Análise de imagens hiperespectrais pelo método multiple endmember spectral mixture analysis (mesma) em depósito supergênico de níquel

Abstract

The hyperspectral remote sensing provides a large amount of data allowing the development computing methods to improve detection and quantification of the materials that compose a given scene. In that context, the Multiple Endmember Spectral Mixture Models (MESMA) is an approach of the Spectral Mixture Analysis, which defines the best-fit model to describe each pixel. A key problem in this method is the computational time expended. The Spectral Correlation Mapper (SCM) was applied for a pre-classification of the material in order to decrease the computational time. The MESMA routine was developed in IDL language to identify the best-fit models considering the least RMS error. This method was applied to for the Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) subscene of Niquelândia, Goias, that includes a lateritic nickel mine. The main minerals present in the weathering profile are: pimelite, saponite, goethite, hematite and kaolinite. The results attest that the calculated relative abundance of the mineral corresponds with field data.