Lateral Variations in Geologic Structure and Tectonic Setting from Remote Sensing Data

Abstract

The principal objective of this study was: (1) to assess the usefulness of remote sensing digital imagery, principally LANDSAT multispectral scanning (MSS) data, for inferring lateral variations in geologic structure and tectonic setting; and (2) to determine the extent to which these inferred variations correlate with observed variations in seismic excitation from underground nuclear explosion test sites in the Soviet Union. Soviet, French and U.S. test sites have been investigated to compare their geologic and tectonic responses as seen by LANDSAT. The characteristics of 'granite' intrusive bodies exposed at Semipalatinsk (Degelen), North Africa (Hoggar), NTS (Climax stock), and an analog site in Maine (Mt. Katahdin), have been studied in detail. The tectonic stress field inferred from the tectonic release portion of seismic signatures of explosions in these three areas is compared with local and regional fracture patterns discernable from imagery. The usefulness of satellite synthetic aperture radar (SAR) to determine geologic conditions and delineate fault (fracture) patterns is demonstrated by the analysis of SEASAT data for an area in the eastern United States. Algorithms to enhance structural boundaries and to use textures to identify rock types were developed and applied to several test sites.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1983
Accession Number
ADA130758

Entities

People

  • Shelton S. Alexander

Organizations

  • Pennsylvania State University

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Data Mining
  • Detection
  • Detectors
  • Earth Sciences
  • Electromagnetic Spectra
  • Geography
  • Geology
  • Glaciology
  • Igneous Rocks
  • Information Processing
  • Information Science
  • Mineralogy
  • Photographic Film
  • Scattering
  • Surveys
  • Tectosilicates
  • Topography

Fields of Study

  • Geology

Readers

  • Computer Vision.
  • Geotechnical Engineering.
  • Seismology

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space