Iron Oxides Mapping from E0-1 Hyperion Data

Abstract

Abstract The spatial and spectral capabilities of hyperion were considered highly suitable for mineral potential mapping. This study aimed to map iron oxide minerals from hyperion data set by following a procedure involving data pre-processing, atmospheric calibration and image classification. By several steps, the noise in the spectral and spatial domains was removed. These include the angular shift, along-track de-striping to remove the vertical stripes from the data set and reducing low-frequency spectral effect (smile). The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm in combination with the radiance transfer code MODTRAN4 was applied for quantification and removal of the atmospheric effect and retrieval of the surface reflectance. The reflectance values were compared with the spectra obtained from USGS spectral library and with the spectra obtained from radiometric measurements. Results derived from the visible and near infrared and shortwave infrared bands of hyperion between 400 to 2500nm represented iron oxide minerals signature at 465, 650 and 850–950 nm.