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UID:pretalx-foss4g-asia-2023-BUNEMV@talks.osgeo.org
DTSTART;TZID=KST:20231130T164000
DTEND;TZID=KST:20231130T170000
DESCRIPTION:Linear geomorphic features such as valleys and ridges tend to r
 epresent geologic lineaments and contribute important information in targe
 ting natural resources\, evaluating hazard risk and elucidate surface defo
 rmation caused by tectonic forces. Several methods have been proposed for 
 automatic lineaments detection and are mainly implemented using proprietar
 y software. As a result\, refinement of algorithm and optimization of para
 meter selection remains unresolved.\nThe focus of this research was to inv
 estigate the process of extracting lineaments from Digital Elevation Model
 s (DEM). The entire workflow was implemented and tested using the Free and
  Open Source GRASS GIS framework using existing functions and addons.\nAs 
 a preliminary step\, DEM was used to calculates terrain forms and associat
 ed geometry using the GRASS r.geomorphon function. As an alternative appro
 ach\, application of Convergence Index that depicts the structure of the r
 elief as channels and ridges was also applied. Test data covering parts of
  the Rokko mountain range in southeastern Hyōgo Prefecture\, Japan\, was 
 used to hightlight valley systems used as input for the Canny edge. The Ca
 nny filter generates one-pixel-wide line(s) representing the most probable
  edge position and combines several steps to produce an edge and an angle 
 map.\nIn the final step\, the Hough Transform algorithm used to extract si
 gnificant lines features by elimination the outlying pixels. The Hough tra
 nsform is optimized by using angle of edges as additional input to search 
 only pixels which are in the direction of a particular line. \nThe results
  using the data processing workflow were evaluated for the test site and t
 he efficacy of automatic lineament extraction techniques were successfully
  demonstrated. Further\, the algorithm was also tested on multi-direction 
 relief shades that highlight terrain features which would not in terrain f
 orm or Convergence Index maps alone. As an ongoing work\, optimizing param
 eter selection using machine learning is being tested to minimize subjecti
 vity in linear feature extraction. The presentation will highlight on adva
 ntages of the approach to extract and validate “geologic” lineaments a
 nd demonstrate results obtained using high-resolution DEM.\n\nKeywords: Li
 neaments\, DEM\, Terrain Forms\, Convergence Index\, Edge Extraction\, Hou
 gh Transform
DTSTAMP:20260609T153712Z
LOCATION:Seoul Archive
SUMMARY:Evaluation of Workflow for Linear Feature Extraction from Digital E
 levation Models Using GRASS GIS - Venkatesh Raghavan
URL:https://talks.osgeo.org/foss4g-asia-2023/talk/BUNEMV/
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