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Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review
Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review
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TY - CONF
T1 - Investigating the structural condition of trees using LiDAR metrics
AU - Murray, Jon
AU - Blackburn, Alan
AU - Whyatt, Duncan
AU - Edwards, Christopher
PY - 2014/4/18
Y1 - 2014/4/18
N2 - Unlike other investigations that use discrete return (DR) light detection and ranging (LiDAR) data for the visualisation and investigation of physical structure, this research attempts to investigate data relationships found within the LiDAR point cloud in order to infer the condition of the subject of interest, which for the purposes of this investigation are tree canopies. During DR LiDAR data capture, a laser pulse is emitted from the scanner and information about the subject is captured at only at specific points known as laser returns (r). Subsequently, not all of the laser waveform is recorded, meaning that although a general impression of the subject is captured in a point cloud, there will be areas of the subject between each data point that remain unrepresented in the dataset. This paper outlines preliminary research into attempting to discover what range of LiDAR metrics, and resulting data relationships, are the most suitable to identify the significance of the structural condition of tree canopies from a tree health perspective. This research contributes to a wider investigation of automated tree health assessment and the early identification of structural failure in trees using remote sensing techniques
AB - Unlike other investigations that use discrete return (DR) light detection and ranging (LiDAR) data for the visualisation and investigation of physical structure, this research attempts to investigate data relationships found within the LiDAR point cloud in order to infer the condition of the subject of interest, which for the purposes of this investigation are tree canopies. During DR LiDAR data capture, a laser pulse is emitted from the scanner and information about the subject is captured at only at specific points known as laser returns (r). Subsequently, not all of the laser waveform is recorded, meaning that although a general impression of the subject is captured in a point cloud, there will be areas of the subject between each data point that remain unrepresented in the dataset. This paper outlines preliminary research into attempting to discover what range of LiDAR metrics, and resulting data relationships, are the most suitable to identify the significance of the structural condition of tree canopies from a tree health perspective. This research contributes to a wider investigation of automated tree health assessment and the early identification of structural failure in trees using remote sensing techniques
M3 - Conference paper
T2 - 22nd GISRUK conference, 16-18th April, 2014
Y2 - 16 April 2014 through 18 April 2014
ER -