Date of Defense
7-4-2025 11:00 AM
Location
F3-132
Document Type
Thesis Defense
Degree Name
Master of Science in Geosciences
College
COS
Department
Geosciences
First Advisor
Dr. Mabrouk Sami Mohamed Hassan
Keywords
Sand Migration, Remote Sensing, Sand Dunes, Heavy Minerals, Geomorphological Features, Al Ain city, United Arab Emirates
Abstract
Sand migration significantly impacts urban development, infrastructure, and ecosystems in arid regions such as Al Ain city, United Arab Emirates (UAE). This study employs advanced remote sensing techniques to monitor and predict sand dune migration across the Sieh Al Hama dune field, a critical area west of Al Ain. The research objectives include quantifying dune migration rates over three years (2018–2020) using monthly Sentinel-2 satellite imagery, identifying distinct dune fields, and analyzing the textural and mineralogical properties of dune sediments to infer their provenance. Field sampling from four dunes (Large Sabra Dune, Dune 1, Dune 2, and Dune 3) was coupled with laboratory analyses, including grain size distribution, X-Ray Diffraction (XRD), and Scanning Electron Microscopy (SEM). The COSI-Corr software facilitated precise measurement of dune displacement, revealing well-sorted fine to medium sand dominated by quartz (up to 89.67%) and carbonates (up to 14.25%), with minor heavy minerals indicating mixed local (Oman Mountains, Jabal Hafit) and distant sources. The results demonstrate significant interannual variability, with the rate of migration peaking in 2019 (average 3.32 m) and changing seasonally, influenced by wind patterns. These findings indicate the effectiveness of remote sensing in tracking sand dynamics, providing important insights for urban development and environmental management in desert areas.
MONITORING SAND MIGRATION IN AL AIN CITY UTILIZING REMOTE SENSING TECHNIQUES
F3-132
Sand migration significantly impacts urban development, infrastructure, and ecosystems in arid regions such as Al Ain city, United Arab Emirates (UAE). This study employs advanced remote sensing techniques to monitor and predict sand dune migration across the Sieh Al Hama dune field, a critical area west of Al Ain. The research objectives include quantifying dune migration rates over three years (2018–2020) using monthly Sentinel-2 satellite imagery, identifying distinct dune fields, and analyzing the textural and mineralogical properties of dune sediments to infer their provenance. Field sampling from four dunes (Large Sabra Dune, Dune 1, Dune 2, and Dune 3) was coupled with laboratory analyses, including grain size distribution, X-Ray Diffraction (XRD), and Scanning Electron Microscopy (SEM). The COSI-Corr software facilitated precise measurement of dune displacement, revealing well-sorted fine to medium sand dominated by quartz (up to 89.67%) and carbonates (up to 14.25%), with minor heavy minerals indicating mixed local (Oman Mountains, Jabal Hafit) and distant sources. The results demonstrate significant interannual variability, with the rate of migration peaking in 2019 (average 3.32 m) and changing seasonally, influenced by wind patterns. These findings indicate the effectiveness of remote sensing in tracking sand dynamics, providing important insights for urban development and environmental management in desert areas.
