Complementing airborne laser bathymetry with UAV-based lidar for capturing alluvial landscapes

Mandlburger, Gottfried; Pfennigbauer, Martin; Riegl, Ursula; Haring, Alexander; Wieser, Martin; Glira, Philipp; Winiwarter, Lukas

doi:10.1117/12.2194779

Cited by 24 publications

(26 citation statements)

References 6 publications

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“…the minimum distance for separating consecutive echoes of a single laser pulse. For more details please refer to Mandlburger et al (2015c). Table 2.…”

Section: Ls Data Acquisitionmentioning

confidence: 99%

ULS LiDAR SUPPORTED ANALYSES OF LASER BEAM PENETRATION FROM DIFFERENT ALS SYSTEMS INTO VEGETATION

Wieser¹,

Hollaus²,

Mandlburger³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This study analyses the underestimation of tree and shrub heights for different airborne laser scanner systems and point cloud distribution within the vegetation column. Reference data was produced by a novel UAV-borne laser scanning (ULS) with a high point density in the complete vegetation column. With its physical parameters (e.g. footprint) and its relative accuracy within the block as stated in Section 2.2 the reference data is supposed to be highly suitable to detect the highest point of the vegetation. An airborne topographic (ALS) and topo-bathymetric (ALB) system were investigated. All data was collected in a period of one month in leaf-off condition, while the dominant tree species in the study area are deciduous trees. By robustly estimating the highest 3d vegetation point of each laser system the underestimation of the vegetation height was examined in respect to the ULS reference data. This resulted in a higher under-estimation of the airborne topographic system with 0.60 m (trees) and 0.55 m (shrubs) than for the topo-bathymetric system 0.30 m (trees) and 0.40 m (shrubs). The degree of the underestimation depends on structural characteristics of the vegetation itself and physical specification of the laser system.

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“…the minimum distance for separating consecutive echoes of a single laser pulse. For more details please refer to Mandlburger et al (2015c). Table 2.…”

Section: Ls Data Acquisitionmentioning

confidence: 99%

ULS LiDAR SUPPORTED ANALYSES OF LASER BEAM PENETRATION FROM DIFFERENT ALS SYSTEMS INTO VEGETATION

Wieser¹,

Hollaus²,

Mandlburger³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Whereas in Mandlburger et al (2015c) it is stated that the water surface can be treated as static within the study reach under moderate discharge conditions (< mean flow) when considering a typical ALB footprint size of 60 cm, this is no longer the case for the small footprints of the laser profiler (3.5 cm @ 15 m altitude) and the ULS system (3 cm @ 60 m altitude). The effect of the rough water surface can clearly be identified in Profile 11 (cf.…”

Section: Accuracy Assessmentmentioning

confidence: 99%

“…Based on the pre-defined waypoints three cross sections were marked off at the river bank and in total 170 check points were measured in the submerged area and at the shoreline using a Leica TPS1200 total station. In addition, areal comparison data from an ALB flight in April 2015 (Mandlburger et al, 2015c) captured from 600 m above ground level with the RIEGL VQ-880-G topo-bathymetric laser scanner mounted on a Diamond DA42 light aircraft were available and served as basis for the quantification of seasonal changes due to fluvial erosion and for estimating the small-scale variability of the riverbed, especially in flow direction.…”

Section: Study Area and Data Acquisitionmentioning

confidence: 99%

Evaluation of a Novel Uav-Borne Topo-Bathymetric Laser Profiler

Mandlburger¹,

Pfennigbauer²,

Wieser³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:We present a novel topo-bathymetric laser profiler. The sensor system (RIEGL BathyCopter) comprises a laser range finder, an Inertial Measurement Unit (IMU), a Global Navigation Satellite System (GNSS) receiver, a control unit, and digital cameras mounted on an octocopter UAV (RiCOPTER). The range finder operates on the time-of-flight measurement principle and utilizes very short laser pulses (<1 ns) in the green domain of the spectrum (λ=532 nm) for measuring distances to both the water surface and the river bottom. For assessing the precision and accuracy of the system an experiment was carried out in October 2015 at a pre-alpine river (Pielach in Lower Austria). A 200 m longitudinal section and 12 river cross sections were measured with the BathyCopter sensor system at a flight altitude of 15-20 m above ground level and a measurement rate of 4 kHz. The 3D laser profiler points were compared with independent, quasi-simultaneous data acquisitions using (i) the RIEGL VUX1-UAV lightweight topographic laser scanning system (bare earth, water surface) and (ii) terrestrial survey (river bed). Over bare earth the laser profiler heights have a std. dev. of 3 cm, the water surface height appears to be underestimated by 5 cm, and river bottom heights differ from the reference measurements by 10 cm with a std. dev. of 13 cm. When restricting the comparison to laser profiler bottom points and reference measurements with a lateral offset below 1 m, the values improve to 4 cm bias with a std. dev. of 6 cm. We report additionally on challenges in comparing UAV-borne to terrestrial profiles. Based on the accuracy and the small footprint (3.5 cm at the water surface) we concluded that the acquired 3D points can potentially serve as input data (river bed geometry, grain roughness) and validation data (water surface, water depth) for hydrodynamic-numerical models.

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“…However, these sensors were still of low performance. The first high performance laser scanner dedicated for UASs is the Riegl UAVX-1UAV (Amon et al, 2015;Mandlburger et al, 2015). In contrast to other UAS scanners, the Riegl UAVX-1UAV is characterized by very long range measurements (up to 920 m).…”

Section: Introductionmentioning

confidence: 99%

UAS TOPOGRAPHIC MAPPING WITH VELODYNE LiDAR SENSOR

Jóźków¹,

Toth²,

Grejner‐Brzezinska³

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission I, ICWG I/VbKEY WORDS: UAS, UAV, LiDAR, mapping, performance analysis ABSTRACT:Unmanned Aerial System (UAS) technology is nowadays willingly used in small area topographic mapping due to low costs and good quality of derived products. Since cameras typically used with UAS have some limitations, e.g. cannot penetrate the vegetation, LiDAR sensors are increasingly getting attention in UAS mapping. Sensor developments reached the point when their costs and size suit the UAS platform, though, LiDAR UAS is still an emerging technology. One issue related to using LiDAR sensors on UAS is the limited performance of the navigation sensors used on UAS platforms. Therefore, various hardware and software solutions are investigated to increase the quality of UAS LiDAR point clouds. This work analyses several aspects of the UAS LiDAR point cloud generation performance based on UAS flights conducted with the Velodyne laser scanner and cameras. The attention was primarily paid to the trajectory reconstruction performance that is essential for accurate point cloud georeferencing. Since the navigation sensors, especially Inertial Measurement Units (IMUs), may not be of sufficient performance, the estimated camera poses could allow to increase the robustness of the estimated trajectory, and subsequently, the accuracy of the point cloud. The accuracy of the final UAS LiDAR point cloud was evaluated on the basis of the generated DSM, including comparison with point clouds obtained from dense image matching. The results showed the need for more investigation on MEMS IMU sensors used for UAS trajectory reconstruction. The accuracy of the UAS LiDAR point cloud, though lower than for point cloud obtained from images, may be still sufficient for certain mapping applications where the optical imagery is not useful.

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Complementing airborne laser bathymetry with UAV-based lidar for capturing alluvial landscapes

Cited by 24 publications

References 6 publications

ULS LiDAR SUPPORTED ANALYSES OF LASER BEAM PENETRATION FROM DIFFERENT ALS SYSTEMS INTO VEGETATION

ULS LiDAR SUPPORTED ANALYSES OF LASER BEAM PENETRATION FROM DIFFERENT ALS SYSTEMS INTO VEGETATION

Evaluation of a Novel Uav-Borne Topo-Bathymetric Laser Profiler

UAS TOPOGRAPHIC MAPPING WITH VELODYNE LiDAR SENSOR

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