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CATEGORIES:Lecture or Presentation
DESCRIPTION:“A Multivariate Comparison of Drone-Based Structure from Motion
  and Drone-Based Lidar for Dense Topographic Mapping Applications.” \n\nMaj
 or advisor: Christopher Parrish\, associate professor of geomatics. Committ
 ee members: Michael Olsen\, associate professor of geomatics\; Daniel Gilli
 ns\, National Geodetic Survey\; Michael Wing\, associate professor of geoma
 tics\, Forestry Engineering (GCR). \n\nOpen to the public.\n\nAbstract: Unm
 anned aircraft systems (UAS)\, also known as drones\, are becoming an incre
 asingly popular method of collecting surveying and mapping data. Two common
  drone-based mapping techniques are lidar and structure from motion (SfM) p
 hotogrammetry. Surveyors and mapping professionals currently need informati
 on on how these two techniques compare. The most common metric for comparis
 on is spatial accuracy\, but the two techniques also vary in other key aspe
 cts\, such as cost\, complexity\, learning curve\, payload requirements\, a
 cquisition and processing speeds\, and abilities to map under canopy or in 
 vegetation. While there is no “one-size-fits-all” technology or technique\,
  comparisons of drone-based lidar and SfM photogrammetry along all of these
  different dimensions and in different settings can help surveyors and mapp
 ers make informed decisions in purchasing and operating UAS-based systems. 
 This study makes these comparisons using data acquired with two remote airc
 raft at a project site with a robust control network and high-accuracy refe
 rence data located in Stevenson\, Washington. The results shed light on the
  relative strengths and weaknesses of UAS-SfM and UAS-lidar. Since the two 
 techniques typically provide comparable data accuracies (with some differen
 ces\, as a function of terrain\, ground cover type and surface texture)\, y
 et UAS-SfM is generally less expensive\, imposes less stringent requirement
 s for the remote aircraft\, requires less expert knowledge and training\, a
 nd yields higher data densities\, an overarching recommendation from this r
 esearch is that UAS-SfM be considered the default technique for many mappin
 g projects. However\, there are a number of specific scenarios in which UAS
 -lidar is preferable to UAS-SfM\, and it is critical to understand these ca
 ses. Additionally\, while the combination of UAS-SfM and UAS-lidar would ty
 pically be unnecessarily expensive and complex for most projects\, the syne
 rgistic use of both techniques could provide an optimal solution for the mo
 st demanding projects.
DTEND:20181114T180000Z
DTSTAMP:20260412T193116Z
DTSTART:20181114T170000Z
GEO:44.567052;-123.273254
LOCATION:Kearney Hall\, 311
SEQUENCE:0
SUMMARY:MS Thesis Defense – Chase Simpson
UID:tag:localist.com\,2008:EventInstance_4064258
URL:https://events.oregonstate.edu/event/ms_thesis_defense_chase_simpson
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