Landsat 7 Enhanced Thematic Mapper Plus image data was used to identify and map alluvial fans features in Shaikh Ibrahim anticline northern Iraq. In the present study, an active flowchart was design to extract and determine alluvial fans using digital image processing operations and digital elevation analysis. Two image processing methods including (image transformation and image enhancement) were used. Image transformation including principal component analysis (PCA) and ratio images (RI) analysis, while image enhancement operation including false color composite images (FCC). In image transformation processing, Based on the detailed analysis of eigenvectors and eigenvalues derived from different combinations of (PCA), five (PC) images of bands (13457) have been extracted and –PC4 has relatively strong positive loading for band 5 (0.632166) and high negative loading for band 7 (-0.369417) consequently, PC4 was given effective delineation about the major alluvial fans at the southwestern footslope from Shaikh Ibrahim anticline. In ratio image analysis, A combination of (RI) based on the spectral characteristics of alluvial fans materials were selected. Image enhancement includes A false color image of the subscene was produced by assigning band (741). This color composite was found to be useful in emphasizing to the all materials of alluvial fans. Digital elevation models (DEM) were used for describing topographic features related to the alluvial fans.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.