Paper No. 19-15
Presentation Time: 11:30 AM
USING HYSPIRI PREPARATORY DATA FOR RAPID CLASSIFICATION OF HYDROTHERMAL ALTERATION
NASA’s Hyperspectral Infrared Imager (HyspIRI) is a proposed satellite instrument that would acquire 212 spectral channels from 0.38 to 2.5 µm concurrently with 8 channels in the thermal infrared. The instrument is well suited to address a wide range of earth science questions. To motivate selection of the satellite, prototype data are being collected seasonally across large sections of California in 2013 and 2014 using the airborne AVIRIS and MASTER instruments. We are funded to show how HyspIRI data could 1) identify new systems linked to critical minerals, 2) identify high priority sites for geothermal energy development, 3) assess the land surface changes associated with large scale energy development, and 4) map and monitor the impacts associated with energy and mineral resource extraction. Data collection swaths were established in collaboration with other investigators addressing many diverse science goals, and include volcanic, geothermal, and mining sites. For this campaign, data are collected at 18 m spatial resolution, and the mission team is generating HyspIRI simulated data at 60 m resolution. We have used the AVIRIS data to map hydrothermal alteration throughout the areas flown, focusing on the Chocolate Mountains, The Geysers geothermal field, and Long Valley caldera. Here we demonstrate how a simple decorrelation stretch using narrow spectral channels consistently highlights and classifies areas of advanced argillic, argillic, and chloritic or propylitic alteration. These areas are associated with ancient hydrothermal systems, which have potential for ore deposits, or modern geothermal systems, which have potential for power production. When the proposed HyspIRI satellite instrument is launched this type of rapid classification will be possible at 60 m spatial resolution for any location, with data collections every 19 days. We are also developing other methods to quickly classify lithologic units using both visible-near infrared and thermal infrared hyperspectral remote sensing data. HyspIRI-derived lithologic maps would aid in reconnaissance for both mineral and geothermal exploration, refining mineral maps previously made using multispectral satellite systems such as Landsat or ASTER.