Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385539
Title: Three-dimensional integration of remotely sensed imagery and subsurface geological data
Author: McMahon, Michelle J.
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 1993
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Abstract:
The standard approach to integration of satellite imagery and sub-surface geological data has been the comparison of a map-view (two-dimensional) image interpretation with a selection of sub-surface cross-sections. The relationship between surface and subsurface geology can be better understood through quantitative three-dimensional (3-D) computer modelling. This study tests techniques to integrate a 3-D digital terrain model with 3-D sub-surface interpretations. Data types integrated, from a portion of the Paradox Basin, SE Utah, USA, include Landsat TM imagery, digital elevation data (DEM), sub-surface gravity and magnetic data, and wellbore data. Models are constructed at a variety of data resolutions. Combined modelling of basement and topographic features suggests the traditional lineament analysis approach to structural interpretation is over-simplistic. Integration of DEM and image data displayed in 3-D proved more effective for lithology discrimination than a map-view approach. Automated strike and dip interpretation algorithms require DEM data at resolutions of the order of 30 metres or better. Methods are described for the creation of fault-plane maps from three-dimensional displays of surface and subsurface data. The approach used in this study of linking existing software packages (Erdas image processing system, CPS3 mapping package and SGM and GTM three-dimensional geological modelling packages) is recommended for future studies. The methodology developed in this study is beneficial to interpretation of imagery data in frontier exploration areas.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.385539  DOI: Not available
Keywords: Pattern recognition & image processing Pattern recognition systems Pattern perception Image processing Geology Mineralogy Sedimentology
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