Geologic Mapping of United Arab Emirates using Multispectral Remotely Sensed Data
- 1 University Technology Malaysia, Malaysia
- 2 University Putra Malaysia, Malaysia
Problem statement: Geological studies are requiring standard methods and procedures to acquire precisely information. However, traditional methods might be difficult to use due to highly earth complex topography. Regarding the previous prospective, the advantage of satellite remote sensing in its application to geology is the wide coverage over the area of interest, where much accurate and useful information such as structural patterns and spectral features can be extracted from the imagery. Yet, abundance of geological features are not be fully understood. Lineaments are considered the bulk geological features which are still unclear in spite of they are useful for geological analysis in oil exploration. In this sense, the lineament extraction is very important for the application of remote sensing to geology. However the real meaning of lineament is still vague. Lineaments should be discriminated from other line features that are not due to geological structures. In this context, the lineament extraction should be carefully interpreted by geologists. Recent research was presented the mapping of geological features in the United Arab Emirates (UAE) using multispectral remotely sensed data. Approach: In doing so, image enhancement contrast, stretching and linear enhancement was performed to acquire an excellent visualization. Further, automatic detection algorithm of Canny was performed to extract linear features in multispectral remote sensing data, lineaments and fractures. Results: Uncertainties DEM model was performed by using fuzzy B-spline algorithm to map spatial lineament variations in a Three Dimensional (3D) visualization. Conclusion: In conclusion, an excellent tool for 3D geological features mapping can be established by integration of the canny algorithm with DEM which was generated by using fuzzy B-spline.
Copyright: © 2021 Maged Marghany, Shattri Mansor and Mazlan Hashim. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- 3D visualizations
- multispectral remotely sensed data