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INDIVIDUAL TREE CROWN DELINEATION USING MULTI-WAVELENGTH TITAN LIDAR DATA

Authors :
F. Naveed
B. Hu
Source :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-3-W3, Pp 143-148 (2017)
Publication Year :
2017
Publisher :
Copernicus Publications, 2017.

Abstract

The inability to detect the Emerald Ash Borer (EAB) at an early stage has led to the enumerable loss of different species of ash trees. Due to the increasing risk being posed by the EAB, a robust and accurate method is needed for identifying Individual Tree Crowns (ITCs) that are at a risk of being infected or are already diseased. This paper attempts to outline an ITC delineation method that employs airborne multi-spectral Light Detection and Ranging (LiDAR) to accurately delineate tree crowns. The raw LiDAR data were initially pre-processed to generate the Digital Surface Models (DSM) and Digital Elevation Models (DEM) using an iterative progressive TIN (Triangulated Irregular Network) densification method. The DSM and DEM were consequently used for Canopy Height Model (CHM) generation, from which the structural information pertaining to the size and shape of the tree crowns was obtained. The structural information along with the spectral information was used to segment ITCs using a region growing algorithm. The availability of the multi-spectral LiDAR data allows for delineation of crowns that have otherwise homogenous structural characteristics and hence cannot be isolated from the CHM alone. This study exploits the spectral data to derive initial approximations of individual tree tops and consequently grow those regions based on the spectral constraints of the individual trees.

Details

Language :
English
ISSN :
16821750 and 21949034
Volume :
XLII-3-W3
Database :
Directory of Open Access Journals
Journal :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.fca41eabceb84af484650c60f8029cc3
Document Type :
article
Full Text :
https://doi.org/10.5194/isprs-archives-XLII-3-W3-143-2017