Boissieu Florian de auteur aut IRD Sevin B. auteur aut IRD Cudahy T. auteur aut IRD Mangeas Morgan auteur aut IRD Chevrel S. auteur aut IRD Ong C. auteur aut IRD Rodger A. auteur aut IRD Maurizot P. auteur aut IRD Laukamp C. auteur aut IRD Lau I. auteur aut IRD Touraivane T. auteur aut IRD Cluzel D. auteur aut IRD Despinoy Marc auteur aut IRD text journalArticle eng text/pdf born digital access Accurate maps of Earth's geology, especially its regolith, are required for managing the sustainable exploration and development of mineral resources. This paper shows how airborne imaging hyperspectral data collected over weathered peridotite rocks in vegetated, mountainous terrane in New Caledonia were processed using a combination of methods to generate a regolith-geology map that could be used for more efficiently targeting Ni exploration. The image processing combined two usual methods, which are spectral feature extraction and support vector machine (SVM). This rationale being the spectral features extraction can rapidly reduce data complexity by both targeting only the diagnostic mineral absorptions and masking those pixels complicated by vegetation, cloud and deep shade. SVM is a supervised classification method able to generate an optimal non-linear classifier with these features that generalises well even with limited training data. Key minerals targeted are serpentine, which is considered as an indicator for hydrolysed peridotitic rock, and iron oxy-hydroxides (hematite and goethite), which are considered as diagnostic of laterite development. The final classified regolith map was assessed against interpreted regolith field sites, which yielded approximately 70% similarity for all unit types, as well as against a regolith-geology map interpreted using traditional datasets (not hyperspectral imagery). Importantly, the hyperspectral derived mineral map provided much greater detail enabling a more precise understanding of the regolith-geological architecture where there are exposed soils and rocks. specialized Hyperspectral Spectroscopy Recognition Classification Support vector machine Mineralogy Geology Iron oxide Serpentine Mapping NOUVELLE CALEDONIE 126 064 128 64 377-385 2018 0303-2434 https://www.documentation.ird.fr/hor/fdi:010071320 10.1016/j.jag.2017.05.012 0303-2434 [F B010071320] https://www.documentation.ird.fr/hor/fdi:010071320 https://www.documentation.ird.fr/intranet/publi/2017/11/010071320.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2017-12-04 2023-07-11 fdi:010071320 fre