Three Dimensional Terrain Modeling for Tectonic Geomorphology of Chinara Anticline, Northern Iraq
Analysis of the terrain using three-dimensional models offers a deep insight view of ground surface topography and terrain representation. The Chinara anticline is one of the main structures of NW-SE trends for the highly folded zone in northeastern Iraq. The objective of this study is to u...
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| Format: | Article |
| Language: | English |
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Union of Iraqi Geologists (UIG)
2021-03-01
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| Series: | Iraqi Geological Journal |
| Online Access: | http://igj-iraq.org/igj/index.php/igj/article/view/406 |
| Summary: | Analysis of the terrain using three-dimensional models offers a deep insight view of ground surface topography and terrain representation. The Chinara anticline is one of the main structures of NW-SE trends for the highly folded zone in northeastern Iraq. The objective of this study is to understand the interrelationship between topography and morphotectonic features using three-dimensional models. This research employed fourth generates principal raster derivative products from the DEM using ArcGIS. To understand the undulating of this anticline with the morphotectonic style, the adaptive equation has been suggested to determine the direction and amount of the main tectonic forces, which can be applied to other undulated anticlines. The values of northeastern and southwestern limbs undulating index UI are 11.7 and 7.8 respectively that indicates the strong tectonic force towards the northeast. Two listric faults have been conducted via the field survey that confirmed by remotely sensed interpretation and DEM products. These listric faults had an intensive impact in comparison with concluded strike-slip faults, and then the Chinara anticline would be less structural undulating in a region of vicinity syncline to Perat undulation. The morphotectonic landscapes reveal that the listric fault has branched into two parts, the first one extending to form the anticline and the other comprises the structural dilemma. |
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| ISSN: | 2414-6064 2663-8754 |