Date of Award
Doctor of Philosophy
Dr. Mohamed Sultan
Dr. Ronald Chase
Dr. Duane Hampton
Dr. Osama Abudayyeh
Mountainous areas are quite often subjected to hazards related to their steep relief and intense precipitation events. These hazards (e.g., debris flows, mudflows, rockfalls) pose serious threats to settlements and structures that support transportation, agriculture, tourism, and other economic activities.
This study applies and develops a wide range of methodologies and tools that take advantage of readily available remote-sensing datasets, geographic information system technologies, and artificial intelligence techniques. The developed approaches allow the characterization of both spatial and temporal conditions that controlled mass movement occurrences and use these characteristics to model and mitigate future occurrences. The Jazan area in the southern Red Sea Hills of Saudi Arabia has been selected as a test site.
This project incorporates four research topics:
In the first section, in an effort to compensate for the paucity or lack of ground systems and historical databases, I implement methodologies that rely heavily on remote-sensing datasets to assess and understand the factors controlling debris flows and to predict their distribution on a regional scale.
In the second section, I develop a new artificial neural network (ANN)–based approach for susceptibility analyses and evaluate its performance by comparing the model outputs to those extracted using a conventional ANN modeling approach.
In the third section, I develop cost-effective, remote-sensing-based solutions for the mitigation of the modeled hazards (previous sections). They include: (1) the determination of optimal locations for civil engineering structures and (2) the development of a warning system for rainfall-induced events. The advocated practices will allow mitigation of the hazardous events with sufficient lead time, thus reducing their impacts on local communities.
In the fourth section, I use radar interferometry to detect and monitor mass movements that are experiencing slow rates of deformation, but that have the potential for much higher rates of movement during brief rainfall or earthquake events.
The four components of the study offer a broad, multidisciplinary range of advanced techniques that provide a better understanding and assessment of typical mountainous slope stability hazards. This effort is a step toward building safe and sustainable communities in data-scare mountainous regions.
Restricted to Campus until
El Kadiri, Racha, "An lntegrated Approach (Remote Sensing, GlS, Engineering, DataMining) for Modeling, Assessing and Mitigating Slope Stability Hazards in Mountainous Environments" (2014). Dissertations. 373.