Handheld Mobile Mapping using Smartphones

Simple item page
dc.contributor.advisorEl-Sheimy, Naser
dc.contributor.authorAlsubaie, Naif Muidh
dc.contributor.committeememberGao, Yang
dc.contributor.committeememberShaker, Ahmed
dc.contributor.committeememberNoureldin, Aboelmagd
dc.contributor.committeememberKattan, Lina
dc.date2018-06
dc.date.accessioned2018-03-06T15:56:28Z
dc.date.available2018-03-06T15:56:28Z
dc.date.issued2018-02-26
dc.description.abstractThis 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.en_US
dc.identifier.citationAlsubaie, N. M. (2018). Handheld Mobile Mapping using Smartphones (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/13060en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/13060
dc.identifier.urihttp://hdl.handle.net/1880/106415
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.facultySchulich School of Engineering
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectMobile mapping system
dc.subjectSmartphones
dc.subjectPhotogrammetry
dc.subjectFree network bundle adjustment
dc.subjectGNSS
dc.subjectIMU
dc.subject.classificationEngineeringen_US
dc.titleHandheld Mobile Mapping using Smartphones
dc.typedoctoral thesis
thesis.degree.disciplineGeomatics Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameDoctor of Philosophy (PhD)
ucalgary.item.requestcopytrue
ucalgary.thesis.checklistI confirm that I have submitted all of the required forms to Faculty of Graduate Studies.en_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ucalgary_2018_alsubaie_naif.pdf
Size:
5.57 MB
Format:
Adobe Portable Document Format
Description:
Thesis
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.74 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Open Theses and Dissertations