An exact technique of counting lineaments

Mostafa, Mostafa E.; Qari, Mohammed H.

doi:10.1016/0013-7952(95)00003-x

Cited by 23 publications

(24 citation statements)

References 5 publications

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“…For instance, geomorphological and hydrogeological evaluations of some wadis in eastern and western Saudi Arabia were made (Alsayari and Zötl 1978;Zaidi 1984). Some studies concentrated on hydrographs, runoff prediction and flood hazards and their relationships to morphometric parameters (Nouh 1987(Nouh , 1989(Nouh , 1990Qari 1995;Mustafa and Qari 1995;Şen and Al-Suba'i 2002;Şen 2008a, b). None of these studies had described, in detail, the interrelationships between morphometric variables of such basins due to difficulties in sampling techniques.…”

Section: Introductionmentioning

confidence: 99%

إستخدام نماذج الإرتفاعات الرقمية والطرق الإحصائية للمتغيرات المتعددة في تحليل المعاملات المورفومترية لبعض أودية غرب المملكة العربية السعودية

2010

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In arid regions, the analysis of wadi morphometric parameters and their interrelationships are fundamental for describing the topographic, geologic evolution, structures and hydrologic potential efficiency of the watershed. Unfortunately, the spatial characteristics and the analyses of these variables are not taken into consideration in an efficient way, especially in arid regions. In this paper, digital elevation model, geographic information system and multivariate statistical techniques are integrated for the identification and the assessment of main morphometric parameters. For this purpose, Q and R modes of cluster analyses and principal component analysis (PCA) are applied to ten different-size watersheds in the western region of Saudi Arabia utilizing 18 morphometric descriptors (variables). The results show that the R-mode cluster analysis classifies the variables into three groups, whereas the Q-mode cluster analysis classifies watersheds according to the similarities in their major variables such as area, perimeter, total stream length and peak discharge. The first three components of PCA accounted for 86% of the total variance in the data and show more details concerning the parameter loadings and the degree of variable significance.

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Section: Introductionmentioning

confidence: 99%

إستخدام نماذج الإرتفاعات الرقمية والطرق الإحصائية للمتغيرات المتعددة في تحليل المعاملات المورفومترية لبعض أودية غرب المملكة العربية السعودية

2010

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“…Then, three variables were calculated utilizing a computer program (Mostafa and Qari 1995). These variables are (1) number of lineaments within each cell, (2) total length of these lineaments within the cell, and (3) the number of lineament-to-lineament intersections within each cell.…”

Section: Lineament Analysismentioning

confidence: 99%

Lineament extraction from multi-resolution satellite imagery: a pilot study on Wadi Bani Malik, Jeddah, Kingdom of Saudi Arabia

Qari

2010

Arab J Geosci

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The study of structural lineaments is important for mineral exploration, geotectonic and geotechnical studies, and for the mitigation of geologic hazards. The present work deals with the extraction of lineaments from satellite imageries of different spatial resolutions as well as the analysis of these extracted lineaments. Wadi Bani Malik area located to the east of Jeddah city on the Red Sea coastal plain is chosen for such a study. Six types of digital satellite imagery data were used in the present study. These comprise satellite imagery of low spatial resolution (LSR) including Landsat MSS of 80-m resolution, Landsat TM of 30-m resolution, and Landsat TM of 25-m resolution; satellite imagery of moderate spatial resolution (MSR) including Landsat ETM+ panchromatic of 15-m resolution and SPOT panchromatic of 10-m resolution; and satellite imagery of high spatial resolution (HSR) including the Indian Remote Sensing satellite IRS data of 5-m resolution. As expected, the analysis of the extracted lineaments from different data sets shows that the imagery data of HSR of the Indian IRS data give the highest frequency of the extracted structural lineaments (N=3,235), while the imagery data of LSR of the Landsat MSS data give the lowest frequency of the extracted lineaments (N = 89). The imagery data of MSR give moderate frequency (N=1,643) in average. Due to the present study, it is recommended to use the imagery data of HSR and MSR for the extraction of structural lineaments for detailed and regional studies, respectively. The imagery data of LSR are not recommended for such studies due to the fact that most of the real structural lineaments framework cannot be extracted; accordingly, it is not useful in the analyses of lineaments for geological purposes.

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“…We can detect all of these conditions in aerial or space imagery (Majumdar and Bhattacharya 1998;Katsuaki et al, 1995;Walsh 2000;Mostafa and Bishta, 2005;Semere and Ghebreab, 2006 Consequently, optical remote sensing techniques over more than three decades have shown a great promise for mapping geological feature variations over wide scale (Mostafa and Bishta, 2005;Semere and Ghebreab, 2006;Marghany et al, 2009a). In referring to Katsuaki et al, (1995);Walsh (2000) lineament information extractions in satellite images can be divided broadly into three categories: (i) lineament enhancement and lineament extraction for characterization of geologic structure;(ii) image classification to perform geologic mapping or to locate spectrally anomalous zones attributable to mineralization (Mostafa et al, 1995;Süzen and Toprak 1998); and (iii) superposition of satellite images and multiple data such as geological, geochemical, and geophysical data in a geographical information system (Novak and Soulakellis 2000;Semere and Ghebreab 2006). Furthermore, remote sensing data assimilation in real time could be a bulk tool for geological features extraction and mapping.…”

Section: Satellite Remote Sensing and Image Processing For Lineament mentioning

confidence: 99%

“…In addition, automatic detection algorithm Canny are performed to acquire excellent accuracy of lineament extraction (Mostafa et al, 1995). Two procedures have involved to extract lineaments from LANDSAT ETM data.…”

Section: Model For 3-d Lineament Visualizationmentioning

confidence: 99%

Three-Dimensional Lineament Visualization Using Fuzzy B-Spline Algorithm from Multispectral Satellite Data

Marghany¹

2012

Remote Sensing - Advanced Techniques and Platforms

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An exact technique of counting lineaments

Cited by 23 publications

References 5 publications

إستخدام نماذج الإرتفاعات الرقمية والطرق الإحصائية للمتغيرات المتعددة في تحليل المعاملات المورفومترية لبعض أودية غرب المملكة العربية السعودية

إستخدام نماذج الإرتفاعات الرقمية والطرق الإحصائية للمتغيرات المتعددة في تحليل المعاملات المورفومترية لبعض أودية غرب المملكة العربية السعودية

Lineament extraction from multi-resolution satellite imagery: a pilot study on Wadi Bani Malik, Jeddah, Kingdom of Saudi Arabia

Three-Dimensional Lineament Visualization Using Fuzzy B-Spline Algorithm from Multispectral Satellite Data

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