A new vegetation index for detecting vegetation anomalies due to mineral deposits with application to a tropical forest area

This study aimed at developing a geobotanical remote sensing method to explore mineral deposits in areas covered by thick vegetation. For this, a new vegetation index (VI) is proposed using reflectance data from five bands in the visible green to shortwave infrared region. This index is called VIGS (Vegetation Index considering Greenness and Shortwave infrared), developed so that the VI can accurately detect vegetation stress caused by metal contamination of soils. A set of laboratory experiments was conducted to demonstrate the capability of VIGS, which investigates change in reflectance spectra based on the concentration of four selected metals (Cu, Pb, Zn, and Cd) in soils. The results show that VIGS values are more sensitive to vegetation stress than the Normalized Difference Vegetation Index and can amplify the stress difference, depending on soil metal contents. The VIGS is further examined for a mineralized area containing hydrothermal copper deposits in Jambi, central Sumatra, Indonesia, for which a set of geochemical data of the top layer composed of weathered rocks and soils were systematically obtained. Through kriging of point content data, the spatial distributions of Cu, Pb, and Zn in soil are found to be strongly correlated with the geology and controlled by faults. Using one Landsat ETM + scene image after atmospheric correction, VIGS values are calculated by a combination of reflectances in bands 2, 3, 4, 5, and 7. The effectiveness of VIGS is proven by this case study, because VIGS anomalies appeared in high-content zones common to the three metals. This concordance probably originated from the fact that plant formations (mainly primary forest) in the high metal zones are closely related to the geological units.