Development of a UAV-LiDAR System with Application to Forest Inventory

Abstract

We present the development of a low-cost Unmanned Aerial Vehicle-Light Detecting and Ranging (UAV-LiDAR) system and an accompanying workflow to produce 3D point clouds. UAV systems provide an unrivalled combination of high temporal and spatial resolution datasets. The TerraLuma UAV-LiDAR system has been developed to take advantage of these properties and in doing so overcome some of the current limitations of the use of this technology within the forestry industry. A modified processing workflow including a novel trajectory determination algorithm fusing observations from a GPS receiver, an Inertial Measurement Unit (IMU) and a High Definition (HD) video camera is presented. The advantages of this workflow are demonstrated using a rigorous assessment of the spatial accuracy of the final point clouds. It is shown that due to the inclusion of video the horizontal accuracy of the final point cloud improves from 0.61 m to 0.34 m (RMS error assessed against ground control). The effect of the very high density point clouds (up to 62 points per m 2 ) produced by the UAV-LiDAR system on the measurement of tree location, height and crown width are also assessed by performing repeat surveys over individual isolated trees. The standard deviation of tree height is shown to reduce from 0.26 m, when using data with a density of 8 points per m 2 , to 0.15 m when the higher density data was used.Improvements in the uncertainty of the measurement of tree location, 0.80 m to 0.53 m, and crown width, 0.69 m to 0.61 m are also shown.Remote Sens. 2012, 4 1520

Application of Low-Cost Fixed-Wing UAV for Inland Lakes Shoreline Investigation

“…Using UAVs is now widespread across a range of disciplines (Anderson and Gaston 2013;Liu et al 2014;Smith et al 2016). The most popular environmental applications are: landslide monitoring (Lucieer et al 2014a), measuring changes in coastal morphology (Casella et al 2014;Gonçalves and Henriques 2015;Papakonstantinou et al 2016), monitoring glacier movement (Immerzeel et al 2014;Ryan et al 2015), studying Antarctic moss beds (Lucieer et al 2014b), soil erosion monitoring (d'Oleire-Oltmanns et al 2012), fluvial geomorphology (Mori et al 2002;Tamminga et al 2015;Woodget et al 2015) and forest research (Tang and Shao 2015;Wallace et al 2012). These studies are conducted using different UAV platforms delivered by various manufacturers (i.e., hybrid, flapping-wing, fixed-wing, coaxial, duct-fan, single rotor, and multi-rotor).…”

Estimating tree heights with images from an unmanned aerial vehicle

“…There have been several studies on the use of airborne LiDAR platforms in forest areas that show accurate results (Breindenbach et al 2010;Gleason & Im 2012) with the use of Unmanned aerial vehiclesLiDAR (UAV-LiDAR) platforms (Wallace et al 2014a;Wallace et al 2014b) and even with spaceborne LiDAR platforms (Selkowitz et al 2012). However, short flight sessions and the high cost of these surveys with experienced personnel prevent continuous studies (Wallace et al 2012;Zarco-Tejada et al 2014). There have also been studies with the satellite images (Gougeon & Lecke 2006;Takahashi et al 2012) based on forest structure and the spatial resolution of the satellite images; the results are less precise but useful for large areas.…”

An overview of existing and promising technologies for national forest monitoring

“…The analysis of such three-dimensional large datasets is still in progress, but several ongoing methodological developments should make this technology useful soon. For instance, the use of mobile laser scanning, such as personal laser scanning systems (Bauwens et al 2014;Liang et al 2014) or unmanned aerial vehicle-LiDAR systems (Wallace et al 2012;Chisholm et al 2013) is a promising easy-to-use way to survey forests and has the potential to constitute an intermediate approach between "classical" terrestrial LiDAR approaches and airborne LiDAR systems.…”