Spoil characterisation using UAV-based optical remote sensing in coal mine dumps
Sureka Thiruchittampalam1
Sarvesh Kumar Singh1
Bikram Pratap Banerjee2
Nancy F.Glenn3
Simit Raval1
1.School of Minerals and Energy Resources Engineering,University of New South Wales,Sydney,NSW 2052,Australia2.Agriculture Victoria,Grains Innovation Park,110 Natimuk Road,Horsham,VIC 3400,Australia3.Department of Geosciences,Boise State University,Boise,ID,USA
摘要：The structural integrity of mine dumps is crucial for mining operations to avoid adverse impacts on the triple bottom-line.Routine temporal assessments of coal mine dumps are a compliant requirement to ensure design reconciliation as spoil off-loading continues over time.Generally,the conventional in-situ coal spoil characterisation is inefficient,laborious,hazardous,and prone to experts'observation biases.To this end,this study explores a novel approach to develop automated coal spoil characterisation using unmanned aerial vehicle(UAV)based optical remote sensing.The textural and spectral properties of the high-resolution UAV images were utilised to derive lithology and geotechnical parameters(i.e.,fabric structure and relative density/consistency)in the proposed workflow.The raw images were converted to an orthomosaic using structure from motion aided processing.Then,structural descriptors were computed per pixel to enhance feature modalities of the spoil materials.Finally,machine learning algorithms were employed with ground truth from experts as training and testing data to characterise spoil rapidly with minimal human intervention.The characterisation accuracies achieved from the proposed approach manifest a digital solution to address the limitations in the conventional characterisation approach.
机标关键词：dumpssatirisaisatminetioncharactercoal
论文发表日期：2023-10-28
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：15( 72-86 )
英文信息