Assessing Utilization of Multi-Resolution Satellite Imageries in Geological Mapping, A Case Study of Jabal Bani Malik Area, Eastern Jeddah City, Kingdom of Saudi Arabia
Adel Zein Bishta
Faculty of Earth Sciences, King Abdulaziz University
P.O.Box 80206, Jeddah 21589, Saudi Arabia
abishta@kau.edu.sa
Fig. 2. False color composite imageries of LSR data for the study area: (a) Landsat MSS
Image (80-m resolution),
(b) Landsat TM image (30-m resolution), and (c) Landsat
TM image (25-m resolution)
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JKAU: Earth Sci., Vol. 21, No. 1, pp: 27-52 (2010 A.D. / 1431 A.H.)
DOI: 10.4197 / Ear. 21-1.2
Abstract:
The different types of satellite imageries are considered as one of important useful source of data for the lithologicl discriminations and geological mapping. The modern and high advanced remote sensing technique supplies huge amounts of satellite imageries of different resolutions. This work aimed to assess utilization of the different satellite imagers of different resolutions in the geological mapping. Jabal Bani Malik area which is located to the east of Jeddah city in the Middle Eastern Red Sea is chosen as a case study for this work. This area is composed of different igneous and metamorphosed rocks of the Arabian shield. It is geologically complicated, sheared, fractured and weathered.
Different types of digital satellite imageries for the study area were used in this work, which comprises: Landsat MSS of 80 m resolution, Landsat TM of 30 m resolution, Landsat TM of 25 m resolution, Landsat ETM+ of 30 m resolution, Landsat ETM+ panchromatic of 15 m resolution, SPOT panchromatic of 10 m resolution and the Indian Remote Sensing Satellite IRS panchromatic data of 5 m resolution. These data are classified into three sets concerning the spatial resolutions: 1- Satellite imagery data of low spatial resolutions (LSR): which have a spatial resolution of 25 m or smaller, 2- Satellite imagery of moderate spatial resolutions (MSR): Which have a spatial resolutions ranging between 25 m to 10 m, and 3- Satellite imagery of high spatial resolutions (HSR): which are characterized by a spatial resolution greater than 10 m.
The processed satellite imagers produced from the three data sets were used in the geological mapping of the investigated area. Satellite imagery data of low spatial resolutions (LSR) are used for the regional studies and producing geological maps of scale 1:100,000 or smaller. Satellite imagery of moderate spatial resolutions (MSR) are used for the semi-regional studies and producing geological maps of scale ranging between 1:100,000 to 1:20,000. Satellite imagery of high spatial resolutions (HSR) are used for the detailed studies and producing geological maps of scale 1:20,000 or larger. The processed HSR imageries were used for the geological and structural interpretation and producing a detailed geological and structural maps of the investigated area. These maps are larger in scale and containing more information than the previous studies.
Introduction
Using of remote sensing data in geological mapping is an important approach for geological and structural studies. The geological mapping using remotely sensed data and image processing techniques has been used increasingly by several authors (e.g., Sultan et al., 1986, Richards, 1995, Meguid et al., 1996, Sabins, 1999, Mostafa and Bishta, 2004, and Bishta, 2005). In this work, the imagery data of different spectral and spatial resolution are employed in the geological mapping to test the different image processing techniques for the regional, semi detailed and detailed studies. Jabal (J) Bani Malik area which is located to the east of Jeddah city in the Middle Eastern Red Sea (Fig. 1) is chosen as a case study for this investigation.
Seven types of digital satellite imageries data for the study area were used in this study. These data were classified in this work into three sets concerning the spatial resolutions:
1- Satellite imagery data of low spatial resolutions (LSR): This type of data include all satellite imageries which have a spatial resolution of 25 m and more. In this work the LSR type comprises: Landsat MSS of 80 m resolution, Landsat TM of 30 m resolution and Landsat TM of 25 m resolution.
2- Satellite imagery of moderate spatial resolutions (MSR): This type of data include all satellite imageries which have a spatial resolution ranging between 25 m to 10 m. In this work the MSR type comprises Landsat ETM+ panchromatic of 15 m resolution and SPOT panchromatic of 10 m resolution.
3- Satellite imagery of high spatial resolutions (HSR): The satellite imageries of this type of data is characterized by a spatial resolution greater than 10 m (higher than both LSR and MSR). The HSR type is exampled in this investigation by the Indian Remote Sensing Satellite IRS panchromatic data of 5 m resolution.
Conclusions
The processed satellite imageries produced from the three data sets were used in the geological mapping and gave the following results:
1- Satellite imagery data of low spatial resolution (LSR), including imageries of spatial resolution of 25 m or lower. They are used for the regional studies, and producing geological maps of scale 1 : 100,000 or smaller. These data are used to construct false color composite images in RGB, color ratio images, and color composite images of principal component analysis. Also the unsupervised classification is carried out for these data.
2- Satellite imagery of moderate spatial resolution (MSR) including satellite imageries which have a spatial resolution ranging between 25 m to 10 m. They are used for the semi-regional studies, and producing geological maps of scale ranging between 1 : 100,000 to 1 : 20,000. The main processing technique applied for these data is the fusion technique, between the SPOT panchromatic image (MSR) and another multispectral color image of the lower resolution, such as ETM+ image(LSR) to get a color MSR image. Another important technique applied for the MSR data is the automatic lineament extraction from the digital panchromatic SPOT data.
3- Satellite imagery of high spatial resolution (HSR) are characterized by a spatial resolution greater than 10 m. They were used for the detailed studies, and producing geological maps of scale 1 : 20,000 or larger. The main processing technique applied for these data are the fusion and the lineaments extraction.
4- The processed HSR imageries are used for the geological and structural interpretation, and producing a detailed geological and structural maps of the investigated area in scale 1 : 5,000. These maps are larger in scale, and containing more information than the previous geological mapping.
5- It is recommended to use the LSR imageries for the regional studies, and producing regional geological maps. It is also recommended to use the LSR imageries with either MSR or HSR imageries, for applying the image processing techniques, to produce semi-regional geological mapping or detailed geological mapping, respectively.
References
Bishta, A.Z. (2005) “Using selective image processing techniques of Landsat-7 data in structural lineaments interpretation of Esh El Mellaha range, North Eastern Desert, Egypt" The fourth International Symposium on Geophysics, Tanta University, Tanta, Egypt.
Casas, A. M., Cortes, Angel L., Maestro, A., Soriano, M.A., Riaguas, A. and Bernal, J. (2000) “A program for lineament length and density analysis”, Computers and Geosciences, 26(9/10): 1011-1022.
Chang, Y., Song, G. and HSU, S. (1998) “Automatic Extraction of Ridge and Valley Axes Using the Profile Recognition and Polygon-Breaking Algorithm”, Computers and Geosciences, 24(1): 83-93.
Cortes, A.L., Soriano, M.A., Maestro, A. and Casas, A.M. (2003) “The role of tectonic inheritance in the development of recent fracture systems, Duero Basin, Spain”, International Journal of Remote Sensing, 24(22): 4325-4345.
Costa, R.D. and Starkey, J. (2001) “Photo Lin: a program to identfy and analyze linear structures in aerial photographs, satellite images and maps”, Computers and Geosciences, 27(5): 527-534.
Koike, K., Nagano, S. and Kawaba,K. (1998) “Constraction and Analysis of Interpreted Fracture Planes Through Combination of Satellite-Image Derived Lineaments and Digital Elevation Model Data”, Computers and Geosciences, 24(6): 573-583.
Leech, D.P., Treloar, P.J., Lucas, N.S. and Grocott, J. (2003) “Landsat TM analysis of fracture patterns: a case study from the Coastal Cordillera of northern Chile”, International Journal of Remote Sensing, 24(19): 3709-3726.
Lillesand, T.M., Keifer, R.W. and Chipman, J.W. (2004) “Remote Sensing and Image Interpretation”, 5th Edition, JohnWiley & Sons, Inc. USA, 763P.
Meguid, A.A., Maksoud, M.A., Abuzied, H.T., El Rakaiby, M.L. and Bishta, A.Z. (1996) "Photogeologic and aeroradiometric characterizations of the younger granites in the north Eastern Desert, Egypt and implications for mineral deposits." Africa Geoscience Review, 3(3/4): 471-484.
Mostafa, M.E. and Bıshta A.Z. (2004) “Significiance of lineament patterns in rock unit classification and designation: A pilot study on the Gharib-Dara area, northern Estern Desert, Egypt”, International Journal of Remote Sensing”, 26(7): 1463-1475.
Nama, E.E. (2004) “Lineament detection on Mount Cameroon during the 1999 volcanic eruptions using Landsat ETM”, International Journal of Remote Sensing, 25(3): 501-510.
O’Leary, D.W., Friedman, J.D. and Pohn, H.A. (1976) Lineament, linear, lineation: Some proposed new standards for old term, Geological Society America Bulletin, 87: 1463- 1469.
PCI, Geomatica, (2004) Version 9.1, Richmond Hill, Ontario, Canada.
Richards, J.A, (1995) Remote Sensing, Digital Image Processing, an Introduction, Springer Verlag, Berlin, 340 p.
Rowan, L. C. and E. H. Lathram, (1980) Mineral Exploration, Chapter 17, in Remote Sensing in Geology (B. S. Siegal and A. R. Gillespie, editors), John Wiley and sons, New York: 553- 605.
Sabins, F. F. (1999) Remote sensing for mineral exploration, Ore Geology Reviews, 14: 157-183.
Spencer, C.H., Cartier, A., and Vincent, P.L., (1988) Industrial mineral resources map of Jiddah, Kingdom of Saudi Arabia. Ministry of Petroleum and Mineral resources, Deputy Ministry for Mineral Resources.
Stefouli, M., A. Angellopoulos, S. Perantonis, N. Vassilas, N. Ambazis and E. Charou (1996) Integrated Analysis and Use of Remotely Sensed Data for the Seismic Risk assessment of the southwest Peloponessus Greec, First Congress of the Balkan Geophysical Society, 23- 27 September, Athens Greece.
Sultan, M., Arvidson, R.E., and Sturchio, N. (1986) "Mapping of serpentinites in the Eastern Desert of Egypt by using Landsat them,atic mapper data." Geology, 14 : 995-999.
Süzen, M.L. and Toprak, V. (1998) “Filtering of Satellite Images in Geological Lineament Analyses: An Application to a Fault Zone in Central Turkey”, International Journal of Remote Sensing, 19(6): 1101-1114.
Vassilas, N., Perantonis, S., Charou, E., Tsenoglou T., Stefouli, M. and Varoufakis, S. (2002) “Delineation of Lineaments from Satellite Data Based on Efficient Neural Network and Pattern Recognition Techniques” 2nd Hellenic Conf. on AI, SETN-2002, 11-12 April 2002, Thessaloniki, Greece, Proceedings, Companion Volume: 355-366.
تقييم استخدام مرئيات الأقمار الصناعية متعددة الدقة في التخريط الجيولوجي، حالة دراسة لمنطقة جبل بني مالك، شرق مدينة جدة، المملكة العربية السعودية
عادل زين الدين بشته
قسم الجيولوجيا والاستشعار عن بعد - كلية علوم الأرض
جدة - المملكة العربية السعودية
المستخلص
تعتبر الأنواع المختلفة لصور الأقمار الصناعية أحد مصادرَالبيانات المفيدة والهامة جدًا في عمليات التمييزالصخري والتخريط الجيولوجي. كما أن تقنيات الاستشعار عن بعد المتقدمة والحديثة تجهزنا دائما بكميات ضخمة من مرئيات الأقمار الصناعية ذات دقة مختلفة. ويهدف هذا العمل لتقييم استخدام مرئيات الأقمار الصناعية المختلفة الدقة في عمليات التخريط الجيولوجي. ولقد تم اختيار منطقة جبل بني مالك بشرق مدينة جدة لتطبيق استخدام هذه التقنية في هذا العمل. وهذه المنطقة متكونة من صخور الدرع العربي النارية والمتحولة، والمتأثرة بكسور فى اتجاهات مختلفة.
وفي هذا العمل تم استخدام أنواع مختلفة لمرئيات الأقمار الصناعية الرقمية لمنطقة الدراسة، التي تشمل: لاندسات MSS 80 م لاندسات TM 30م ولاندسات TM 25م و لاندسات ETM+ 30م و15م وسبوت 10م والقمر الصناعي الهندي للاستشعار عن بعد IRS 5م. وهذه البيانات تم تصنيفها إلى ثلاث مجموعات علي أساس الدقة المكانية:
1- بيانات مرئيات أقمار صناعية ذات دقة مكانية منخفضة (LSR): التي لها دقة مكانية 25م أَو أصغر.
2 - بيانات مرئيات أقمار صناعية ذات دقة مكانية متوسطة (MSR): التي لها دقة مكانية تتراوح بين 10 إلى 25م.
3 - بيانات مرئيات أقمار صناعية ذات دقة مكانية عالية (HSR): التي تتميز بدقة مكانية أكبر من 10م. ولقد تم تطبيق معالجات المرئيات الفضائية التي تناسب كل نوع من الأنواع السابقة.
ومرئيات الأقمار الصناعية المنتجة من الثلاثة مجموعات ذوات الدقة المختلفة استعملت في التخريط الجيولوجي لمنطقة الدراسة. ولقد اتضح أن بيانات الأقمار الصناعية ذات الدقة المنخفضة (LSR) يمكن استعمالها للدراسات الإقليمية والخرائط الجيولوجية المنتجة من مقياس 1: 100.000 أَو أصغر. بيانات الأقمار الصناعية ذات الدقة المتوسطة (MSR) يمكن استعمالها للدراسات نصف الإقليمية والخرائط الجيولوجية المنتجة من مقياس يَتراوح بين 1: 100.000 إلى 1: 20.000. أما بيانات الأقمار الصناعية ذات الدقة المكانية العالية (HSR) فتستعمل للدراسات المفصلة والخرائط الجيولوجية المنتجة من مقياس 1: 20.000 أَو أكبر. ولقد تم استخدام المرئيات الفضائية المنتجة من الأقمار الصناعية ذات الدقة المكانية العالية في التفسير الجيولوجي والتركيبي وانتاج خرائط جيولوجية وتركيبية لمنطقة الدراسة. هذه الخرائط أكبر في المقياس وتحتوي على المزيد من المعلومات أكثر من الدراسات السابقة.
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