Towards multiscale and multisource remote sensing mineral exploration using rpas: A case study in the lofdal carbonatite-hosted ree deposit, Namibia

Simple item page
dc.article.end-page28
dc.article.start-page1
dc.contributor.authorBooysen, René
dc.contributor.authorNex, Paul A.M.
dc.contributor.authorZimmermann, Robert
dc.contributor.authorLorenz, Sandra
dc.contributor.authorGloaguen, Richard
dc.contributor.authorAndreani, Louis
dc.contributor.authorMöckel, Robert
dc.date.accessioned2024-04-30T18:49:55Z
dc.date.available2024-04-30T18:49:55Z
dc.date.issued2019
dc.descriptionThis article belongs to the Special Issue Surface Mineral Allocation and Lithological Mapping Based on Remote Sensing
dc.description.abstractTraditional exploration techniques usually rely on extensive field work supported by geophysical ground surveying. However, this approach can be limited by several factors such as field accessibility, financial cost, area size, climate, and public disapproval. We recommend the use of multiscale hyperspectral remote sensing to mitigate the disadvantages of traditional exploration techniques. The proposed workflow analyzes a possible target at different levels of spatial detail. This method is particularly beneficial in inaccessible and remote areas with little infrastructure, because it allows for a systematic, dense and generally noninvasive surveying. After a satellite regional reconnaissance, a target is characterized in more detail by plane-based hyperspectral mapping. Subsequently, Remotely Piloted Aircraft System (RPAS)-mounted hyperspectral sensors are deployed on selected regions of interest to provide a higher level of spatial detail. All hyperspectral data are corrected for radiometric and geometric distortions. End-member modeling and classification techniques are used for rapid and accurate lithological mapping. Validation is performed via field spectroscopy and portable XRF as well as laboratory geochemical and spectral analyses. The resulting spectral data products quickly provide relevant information on outcropping lithologies for the field teams. We show that the multiscale approach allows defining the promising areas that are further refined using RPAS-based hyperspectral imaging. We further argue that the addition of RPAS-based hyperspectral data can improve the detail of field mapping in mineral exploration, by bridging the resolution gap between airplane- and ground-based data. RPAS-based measurements can supplement and direct geological observation rapidly in the field and therefore allow better integration with in situ ground investigations. We demonstrate the efficiency of the proposed approach at the Lofdal Carbonatite Complex in Namibia, which has been previously subjected to rare earth elements exploration. The deposit is located in a remote environment and characterized by difficult terrain which limits ground surveys.
dc.description.librarianMM2024
dc.facultyFaculty of Science
dc.identifier.citationBooysen, R., Zimmermann, R., Lorenz, S., Gloaguen, R., Nex, P.A., Andreani, L. and Möckel, R., 2019. Towards multiscale and multisource remote sensing mineral exploration using rpas: A case study in the lofdal carbonatite-hosted ree deposit, Namibia. Remote Sensing, 11(21), p.2500.
dc.identifier.doihttps://doi.org/10.3390/rs11212500
dc.identifier.urihttps://hdl.handle.net/10539/38408
dc.journal.titleRemote Sensing
dc.language.isoen
dc.publisherMDPI, Basel, Switzerland
dc.rights© 2019 by the authors
dc.schoolSchool of Geosciences
dc.subjectRemotely Piloted Aircraft System (RPAS)
dc.subjectMounted hyperspectral sensors
dc.subjectLofdal Carbonatite Complex
dc.subjectNamibia
dc.subjectMineral exploration
dc.subjectHyperspectral sensors
dc.subjectMultiscale
dc.subjectCarbonatite complex
dc.subject.otherSDG-17: Partnerships for the goals
dc.titleTowards multiscale and multisource remote sensing mineral exploration using rpas: A case study in the lofdal carbonatite-hosted ree deposit, Namibia
dc.typeArticle
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Booysen_Towards Multiscale_2019.pdf
Size:
18.06 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.43 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
*School of Geosciences (Journal Articles)