Abstract
Dayaoshan, as an important metal ore-producing area in China, is faced with the dilemma of resource depletion due to long-term exploitation. In this paper, remote sensing methods are used to circle the favorable metallogenic areas and find new ore points for Gulong. Firstly, vegetation interference was removed by using mixed pixel decomposition method with hyperplane and genetic algorithm (GA) optimization; then, altered mineral distribution information was extracted based on principal component analysis (PCA) and support vector machine (SVM) methods; thirdly, the favorable areas of gold mining in Gulong was delineated by using the ant colony algorithm (ACA) optimization SVM model to remove false altered minerals; and lastly, field surveys verified that the extracted alteration mineralization information is correct and effective. The results show that the mineral alteration extraction method proposed in this paper has certain guiding significance for metallogenic prediction by remote sensing.
Highlights
Surrounding rock alteration is one of the important interpretation markers of mineral exploration using remote sensing technology [1,2]
This study describes a methodology for gold ore deposit identification based on ASTER data using support vector machine (SVM) and principal component analysis (PCA) in areas of high vegetation
Gulong in the Dayaoshan metallogenic belt of Guangxi was taken as the study area for field verification
Summary
Surrounding rock alteration is one of the important interpretation markers of mineral exploration using remote sensing technology [1,2]. The metasomatism of hydrothermal mineralization can cause the minerals to alter and generate groups or ions such as Fe3+, magnesium hydroxyl group and aluminum hydroxyl group, which show different hue and spectral characteristics compared to the non-altered rock in remote sensing images [3,4,5]. In the process of mineral exploration, according to the different hue and reflectance spectra of altered minerals, the composition and spatial distribution of altered minerals can be analyzed using remote sensing technology, and the favorable metallogenic areas can be found out. Some have researched the identification of hydrothermal alteration minerals using multi- and hyper-spectral images [13,14,15,16]. In recent years, altered mineral identification has been investigated by using different methods in different locations for mineral exploration, including alteration mineral mappRienmgoteinSenths.e20N19o, 1r1t,hxwFOeRstPeErEnR JRuEnVgIEgWar basin using Landsat thematic mapper (TM) data and2porfi2n3cipal compaolnteernattiaonnamlyinsiesra(Pl mCAap)p[1in7g],ipnrtehdeiNctoivrtehmweinsteerranl JpurnogsgpaercbtiavsiitnyumsiondgeLlainngdsfaotrtCheumdaetpicomsiatspipnerV(aTrMza)ghan distridcta,taNaWndIprarinncbipaaslecdomonpothnenstuapnpaloyrstisv(ePcCtAor) [m17a]c, hprinedeic(StiVveMm)in[1e8ra],l apsrowspeelcltaivsitpyrmedoidcetilivnegmfoor dCeuls for RodaldqeupiolasirtsmininVinagrzdagishtarnicdt imstirnicetr, aNlWproIrsapnebcatisveidtyoninththeesuspopuothrtevaescttoofr Smpaacihninwei(tShVmMa)c[h18in],ealsewarenllinags [19]
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