Mohammed El-Diasty

Sultan Qaboos University

Mohammed El-Diasty has been an associate professor in the Department of Civil and Architectural Engineering, College of Engineering, Sultan Qaboos University, since 2021. He was previously at Mansoura University, Egypt for twelve years and at King Abdulaziz University, Saudi Arabia for nine years. He received his MSc degree in civil engineering from Ryerson University, Canada and his Ph.D. in geomatics engineering from York University, Canada. Dr. El-Diasty’s Certified Professional Engineer (P.Eng.) status was awarded in Ontario, Canada. Dr. El-Diasty specializes in geomatics engineering. His research interests include positioning, navigation, mobile mapping, GNSS/INS integration, hydrography and gravimetry. He has received several research grants and has published scholarly scientific manuscripts in geomatics engineering research and practical fields.

1chapters authored

Chapters authored

Sensitivity Analysis and Modeling for DEM Errors

By Mohammed El-Diasty and Rifaat Abdalla

The Digital Elevation Model (DEM) can be created using airborne Light Detection And Ranging (LIDAR), Image or Synthetic-Aperture Radar (SAR) mapping techniques. The direct georeferencing of the DEM model is conducted using a GPS/inertial navigation system. The airborne mapping system datasets are processed to create a DEM model. To develop an accurate DEM model, all errors should be considered in the processing step. In this research, the errors associated with DEM models are investigated and modeled using Principal Component Analysis (PCA) and the least squares method. The sensitivity analysis of the DEM errors is investigated using PCA to define the significant GPS/inertial navigation data components that are strongly correlated with DEM errors. Then, the least squares method is employed to create a functional relationship between the DEM errors and the significant GPS/inertial navigation data components. The DEM model errors associated with airborne mapping system datasets are investigated in this research. The results show that the combined PCA analysis and least squares method can be used as a powerful tool to compensate the DEM error due to the GPS/inertial navigation data with about 27% in average for DEM errors produced by the direct georeferenced airborne mapping system.

Part of the book: Time Series Analysis

Mohammed El-Diasty

Chapters authored

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