Agile lithology identification can assist mining by providing important information in the exploration and production of mineral resources.This study proposes a new lithology recognition procedure using video-logging ...Agile lithology identification can assist mining by providing important information in the exploration and production of mineral resources.This study proposes a new lithology recognition procedure using video-logging of boreholes with an endoscope,applied to six production blocks in a limestone quarry.Images are automatically extracted from the videos and the lithology is classified into three classes based on clay content,i.e.massive limestone,brecciated limestone,and high amount of clay.The image quality is evaluated with a gray pixel intensity threshold and three no-reference image quality metrics,i.e.perception-based image quality evaluator,natural image quality evaluator,and blind/referenceless image spatial quality evaluator.After removing low-quality images,7583 images are retained and used for developing lithology classification models using six optimized classification techniques.The contrast-limited adaptive histogram equalization(CLAHE)technique is used to improve image quality.Ten color characteristics involving three percentiles of red,green and blue pixel intensities,together with color counting and five texture characteristics-correlation,entropy,homogeneity,contrast and energy-are used as inputs.Bayesian optimized light gradient boosting machine model performs best,with an overall accuracy of 88.04%,and a precision on the classes of massive limestone,brecciated limestone and high amount of clay of 90.72%,83.52%and 85.29%,respectively,for the testing set.The feature importance scores show that the color counting is the most significant parameter for the development of the classification model.Compared with previous image-based methodologies,this study provides a more flexible and cheaper procedure to identify lithology.展开更多
The exploitation of quarries represents a strategic component of Morocco’s construction-materials sector,especially amid rapid urbanization and infrastructure expansion.To ensure that extractive activities remain env...The exploitation of quarries represents a strategic component of Morocco’s construction-materials sector,especially amid rapid urbanization and infrastructure expansion.To ensure that extractive activities remain environmentally sustainable and compliant with national regulations,this study applies a spatial suitability analysis based on Geographic Information Systems(GIS)and Multi-Criteria Decision Analysis(MCDA)within the ArcGIS Pro environment.The methodology integrates six key criteria:lithology,slope gradient,hydrographic buffers,land-use/land-cover patterns,accessibility to transport networks,and exclusion of urbanized or ecologically sensitive zones.Each parameter was weighted using the Analytical Hierarchy Process(AHP)to generate a composite suitability map for quarry site selection in north-western Morocco.The resulting classification shows that 18%of the total area is highly suitable,34%moderately suitable,and 48%unsuitable for sustainable quarrying.Priority zones occur mainly within carbonate formations in the Tangier–Assilah Province and,to a lesser extent,within Numidian flysch units in the Fahs-Anjra Province.These findings demonstrate that GIS–MCDA methods offer a robust and transparent framework for optimizing quarry site selection,reducing ecological risk,and improving decision-making for land-use planning and resource management in Morocco’s extractive sector.展开更多
基金the DigiEcoQuarry project,funded by the European Union's Horizon 2020 research and innovation program under Grant Agreement No.101003750supported by the China Scholarship Council(Grant No.202006370006).
文摘Agile lithology identification can assist mining by providing important information in the exploration and production of mineral resources.This study proposes a new lithology recognition procedure using video-logging of boreholes with an endoscope,applied to six production blocks in a limestone quarry.Images are automatically extracted from the videos and the lithology is classified into three classes based on clay content,i.e.massive limestone,brecciated limestone,and high amount of clay.The image quality is evaluated with a gray pixel intensity threshold and three no-reference image quality metrics,i.e.perception-based image quality evaluator,natural image quality evaluator,and blind/referenceless image spatial quality evaluator.After removing low-quality images,7583 images are retained and used for developing lithology classification models using six optimized classification techniques.The contrast-limited adaptive histogram equalization(CLAHE)technique is used to improve image quality.Ten color characteristics involving three percentiles of red,green and blue pixel intensities,together with color counting and five texture characteristics-correlation,entropy,homogeneity,contrast and energy-are used as inputs.Bayesian optimized light gradient boosting machine model performs best,with an overall accuracy of 88.04%,and a precision on the classes of massive limestone,brecciated limestone and high amount of clay of 90.72%,83.52%and 85.29%,respectively,for the testing set.The feature importance scores show that the color counting is the most significant parameter for the development of the classification model.Compared with previous image-based methodologies,this study provides a more flexible and cheaper procedure to identify lithology.
文摘The exploitation of quarries represents a strategic component of Morocco’s construction-materials sector,especially amid rapid urbanization and infrastructure expansion.To ensure that extractive activities remain environmentally sustainable and compliant with national regulations,this study applies a spatial suitability analysis based on Geographic Information Systems(GIS)and Multi-Criteria Decision Analysis(MCDA)within the ArcGIS Pro environment.The methodology integrates six key criteria:lithology,slope gradient,hydrographic buffers,land-use/land-cover patterns,accessibility to transport networks,and exclusion of urbanized or ecologically sensitive zones.Each parameter was weighted using the Analytical Hierarchy Process(AHP)to generate a composite suitability map for quarry site selection in north-western Morocco.The resulting classification shows that 18%of the total area is highly suitable,34%moderately suitable,and 48%unsuitable for sustainable quarrying.Priority zones occur mainly within carbonate formations in the Tangier–Assilah Province and,to a lesser extent,within Numidian flysch units in the Fahs-Anjra Province.These findings demonstrate that GIS–MCDA methods offer a robust and transparent framework for optimizing quarry site selection,reducing ecological risk,and improving decision-making for land-use planning and resource management in Morocco’s extractive sector.
