GSA Connects 2023 Meeting in Pittsburgh, Pennsylvania

Paper No. 96-5
Presentation Time: 8:00 AM-5:30 PM

ANALYSIS OF HYPERSPECTRAL VERSUS MULTI-SPECTRAL DATA FROM DRONE-BASED ACID MINE DRAINAGE MONITORING IN PERRY CANYON, NV


SOLDANO, Vincent, Department Of Geological Sciences and Engineering, University of Nevada - Reno, 1664 N. Virginia Street, Reno, NV 89557, CALVIN, Wendy, Department of Geological Sciences and Engineering, University of Nevada, Reno, NV 89557 and MCCOY, Scott, Department of Geological Sciences and Engineering, University of Nevada, Reno, Reno, NV 89557

Remotely operated aerial systems (drones) are effective for monitoring temporal change at remediated acid mine drainage sites (Cramer et al. "Mapping Potentially Acid Generating Material on Abandoned Mine Lands Using Remotely Piloted Aerial Systems". Minerals, 2021, 11, 365). In June of 2021, hyperspectral data of Perry Canyon, NV was acquired in 271 spectral channels in the visible and near-infrared (VNIR) and 270 spectral channels in the short-wave infrared (SWIR). This project seeks to evaluate whether the increased spectral fidelity justifies the increased cost for the hyperspectral analysis of acid mine drainage sites. These hyperspectral images were analyzed using Environment for Visualizing Images (ENVI) software to map different spectral signatures throughout the site. This analysis provides evidence of three unique spectral signatures that could be associated with potentially acid generating material (PAGM). These spectra are classified as Yellow Soil (jarosite), White and Blue Soil (efflorescent mineral salts), and Red Soil (iron oxides and secondary iron-rich coatings indicative of acid mine drainage). Jarosite is an iron-bearing sulfate used to locate areas of PAGM, and red soils can isolate heavy metals that generate acidic water. Both jarosite and iron-oxide bearing soils have a diagnostic spectral reflectance which makes them useful at locating PAGM. Classification models such as Spectral Angle Mapper (SAM), Maximum Likelihood (ML), and Band Math Ratios (BMR) delineate areas where these spectra are observed. These classification models will be used to corroborate both VNIR and SWIR datasets as well as to compare spectral fidelity. Inclusion of SWIR data will increase knowledge of possible benefits or setbacks when using these data to map PAGMs. SWIR data also provides a greater range of spectral wavelengths that can lead to increased accuracy when determining pixel choice for PAGMs because most have stronger absorption and reflectance features in SWIR. These new surface compositional maps allow the comparison of our results to those of the previous 5-channel data, which were only analyzed using VNIR. It is expected that the increased spectral fidelity will offer more information, and greater detail, of PAGM at this site.