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Terrain Analysis Algorithms Applied to Analyzing Geologic Structure

Dacre, Cynthia *1; Berry, John L.2; Way, Douglas S.1; Macdonald, Bruce 3
(1) MDA Information Systems Inc., Gaithersburg, MD.
(2) John Berry Associates Geology & Remote Sensing, Austin, TX.
(3) MDA Geospatial Services, Inc., Richmond, BC, Canada.

Recent advances in terrain analysis layers and methods have proven to be useful tools for improving efficiency in photogeologic interpretation. We provide descriptions and examples of four specific terrain analysis outputs that can be used to quickly identify geomorphic characteristics suggestive of underlying structure. These outputs include Summed Relative Elevation, Terrain Complexity, Likely Wet, and a RADAR processing algorithm that enhances texture. Summed Relative Elevation and Terrain Complexity are calculated strictly from Digital Elevation Models (DEMs). Summed Relative Elevation provides a measure of both local relief and regional relief trends, and effectively shows drainage patterns and other features without the directional bias inherent in a hillshade presentation. Terrain complexity is a measure of variation in morphology attributes, and often shows unusually-incised areas that may be related to folds or faults. The Likely Wet layer is developed from elevation data and landcover from spectral imagery. This data set shows areas where groundwater is likely close to the ground surface, and often highlights linear edges related to faults. Each of these three layers can be produced from various-resolution inputs if kernel size and other parameters are adjusted. The fourth example, from RADAR amplitude data, provides a display that optimally enhances variations in texture that may be due to linear and non-linear geologic features


AAPG Search and Discovery Article #90142 © 2012 AAPG Annual Convention and Exhibition, April 22-25, 2012, Long Beach, California