River Courses Affected by Landslides and Implications for Hazard Assessment: A High Resolution Remote Sensing Case Study in NE Iraq–W Iran

Othman, Arsalan Ahmed; Gloaguen, Richard

doi:10.3390/rs5031024

Cited by 39 publications

(19 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This belt is around 2000 km long, extending from SE Turkey through Iraq to southern Iran [35][36][37][38]. The Iraqi part of the Zagros orogenic belt consists of three main tectonic zones: (1) the Inner Platform (stable shelf); (2) the Outer Platform (unstable shelf), which comprises the Mesopotamia Foredeep, the Foothill Zone, the High Folded Zone, and the Imbricated Zone (IZ); and (3) the Zagros Suture Zone (ZSZ) ( [9,30,36,39,40]; Figure 1).…”

Section: Location and Geological Settingmentioning

confidence: 99%

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

2014

Self Cite

View full text Add to dashboard Cite

Abstract:The mineral ore potential of many mountainous regions of the world, like the Kurdistan region of Iraq, remains unexplored. For logistical and sometimes political reasons, these areas are difficult to map using traditional methods. We highlight the improvement in remote sensing geological mapping that arises from the integration of geomorphic features in classifications. The Mawat Ophiolite Complex (MOC) is located in the NE of Iraq and is known for its mineral deposits. The aims of this study are: (I) to refine the existing lithological map of the MOC; (II) to identify the best discriminatory datasets for lithological classification, including geomorphic features and textures; and (III) to identify potential locations with high concentrations of chromite. We performed a Support Vector Machine (SVM) classification method to allow the joint use of geomorphic features, textures and multispectral data of the Advanced Space-borne Thermal Emission and Reflection radiometer (ASTER) satellite. The updated map allowed the identification of a new mafic body and a substantial improvement of the geometry of the known lithological units. The use of geomorphic features allowed for the increase of the overall accuracy from 73% to 79.3%. In addition, we detected chromite occurrences within the ophiolite by applying Spectral Angle Mapping (SAM) technique. We identified two new locations having high concentrations of chromite and verified one of these promising areas and has coarsely crystalline chromite within dunite host rock. The chromium (Cr 2 O 3 ) concentration is ~8.46%. The SAM and SVM methods applied on ASTER satellite data show that these can be used as a powerful tool to explore ore deposits and to further improve lithological mapping in mountainous semi-arid regions.

show abstract

Section: Location and Geological Settingmentioning

confidence: 99%

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…It is of high practical value in a large number of applications in diverse disciplines, such as crop growth monitoring [2], urban sprawl detection [3,4], hazard assessment [5], and snow cover monitoring [6]. Therefore, change detection has become an attractive research topic in remote sensing communities recent years.…”

Section: Introductionmentioning

confidence: 99%

Change Detection in SAR Images Based on Deep Semi-NMF and SVD Networks

et al. 2017

View full text Add to dashboard Cite

Abstract:With the development of Earth observation programs, more and more multi-temporal synthetic aperture radar (SAR) data are available from remote sensing platforms. Therefore, it is demanding to develop unsupervised methods for SAR image change detection. Recently, deep learning-based methods have displayed promising performance for remote sensing image analysis. However, these methods can only provide excellent performance when the number of training samples is sufficiently large. In this paper, a novel simple method for SAR image change detection is proposed. The proposed method uses two singular value decomposition (SVD) analyses to learn the non-linear relations between multi-temporal images. By this means, the proposed method can generate more representative feature expressions with fewer samples. Therefore, it provides a simple yet effective way to be designed and trained easily. Firstly, deep semi-nonnegative matrix factorization (Deep Semi-NMF) is utilized to select pixels that have a high probability of being changed or unchanged as samples. Next, image patches centered at these sample pixels are generated from the input multi-temporal SAR images. Then, we build SVD networks, which are comprised of two SVD convolutional layers and one histogram feature generation layer. Finally, pixels in both multi-temporal SAR images are classified by the SVD networks, and then the final change map can be obtained. The experimental results of three SAR datasets have demonstrated the effectiveness and robustness of the proposed method.

show abstract

“…This rugged topography with the presence of long and narrow anticlines (Sissakian and Fouad, 2012;Fouad, 2012;Othman and Gloaguen, 2014;2013a;2013b) and climatic effect has contributed in increasing the intensity of the erosion, the water being the main agent. Consequently, the anticlines are deeply dissected by tens of erosional forms, which are continuously developing and enlarged in size due to the continuous growth of the anticlines (Keller and Pinter, 2002;Huggett, 2007;Ramsey, et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Factors Controlling the Development of Straight Valleys and Streams in the Kurdistan Region, North and Northeast of Iraq

Sissakian

Shihab²,

Othman³

2017

ARO

Self Cite

View full text Add to dashboard Cite

Abstract-TheIraqi Kurdistan Region is a mountainous area with relief difference ranging from few hundred meters up to 3000 m, and locally more. Almost all of the mountains form anticlines that have NW-SE trend changing westwards of longitude to E-W. The carapace of the majority of the mountains is built up of Cretaceous rocks; however, some of them are of older rocks. Many of those anticlines are crossed by straight valleys and/or are crossed by streams and rivers which form again straight lines and almost coincide with regional lineaments, usually in N-S or NE-SW trend. The studied straight valleys are controlled, most probably by tectonic factors, therefore, exhibit special topographic forms, like straight lineaments crossing many successive anticlines, and also clear bending in some of the ridges in their crossing points to the valleys and/or streams. This paper aims to determine and discuss the factors that control the development of the straight valleys and/or lineaments. To achieve this aim, remote sensing and GIS techniques were followed, using Landsat, QuickBird images as well as geological maps of different scales, and different published articles.

show abstract

River Courses Affected by Landslides and Implications for Hazard Assessment: A High Resolution Remote Sensing Case Study in NE Iraq–W Iran

Cited by 39 publications

References 28 publications

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

Change Detection in SAR Images Based on Deep Semi-NMF and SVD Networks

Factors Controlling the Development of Straight Valleys and Streams in the Kurdistan Region, North and Northeast of Iraq

Contact Info

Product

Resources

About