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Improved Automated Identification and Mapping of Iron Sulfate Minerals, Other Mineral Groups, and Vegetation using Landsat 8 Operational Land Imager Data, San Juan Mountains, Colorado, and Four Corners Region

Scientific Investigations Map 3466
By: , , and 
https://doi.org/10.3133/sim3466

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Abstract

Multispectral remote sensing data acquired by the Landsat 8 Operational Land Imager (OLI) sensor were analyzed using a new, automated technique to generate a map of exposed mineral and vegetation groups in the western San Juan Mountains, Colo., and the Four Corners Region of the United States. Band ratio results were combined into displayed mineral and vegetation groups using Boolean algebra. New analysis logic has been implemented to exploit the coastal aerosol band in Landsat 8 OLI data and identify concentrations of iron sulfate minerals. These may indicate the presence of near-surface pyrite, which can be a potential nonpoint source of acid rock drainage. Zoned occurrences of iron sulfate minerals in areas surrounding and down gradient of known sources of pyrite have been mapped using this technique. They show high correlation with occurrences of jarosite-bearing mineral assemblages, as mapped using airborne imaging spectrometer data and supporting field verification surveys. Mapping the occurrence of iron sulfate minerals produced by the weathering and oxidation of pyrite in exposed hydrothermally altered rocks can also provide an important indicator of the genetic environment of alteration and the associated mineral deposit type. The automated analysis methodology is being employed to rapidly and cost-effectively generate maps of large regions of the United States in support of U.S. Geological Survey mineral resource and mineral-environmental assessments. This map, which includes the ERDAS IMAGINE thematic raster format in the data release, has been attributed by pixel value with mineral and vegetation group classification data, which can be queried in most image processing and GIS software packages.

Suggested Citation

Rockwell, B.W., Gnesda, W.R., and Hofstra, A.H., 2021, Improved automated identification and mapping of iron sulfate minerals, other mineral groups, and vegetation using Landsat 8 Operational Land Imager data, San Juan Mountains, Colorado, and Four Corners Region: U.S. Geological Survey Scientific Investigations Map 3466, 1 sheet, scale 1:325,000, 37-p. pamphlet, https://doi.org/10.3133/sim3466.

ISSN: 2329-132X (online)

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Table of Contents

  • Abstract
  • Introduction
  • Descriptions of Map Sheet and Associated ERDAS Imagine Raster Image File Included in This Publication
  • Description of Automated Analysis Methodology
  • Deficiencies of the Automated Analysis Methodology
  • Conclusions
  • Acknowledgments
  • References Cited
Publication type Report
Publication Subtype USGS Numbered Series
Title Improved Automated Identification and Mapping of Iron Sulfate Minerals, Other Mineral Groups, and Vegetation using Landsat 8 Operational Land Imager Data, San Juan Mountains, Colorado, and Four Corners Region
Series title Scientific Investigations Map
Series number 3466
DOI 10.3133/sim3466
Year Published 2021
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Geology, Geophysics, and Geochemistry Science Center
Description Pamphlet: v, 37 p.; 1 Sheet: 38.72 x 37.71 inches; 2 Data Releases: Read Me
Country United States
State Colorado, Utah
Other Geospatial Four Corners region, San Juan Mountains
Online Only (Y/N) Y
Google Analytic Metrics Metrics page
Additional publication details