HIGH-SPECTRAL RESOLUTION REMOTE SENSING FOR MINERAL MAPPING IN THE BODIE AND PARAMOUNT 
MINING DISTRICTS, CALIFORNIA 
Alvaro P. Crösta 
Geosciences Institute - University of Campinas 
Campinas, Säo Paulo, Brazil 
Charles Sabine 
James V. Taranik 
Desert Research Institute 
University and Community College System of Nevada 
Reno, Nevada, USA 
Commission VII, Working Group 4, ISPRS 
KEY WORDS: Remote Sensing, Geology, Radiometry, Hyperspectral, Classification, Mapping, Processing, Algorithms. 
ABSTRACT: 
This paper examines and compares recently developed techniques for hyperspectral data processing in the context of mineral 
mapping and exploration for precious metals. Hyperspectral data comprises AVIRIS (Airborne Visible and Infrared Imaging 
Spectrometer) imagery acquired by NASA's ER-2 aircraft at an altitude of 25 km in August, 1992. The study area is the Bodie and 
Paramount mining districts, in California, USA, both containing hydrothermally altered Tertiary volcanic rocks. 
Hyperspectral data were converted from radiance to apparent surface reflectance using a radiative transfer approach, based on 
atmospheric modelling using a modified MODTRAN method. The data were then processed for mineral identification using two 
techniques: spectral angle mapping (SAM) and the Tricorder algorithm. SAM is a supervised classification technique for mapping 
the similarity of image spectra to reference spectra. Tricorder uses an optimized least-square method to compare the spectrum for 
each pixel on the scene to library spectra. 
The results obtained for the Bodie and Paramount districts show that alteration zones of different mineralogy can be separated 
using these methods without any knowledge of field spectra or any a priori field data, thus configuring a "true" remote sensing 
method. Applications of this kind of technology are likely to benefit mineral exploration programs for precious metals, 
particularly in frontier regions where little geological information is readily available. 
1. INTRODUCTION 
Hyperspectral remote sensing has been under development 
since the first experimental sensor of this type, the Airborne 
Imaging Spectrometer (AIS), was first flown in 1983. Its 
successor, the Airborne Visible/Infrared Imaging Spectrometer 
(AVIRIS) was developed at JPL in 1987 and has continued to 
evolve since then. Data acquired by AVIRIS and also by some 
commercially operated imaging spectrometers developed during 
the 80's allowed a significant number of geological applications 
to be developed. Among these applications is the 
discrimination of rocks and minerals important to mineral 
exploration, in particular, mapping hydrothermal alteration 
minerals. 
However, the lack of routine availability of hyperspectral data 
covering diverse geological environments in different regions 
has restricted the full utilization of this type of data. Also, 
hyperspectral data required image processing algorithms 
specifically designed to take advantage of the high spectral 
resolution and to cope with the much larger amount of data than 
those used with conventional multispectral data. 
With the continued deployment of AVIRIS in different regions 
of North America, Europe (1991) and South America (1995), 
and the continued operation of other airborne scanners, 
progressively more data have become available. New 
algorithms for processing hyperspectral data have also been 
developed and some of them algorithms have recently been 
incorporated into commercial image processing software. 
This technology is currently under significant development, 
with several new imaging spectrometers being built and 
operated in recent years. In addition, spaceborne imaging 
spectrometers are planed for the near future. These 
developments, summarized by Taranik and Crôsta (1996), 
indicate a clear trend toward operational use of hyperspectral 
data in geological remote sensing in the near future. 
2. OBJECTIVES 
This paper examines and compares two different algorithms, the 
Spectral Angle Mapper (SAM) and Tricorder, recently 
developed for identifying surface materials in imaging 
spectrometry data. The objective was to assess the performance 
of these algorithms and their ability to map alteration minerals 
important to precious metals exploration. Unlike previous 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B7. Vienna 1996