The statistical prediction model for prospecting Nickel-Copper deposit based on aster remote sensing-geochemistry data in JinChuan and its peripheral

Abstract

Based on the relationship between the net reflectivity value of Aster data and geochemical index of trace elements, a statistical model had been established in Jinchuan Nickel-copper Mining area, Gansu province, China. The remote sensing geochemical anomalies over the areas extending towards south and northwest had been enclosed by analysing the geochemical surface sampling, surveying spectrum at corresponding points in field, determing spectrum characteristic spectral range and the threshold value of different element anomalies or different lithological section, as well as making line No.55 of remote sensing ,geology exploration and geochemical section as a benchmark. The study shows that the zones of remote sensing-geochemistry anomaly calculated by the statistical models consistent with the known mining areas, and there are traditional geochemical anomaly within the remote sensing geochemical anomaly in the parts of the unknown area, which is also validated by remote sensing geochemical anomalies distributed in periphery. By analyzing both remote sensing geochemical anomaly and regional geological data, the predictions achieve better effects than that by using the information of remote sensing and geochemical anomalies only.