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• W1417025892 abstract "Airborne Laser scanning (ALS) has emerged as an important tool for providing costeffectivecharacterisation of the 3D structure of forests over large areas. As data resolutionis often inversely proportional to coverage area, laser scanning from alternative platformshas been a recent subject of investigation. This thesis advances this exploration byinvestigating the use of Unmanned Aerial Vehicles (UAVs) as a laser scanning platform(UAVLS) for forest inventory purposes. The design of a small laser scanning systemconsisting of an automotive laser scanner, a Micro-Electro-Mechanical Systems basedInertial Measurement Unit (IMU), a dual frequency Global Positioning System (GPS)receiver and a downward pointing video camera for use on-board an Oktokopter multirotorplatform is described. A novel algorithm was developed for the direct georeferencingof laser returns utilising a vision aided GPS-IMU sigma-point Kalman smoother.Evaluating improvements due to the inclusion of vision, both stochastically and in practice,it is demonstrated that an accuracy similar to modern ALS systems and adequatefor forest inventory measurements can be achieved (34 cm horizontal, 14 cm verticalRMSE).Two 4 year old Eucalyptus plantations in south east Tasmania were selected as theprimary study area in order to assess the utility of the UAVLS system to map andassess change in key inventory metrics. Analysis of the point clouds captured withdifferent flying parameters indicated that the flying height should be restricted to lessthan 50 m above ground level and scan angle restricted to ±30. A survey method withinthese restraints and utilising overlapping transects was designed to provide cost-effectiveand repeatable observations of the 3D structure of the plot sized areas (500 m2). It wasfound that the maximum deviations of plot level descriptive statistics captured in repeatmultiple flights were less than 3%.Investigating the accuracy and repeatability of individual tree level metrics derived fromthe high density UAVLS point clouds (up to 300 points/m2) using five different automatictree detection and delineation methods highlighted that increased data resolutionprovided more detail in the characterisation of individual trees. The best performingmethod, which utilised both the CHM and the point cloud, resulted in 98% of trees beingrepeatedly and correctly delineated from the point cloud. Tree height (absolute meandeviation of 0.35 m), location (0.48 m), crown area (3.3 m2) and canopy closure (2.3%)extracted from the delineated tree segments were observed with higher repeatability andbetter efficiency than that currently achieved using modern field techniques. Subsequent analysis of change following the application of sequential silvicultural treatments showedthat UAVLS is capable of detecting pruning rates of between 96 and 125% of the truepruning rate.This thesis demonstrates that UAVLS offers unprecedented temporal and spatial resolution,enabling the determination of highly accurate forest inventory metrics and theirchange over time. In comparison with in situ field techniques, UAVLS offers more efficientand detailed characterisation of the 3D structure of forests." @default.
• W1417025892 created "2016-06-24" @default.
• W1417025892 creator A5084859688 @default.
• W1417025892 date "2014-08-01" @default.
• W1417025892 modified "2023-09-26" @default.
• W1417025892 title "Development and application of a unmanned aerial vehicle laser scanning system for forest management" @default.
• W1417025892 hasPublicationYear "2014" @default.
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