To evaluate the effectiveness of the FARO 3D handheld LiDAR unit, I determined when ambient light affected the LiDAR’s detection capability. I then used standard destructive harvest methods combined with LiDAR data to examine the relationship between the number of pixels captured by the LiDAR unit with the log transformed dry biomass of the harvest fuels in both leaf-on and leaf-off conditions. Using a Bayesian regression model with a non-informative prior, the analysis showed a weak relationship between pixels and log biomass in leaf-on conditions with an R2 of 0.22 and a moderately strong relationship between pixels and log biomass in leaf-off conditions with an R2 of 0.67. The results suggest that handheld LiDAR units have the potential to replace destructive harvest methods under certain conditions, but may not serve as a tool for fire managers to utilize as a regular tool for estimate surface fuel loading.
Subject (authority = RUETD)
Topic
Ecology and Evolution
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_8565
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (vi, 43 p. : ill.)
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Three-dimensional imaging
Subject (authority = ETD-LCSH)
Topic
Forest fires--Prevention and control
Note (type = statement of responsibility)
by Joseph Rua
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.