Assessing the stability of canopy maps produced from UAV-LiDAR data

The use of Unmanned Aerial Vehicles (UAVs) as a remote sensing platform offers a unique combination of high resolution data collected within relatively low cost targeted missions. This paper investigates the use of UAV-borne Light Detecting and Ranging (LIDAR) systems (UAVL) as a platform to gain kn...

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Bibliographic Details
Published in2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS pp. 3879 - 3882
Main Author Wallace, Luke
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2013
Subjects
Canopy Cover
Forestry
Indexes
Laser radar
Laser stability
LiDAR
Measurement
Remote sensing
Shape
Unmanned aerial vehicles
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Summary:The use of Unmanned Aerial Vehicles (UAVs) as a remote sensing platform offers a unique combination of high resolution data collected within relatively low cost targeted missions. This paper investigates the use of UAV-borne Light Detecting and Ranging (LIDAR) systems (UAVL) as a platform to gain knowledge of the canopy structure within forested environments. Repeat datasets were collected with a UAVL system over six Eucalyptus Globulus plots with varying levels of canopy cover. The relative stability of four metrics for estimating canopy structure, First Cover Index (FCI), Last Cover Index (LCI), a Grid based method (GCI) and an Alpha shape based method (ACI) were assessed using these repeat datasets. It is shown that the repeatability of the GCI metric is subject to variations in plot level point density (standard deviation of 4.06 %). Instabilities in the FCI (1.91 %) and LCI (2.28 %) metrics were found to be related to the properties of the sensor and the lasers interaction with the canopy. The ACI metric (1.86 %) was found to be the most stable.
ISSN:2153-6996
DOI:10.1109/IGARSS.2013.6723679