GEP  Vol.6 No.11 , November 2018
Vulnerability Analysis of Land Instability Using Multi-Criteria Evaluation for Urban Sustainability: Methodological Overview and Case Study Assessment
Abstract: There were many developed urban areas have been established without well studied from the hazards perspective. However, Mokattam Plateau is one of the most vulnerable areas of frequent landslides and rock-falls disasters (Moustafa et al., 1991). So, an integrated analysis method is highly needed. Spatial analysis of Multi-criteria evaluation (MCE) provided an assessment of the hazards’ factors (i.e. faults, joints, lithology, slope, old wadies/surface drainage, and quarries) at Mokattam area. The data have been analyzed by the MCE, Analytical Hierarchy Process (AHP)/Ordered Weighted Average (OWA)/Weighted Linear Combination (WLC). The research found that the geological factors (faults, joints, and lithology) were the highest contributors by about 65% of the hazardous driving forces, while the geomorphological processes (slope and old wadies/surface drainage) were contributed by about 30%. In addition, the impact of the human activities such as random urbanization, excess use of irrigation water and the transportation are critical hidden drivers that affect the land instability and accelerates the landslides and rock-falls (Amasha, 2009). Therefore, the decision makers and urban planners have to consider the four scenarios of low risk-high tradeoff (MIDAND), and high risk-some tradeoff (MIDOR) in their disaster risk management plans. While the risk-taking (OR) option is highly recommended for the new urban development projects to ensure the sustainability and risk resilience. While the risk-averse (AND) scenario is not recommended.
Cite this paper: Amasha, A. (2018) Vulnerability Analysis of Land Instability Using Multi-Criteria Evaluation for Urban Sustainability: Methodological Overview and Case Study Assessment. Journal of Geoscience and Environment Protection, 6, 124-138. doi: 10.4236/gep.2018.611010.

[1]   Albrecht, J. H. (1996). Universal GIS Operations for Environmental Modeling. Proceedings of the 3rd International Conference/Workshop on Integrating Geographic Information Systems and Environmental Modeling, Santa Fe, NM, 21-25 January 1996, National Center for Geographic Information and Analysis (NCGIA).

[2]   Amasha, A. (2009). Application of Remote Sensing, GIS and Multi-Criteria Evaluation in Hazard Assessment for Sustainable Development of GabalMokattam Area, East Cairo, Egypt (p. 167). Ph.D. Thesis, Egypt: Geology Department, Faculty of Science, Mansoura University.

[3]   CAPMAS (2017). The Estimated Census Data of Jan. 2017.

[4]   Carrara, A., Cardinali, M., Detti, R., Guzzettt, F., Pasqui, V., & Reichenbach, P. (1991). GIS Techniques and Statistical Models in Evaluating Landslide Hazard. Earth Surface Processes and Landforms, 16, 427-445.

[5]   Carver, S. (1991). Integrating Multi-Criteria Evaluation with Geographical Information Systems. International Journal Geographical Information Systems, 5, 321-339.

[6]   Eastman, J. R. (2006). IDRISI Andes Manual, Guide to GIS and Image Processing. Clark Labs, Clark Uni.

[7]   Eastman, J. R., & Jiang, H. (1996). Fuzzy Measures in Multi-Criteria Evaluation. 2nd International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Studies, Fort Collins, 21-23 May 1996, 527-534.

[8]   Gunawan, I., Giardino, J. R., & Tchakerian, V. P. (1992). Displaying and Evaluating Engineering Properties and Natural Hazards Using Geomorphic Mapping Techniques. Geological Society America Abstracts with Programs, 24, 18.

[9]   Lee, S., & Pradhan, B. (2006). Probabilistic Landslide Risk Mapping at Penang Island, Malaysia. Journal of Earth System Science, 115, 661-672.

[10]   Lee, S., & Pradhan, B. (2007). Landslide Hazard Mapping at Selangor, Malaysia Using Frequency Ratio and Logistic Regression Models. Landslides, 4, 33-41.

[11]   Moustafa, A. R., El-Nahhas, F., & Abdel Tawab, S. (1991). Engineering Geology of Mokattam City and Vicinity, Eastern Greater Cairo, Egypt. Engineering Geology, 31, 327-344.

[12]   National Authority for Remote Sensing and Space Sciences (NARSS) and Egyptian Geological Survey and Mining Authority, (EGSMA). Several Geological, Geomorphological and Geotechnical Studies for Selected Areas of Mokattam Plateau, as Internal Reports, in Years from 1993 to 2002.

[13]   Pradhan, B., & Lee, S. (2007). Utilization of Optical Remote Sensing Data and GIS Tools for Regional Landslide Hazard Analysis by Using an Artificial Neural Network Model at Selangor, Malaysia. Earth Science Frontier, 14, 143-152.

[14]   Pradhan, B., & Lee, S. (2009a). Landslide Susceptibility Assessment and Factor Effect analysis: Back Propagation Artificial Neural Networks and Their Comparison with Frequency Ratio and Bivariate Logistic Regression Modeling. Environmental Modelling & Software, 25, 747-759.

[15]   Pradhan, B., & Lee, S. (2009b). Landslide Risk Analysis Using Artificial Neural Network Model Focusing on Different Training Sites. International Journal of Physical Sciences, 3, 1-9.

[16]   Pradhan, B., Lee, S., & Buchroithner, M. F. (2009). Use of Geospatial Data for the Development of Fuzzy Algebraic Operators to Landslide Hazard Mapping: A Case Study in Malaysia. Applied Geomatics, 1, 3-15.

[17]   Ritter, D. F. (1988). Landscape Analysis and the Search for Geomorphic Unity. Geological Society of America Bulletin, 100, 160-171.<0160:LAATSF>2.3.CO;2

[18]   Ritter, D. F., Kochel, R. C., & Miller, J. R. (2001). Process Geomorphology (4th ed., p. 560). New York: McGraw-Hill College.

[19]   Roy, B. (1996). Multicriteria Methodology for Decision Aiding. Dordrecht: Kluwer Academic Publishers.

[20]   Saaty, T. L. (1977). A Scaling Method for Priorities in Hierarchical Structures. Journal of Mathematical Psychology, 15, 234-281.

[21]   Saaty, T. L. (1980). The Analytic Hierarchy Process, Planning, Priority Setting, Resource Allocation (p. 287). New York: McGraw-Hill.

[22]   Saaty, T. L. (1996). Decision Making for Leaders: The Analytical Hierarchy Process for Decisions in a Complex World. Vol. II. The Analytic Hierarchy Process Series (3rd ed., p. 291). Pittsburgh: RWS.

[23]   Saaty, T. L. (2003). Decision Making with the AHP. Why Is the Principle Eigenvector Necessary. European Journal of Operational Research, 145, 85-91.

[24]   Schumm, S. A. (1973). Geomorphic Thresholds and Compels Response in Drainage Systems. Fluvial Geomorphology, Binghamton, 299-310.

[25]   UNISDR (2015). Sendai Framework for Disaster Risk Reduction 2015-2030 (p. 32). United Nations Office for Disaster Risk Reduction (UNISDR).

[26]   Voogd, H. (1983). Multicriteria Evaluation for Urban and Regional Planning. London: Pion Ltd.

[27]   Yager, R. (1988). On Ordered Weighted Averaging Aggregation Operators in Multi-Criteria Decision Making. IEEE Transactions on Systems, Man, and Cybernetics, 18, 183-190.