Mineral mapping with HYperspectral Digital Imagery Collection Experiment (HYDICE) sensor data at Cuprite, Nevada, U.S.A.

Abstract

Abstract Abstract The areal distributions of the minerals alunite, kaolinite, and calcite in an approximately 1.8km 2 area of the Cuprite mining district, Nevada, have been mapped by applying constrained energy minimization (CEM) to remotely sensed data from the HYperspectral Digital Imagery Collection Experiment (HYDICE) sensor, a 210 channel, 0.4 mum to 2.5 mum airborne hyperspectral imaging spectrometer. The image data analysed here have ground sample distances of approximately 3 m. CEM is a powerful and rapid technique for mineral mapping which requires only the spectrum of the mineral to be mapped and no prior knowledge of background constituents. Other spectral image processing techniques applied to the data produce results essentially identical to those of CEM and which agree with the mapping of Ashley and Abrams (1980).