Doctoral Dissertations
Keywords and Phrases
Drone; Geospatial; Mapping; Surveying; Unmanned Aerial Vehicles; Unmanned Aircraft Systems
Abstract
"Unmanned Aerial Systems (UAS) are rapidly blurring the lines between traditional and close range photogrammetry, and between surveying and photogrammetry. UAS are providing an economic platform for performing aerial surveying on small projects. The focus of this research was to describe traditional photogrammetric imagery and Light Detection and Ranging (LiDAR) geospatial products, describe close range photogrammetry (CRP), introduce UAS and computer vision (CV), and investigate whether industry mapping standards for accuracy can be met using UAS collection and CV processing. A 120-acre site was selected and 97 aerial targets were surveyed for evaluation purposes. Four UAS flights of varying heights above ground level (AGL) were executed, and three different target patterns of varying distances between targets were analyzed for compliance with American Society for Photogrammetry and Remote Sensing (ASPRS) and National Standard for Spatial Data Accuracy (NSSDA) mapping standards. This analysis resulted in twelve datasets. Error patterns were evaluated and reasons for these errors were determined. The relationship between the AGL, ground sample distance, target spacing and the root mean square error of the targets is exploited by this research to develop guidelines that use the ASPRS and NSSDA map standard as the template. These guidelines allow the user to select the desired mapping accuracy and determine what target spacing and AGL is required to produce the desired accuracy. These guidelines also address how UAS/CV phenomena affect map accuracy. General guidelines and recommendations are presented that give the user helpful information for planning a UAS flight using CV technology."--Abstract, page iii.
Advisor(s)
Burken, Joel G. (Joel Gerard)
Mendoza, Cesar
Committee Member(s)
Baik, Hojong
Maerz, Norbert H.
Elgin, Richard L. (Richard Lewis)
Paiva, Joseph
Department(s)
Civil, Architectural and Environmental Engineering
Degree Name
Ph. D. in Civil Engineering
Publisher
Missouri University of Science and Technology
Publication Date
2015
Pagination
xx, 272 pages
Note about bibliography
Includes bibliographic references (pages 266-271).
Rights
© 2015 James Preston Peterson II, All rights reserved.
Document Type
Dissertation - Open Access
File Type
text
Language
English
Subject Headings
Drone aircraftPhotogrammetryGeographic information systemsGeospatial data
Thesis Number
T 10774
Electronic OCLC #
923735422
Recommended Citation
Peterson, James Preston II, "Unmanned aircraft systems image collection and computer vision image processing for surveying and mapping that meets professional needs" (2015). Doctoral Dissertations. 2433.
https://scholarsmine.mst.edu/doctoral_dissertations/2433