Research on Information Extraction Technology of Iron Oxide Based on Airborne Hyperspectral Data

Aiming at the problem of low accuracy in evaluating the content of hematite, goethite and limonite by hyper-spectral technology, this paper proposed a method for estimating iron oxide abundance in surface rocks by using airborne hyper-spectral data CASI. The research is started with accurate and reliable data collection. Then, the airborne hyper-spectral data were preprocessed, including geometric rectification, radiation correction, atmospheric correction and spectral reconstruction. Basing on that, the spatial distributing information of hematite, goethite and limonite had been extracted. Besides, according to the spectral absorption features, the iron relative abundance inversion model was built. Finally, combining with the geological setting of study area and previous study, the authors forecast other favorable target areas using alteration distribution map. The results reveal that extraction of anomalies agrees with the ore-bearing strata. Mineralization clues have been found in prediction areas, which show practical meanings.