Information Systems (GIS) and Artificial Intelligence (AI)—utilizing models like YOLOv11 and convolutional neural networks—we automate the detection and characterization of WRD and LWD from satellite imagery, extracting critical parameters for PS assessment. This approach reduces analysis time and minimizes human error. Validated in the Antofagasta Region, Chile’s primary mining area, we identified and evaluated 70 WRD and 54 LWD. The results demonstrate the effectiveness of prioritizing deposits based on potential risk, enhancing SERNAGEOMIN’s capacity for supervision. The successful application suggests scalability to other mining regions and adaptability to different facility types, including tailings storage facilities. This work offers a practical tool to improve safety and risk management in the mining industry, addressing critical challenges in PS evaluation under current regulatory constraints. |
| format | Article |
| id | doaj-art-29de8397e1574783ade36c8935e7805a |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-29de8397e1574783ade36c8935e7805a2025-01-25T00:02:44ZengIEEEIEEE Access2169-35362025-01-0113144531447010.1109/ACCESS.2025.353085610843715Simplified Physical Stability Assessment of Chilean Mine Waste Storage Facilities Using GIS and AI: Application in the Antofagasta RegionGabriel Hermosilla0https://orcid.org/0000-0002-0674-2254Gabriel Villavicencio1https://orcid.org/0000-0002-5342-0063Giovanni Cocca-Guardia2https://orcid.org/0009-0006-4962-0659Vicente Aprigliano3Manuel Silva4https://orcid.org/0009-0005-0900-4117Juan Carlos Quezada5https://orcid.org/0000-0001-6164-7949Pierre Breul6https://orcid.org/0000-0003-1231-3496Vinicius Minatogawa7https://orcid.org/0000-0002-7441-7242Jaime Morales8https://orcid.org/0000-0001-5722-7781Escuela de Ingeniería Eléctrica, Pontificia Universidad Católica de Valparaíso, Valparaíso, ChileEscuela de Ingeniería de Construcción y Transporte, Pontificia Universidad Católica de Valparaíso, Valparaíso, ChileEscuela de Ingeniería Eléctrica, Pontificia Universidad Católica de Valparaíso, Valparaíso, ChileEscuela de Ingeniería de Construcción y Transporte, Pontificia Universidad Católica de Valparaíso, Valparaíso, ChileEscuela de Ingeniería Eléctrica, Pontificia Universidad Católica de Valparaíso, Valparaíso, ChileICUBE, UMR 7357, CNRS, INSA de Strasbourg, Strasbourg, FranceDépartement Génie Civil, Polytech Clermont, Institut Pascal UMR CNRS 6602, Université Clermont Auvergne, CEDEX, Clermont Ferrand, FranceEscuela de Ingeniería de Construcción y Transporte, Pontificia Universidad Católica de Valparaíso, Valparaíso, ChileEscuela de Ingeniería Química, Pontificia Universidad Católica de Valparaíso, Valparaíso, ChileChile’s mining industry, a global leader in copper production, faces challenges due to increasing volumes of mining waste, particularly Waste Rock Dumps (WRD) and Leaching Waste Dumps (LWD). The National Service of Geology and Mining (SERNAGEOMIN) requires assessment of the physical stability (PS) of these facilities, but current methods are hindered by data scarcity and resource constraints. This study proposes a simplified evaluation methodology using first-order parameters from open-access data. By integrating Geographic Information Systems (GIS) and Artificial Intelligence (AI)—utilizing models like YOLOv11 and convolutional neural networks—we automate the detection and characterization of WRD and LWD from satellite imagery, extracting critical parameters for PS assessment. This approach reduces analysis time and minimizes human error. Validated in the Antofagasta Region, Chile’s primary mining area, we identified and evaluated 70 WRD and 54 LWD. The results demonstrate the effectiveness of prioritizing deposits based on potential risk, enhancing SERNAGEOMIN’s capacity for supervision. The successful application suggests scalability to other mining regions and adaptability to different facility types, including tailings storage facilities. This work offers a practical tool to improve safety and risk management in the mining industry, addressing critical challenges in PS evaluation under current regulatory constraints.https://ieeexplore.ieee.org/document/10843715/Artificial intelligenceclosure plangeographical information systemsmine waste storage facilitiesphysical stability assessmentSentinel-2 satellite imagery |
| spellingShingle | Gabriel Hermosilla Gabriel Villavicencio Giovanni Cocca-Guardia Vicente Aprigliano Manuel Silva Juan Carlos Quezada Pierre Breul Vinicius Minatogawa Jaime Morales Simplified Physical Stability Assessment of Chilean Mine Waste Storage Facilities Using GIS and AI: Application in the Antofagasta Region IEEE Access Artificial intelligence closure plan geographical information systems mine waste storage facilities physical stability assessment Sentinel-2 satellite imagery |
| title | Simplified Physical Stability Assessment of Chilean Mine Waste Storage Facilities Using GIS and AI: Application in the Antofagasta Region |
| title_full | Simplified Physical Stability Assessment of Chilean Mine Waste Storage Facilities Using GIS and AI: Application in the Antofagasta Region |
| title_fullStr | Simplified Physical Stability Assessment of Chilean Mine Waste Storage Facilities Using GIS and AI: Application in the Antofagasta Region |
| title_full_unstemmed | Simplified Physical Stability Assessment of Chilean Mine Waste Storage Facilities Using GIS and AI: Application in the Antofagasta Region |
| title_short | Simplified Physical Stability Assessment of Chilean Mine Waste Storage Facilities Using GIS and AI: Application in the Antofagasta Region |
| title_sort | simplified physical stability assessment of chilean mine waste storage facilities using gis and ai application in the antofagasta region |
| topic | Artificial intelligence closure plan geographical information systems mine waste storage facilities physical stability assessment Sentinel-2 satellite imagery |
| url | https://ieeexplore.ieee.org/document/10843715/ |
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