Keywords and Phrases
Drone; Geospatial; Mapping; Surveying; Unmanned Aerial Vehicles; Unmanned Aircraft Systems
"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.
Burken, Joel G. (Joel Gerard)
Maerz, Norbert H.
Elgin, Richard L. (Richard Lewis)
Civil, Architectural and Environmental Engineering
Ph. D. in Civil Engineering
Missouri University of Science and Technology
xx, 272 pages
© 2015 James Preston Peterson II, All rights reserved.
Dissertation - Open Access
Library of Congress Subject Headings
Geographic information systems
Electronic OCLC #
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.