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ZENODO
Article . 2020
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2020
License: CC BY
Data sources: Datacite
ZENODO
Article . 2020
License: CC BY
Data sources: Datacite
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LEVERAGING MULTISPECTRAL DRONE IMAGING TECHNOLOGIES FOR MONITORING OPEN-PIT MINES AND IMPROVING PRODUCTION EFFICIENCY

Authors: Lukman A. Alabede, Samuel Mohammed Maimak, Joel Mintah Opoku;

LEVERAGING MULTISPECTRAL DRONE IMAGING TECHNOLOGIES FOR MONITORING OPEN-PIT MINES AND IMPROVING PRODUCTION EFFICIENCY

Abstract

Multispectral drone imaging has emerged as a transformative tool in modern open-pit mining, offering a powerfulmeans of capturing high-resolution spatial, spectral, and environmental data at unprecedented scales andfrequencies. At a broad level, the technology enables mining operations to transition from periodic manual surveysto continuous, data-rich monitoring, creating a foundation for more predictive, automated, and efficient resourcemanagement. By capturing reflectance values across visible and near-infrared bands, multispectral sensors providedetailed insights into surface composition, moisture distribution, vegetation stress, and material differentiationinformation that conventional optical imaging alone cannot deliver. This broader analytical capability supportsenvironmental compliance, land-rehabilitation planning, and early detection of geotechnical risks such as slopeweakening or excessive water accumulation. Narrowing to direct production outcomes, multispectral droneimaging strengthens operational efficiency through precise monitoring of haul roads, ore stockpiles, pit-floorconditions, and blast impact zones. The spectral data allows operators to distinguish ore from waste with higheraccuracy, optimize dig-line placement, and reduce misclassification errors that drive unnecessary hauling andprocessing costs. Moisture and thermal variations captured through multispectral signatures can reveal unstableareas and inform scheduling decisions for excavation, machinery deployment, and haul-road maintenance.Integrating multispectral datasets with mine-planning software, digital twins, and automated dispatch systemsfurther enhances production efficiency. Machine-learning models trained on spectral patterns can predict orequality, fragmentation outcomes, and equipment performance impacts long before problems occur. Ultimately,multispectral drone imaging provides a scalable, non-intrusive monitoring framework that enhances situationalawareness, improves operational precision, and enables mining enterprises to make smarter, data-driven decisionsthat boost productivity while reducing risks and operational costs.

Keywords

Multispectral scanner, Drones

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green