Browsing by Author "Alsubaie, Naif Muidh"
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- ItemOpen AccessHandheld Mobile Mapping using Smartphones(2018-02-26) Alsubaie, Naif Muidh; El-Sheimy, Naser; Gao, Yang; Shaker, Ahmed; Noureldin, Aboelmagd; Kattan, LinaThis dissertation proposes a low-cost, handheld mobile mapping system (MMS) using smartphones. The current generation of smartphones is equipped with low-cost GPS receivers, high-resolution digital cameras, and micro-electro mechanical systems (MEMS)-based navigation sensors (e.g., accelerometers, gyroscopes, magnetic compasses, and barometers). These sensors are in fact the essential components for a MMS. However, smartphone navigation sensors suffer from the poor accuracy of global navigation satellite system (GNSS), accumulated drift, and high noise to signal ratio that are associated with inertial measurement unite (IMU). These issues affect the accuracy of the initial exterior orientation parameters (EOPs) that are input into the bundle adjustment algorithm, which then produces inaccurate 3D mapping solutions. First, the law of error propagation of variance is used to estimate the theoretical accuracy of using smartphones as handheld MMS. Then, robust sensors calibration is carried out to eliminate the deterministic errors associated with each sensor. Afterward, new methodologies are proposed to increase the accuracy of direct geo-referencing of smartphones. The prototype system was started by developing an iOS application that was to capture synchronized images with GPS and motion sensors measurements. The geo-referencing of captured mapping images was verified and improved using the proposed methodologies. This system was evaluated against ground truth data in different environments. In the absence of GPS multipath error, the RMSE of the system absolute accuracy is 3-4 meters in the horizontal direction and 13 meters in vertical direction. Furthermore, the RMSE of the system relative accuracy is 5 centimeters in the case of having more than 3 intersected light rays.
- ItemOpen AccessThe Potential of Using Worldview-2 Imagery for Shallow Water Depth Mapping(2012-12-14) Alsubaie, Naif Muidh; El-Sheimy, NaserWorldview-2 is the first very high resolution satellite imagery that has the ability to acquire data of eight bands named: Coastal (400 - 450 nm), Blue (450-510 nm), Green (510-580 nm), Yellow (585 - 625 nm), Red (630-690 nm), Red Edge (705 - 745 nm), Near Infrared(NIR) 1 (770-895 nm) and Near Infrared(NIR) 2 (860 - 1040 nm). Furthermore, five of these bands — Coastal Blue, yellow, red edge and NIR 2 are the new bands in WorldView-2 that are capable of extracting new features that were not possible with previous satellite imagery. Accurate and up-to-date bathymetric models are an effective tool for gaining a clearer understanding of the world’s waterways, and thus play an important role in many marine applications such as navigation. In this research, the automatic feature extraction technique will be used to locate water area edges. A threshold mask will then be used to determine small land and ships inside the shallow water area. An assessment will be done for all the eight bands to show their contribution to the bathymetry application and shore edge and shallow water outlining, with an emphasis on the yellow and Coastal bands. The conclusion and recommendation will be based on a statistical analysis of the comparison between Worldview-2 data and DEM data for the same area of interest.