Assessing the Positioning Accuracy of High density Point Clouds produced from Rotary Wing Quadrocopter Unmanned Aerial System based Imagery

Author(s):  
Yong Chang Lee
2014 ◽  
Vol 6 (6) ◽  
pp. 5407-5427 ◽  
Author(s):  
Álvaro Gómez-Gutiérrez ◽  
José de Sanjosé-Blasco ◽  
Javier de Matías-Bejarano ◽  
Fernando Berenguer-Sempere

2020 ◽  
Author(s):  
Francesca Bearzot ◽  
Roberto Garzonio ◽  
Biagio Di Mauro ◽  
Umberto Morra Di Cella ◽  
Edoardo Cremonese ◽  
...  

<p>The acquisition of high-resolution topographic data is a widely used tool for studies related to the processes and dynamics of the Earth's surface. In this work, we present the results of the repeated acquisition of photogrammetric data by Unmanned Aerial Vehicle (UAV) in order to detect the topographic evolution of an alpine rock glaciers located in Valtournenche (AO, Italy). Field monitoring conducted in recent years has shown significant variations in the behaviour of these landforms, with an increasing trend of their dynamism, raising questions about their stability in changing climatic conditions.</p><p> </p><p>The photogrammetric shots were taken with a DJ Phantom 4 UAV equipped with a compact RGB digital camera. The acquisitions were performed yearly from 2012 up to 2019 with a ground sampling distance never exceeding 5 cm/px. Contemporary to the acquisitions, approximately 20 Ground Control Points were placed on the rock glacier and on the surrounding areas and their coordinates were measured with a differential GPS (dGPS) for georeferencing UAV images. Moreover, in 2014, 2015 and 2019 geophysical campaigns were carried out for the detection of ice lenses under the debris cover of the rock glacier.</p><p> </p><p>Structure-from-motion techniques were applied on overlapping images to create high-density point clouds, than converted in orthophotos and digital surface models of the Earth’s surface.</p><p>The point clouds were analysed using the M3C2 (Multiscale Model to Model Cloud Comparison) plug-in, freely available in the CloudCompare software. Maps of surface changes between acquisition pairs in the period from 2015-2019 have been created. The comparison allowed the identification of "material supply" and "material removal" zones, slightly variable from one year to the next. The major accumulation zones are concentrated along the frontal sector of the rock glacier, more focused on the western sector (black lobe) and secondly on the right side of the rock glacier (white lobe). The removal of material is mainly concentrated on the higher altitude of the body but also in correspondence to the systems of crevasses and scarps and on the central part of the black lobe.</p><p>The surface displacement analysis of the rock glacier was also performed selecting manually several clearly identifiable features on the orthomosaics collected. Blocks and ridges-and-furrows complex were marked on the 2019 orthomosaic and found them on the 2015 orthomosaic. This approach allows improving and quantifying the dynamics of the different portions of the individual apparatus.</p><p>The velocity fields’ patterns highlight non-homogeneous displacements between the West (black lobe) and East part (white lobe) of the whole rock glacier. Specifically, the black lobe showed an average horizontal displacement of around 1 m/y while the white lobe moved significantly slower than the previous one (approximately 0.5 m/y). Overall, the rock glacier moved downslope at an average horizontal velocity of 0.60 m/y in the frontal tongue, 0.48 m/y in the central portion and 0.30 m/y in the upper zone.</p>


2012 ◽  
Vol 3 (5) ◽  
pp. 81 ◽  
Author(s):  
Ana Mª Charquero Ballester ◽  
Jordi A. López Lillo

<p>In this paper a stratigraphic recording methodology is presented after a practial experience at the lo Boligni archaeological site. This experience has allowed, on the basis of cenital stereo-photo pairs, the digitalization of interfacial surfaces through high density point clouds renderization as the excavation went on, in order to obtain a Three-dimmensional Cummulative Model (TCM) of the stratigraphical sequence. It will be exposed the way some easy and affordable digital tools are used at the excavation in order to achieve a massive data recovery, and how their integration in CAD and GIS environments opens new possibilities for the everyday archaeological information treatement.</p>


2010 ◽  
Vol 7 (6) ◽  
pp. 863-874 ◽  
Author(s):  
C. Mehdi-Souzani ◽  
J. Digne ◽  
N. Audfray ◽  
C. Lartigue ◽  
J.-M. Morel

2012 ◽  
Vol 24 (6) ◽  
pp. 1267-1279 ◽  
Author(s):  
Lee J. Wells ◽  
Fadel M. Megahed ◽  
Cory B. Niziolek ◽  
Jaime A. Camelio ◽  
William H. Woodall

2018 ◽  
Vol 39 (15-16) ◽  
pp. 5211-5235 ◽  
Author(s):  
Juan Guerra-Hernández ◽  
Diogo N. Cosenza ◽  
Luiz Carlos Estraviz Rodriguez ◽  
Margarida Silva ◽  
Margarida Tomé ◽  
...  

2021 ◽  
Vol 13 (8) ◽  
pp. 1442
Author(s):  
Kaisen Ma ◽  
Yujiu Xiong ◽  
Fugen Jiang ◽  
Song Chen ◽  
Hua Sun

Detecting and segmenting individual trees in forest ecosystems with high-density and overlapping crowns often results in bias due to the limitations of the commonly used canopy height model (CHM). To address such limitations, this paper proposes a new method to segment individual trees and extract tree structural parameters. The method involves the following key steps: (1) unmanned aerial vehicle (UAV)-scanned, high-density laser point clouds were classified, and a vegetation point cloud density model (VPCDM) was established by analyzing the spatial density distribution of the classified vegetation point cloud in the plane projection; and (2) a local maximum algorithm with an optimal window size was used to detect tree seed points and to extract tree heights, and an improved watershed algorithm was used to extract the tree crowns. The proposed method was tested at three sites with different canopy coverage rates in a pine-dominated forest in northern China. The results showed that (1) the kappa coefficient between the proposed VPCDM and the commonly used CHM was 0.79, indicating that performance of the VPCDM is comparable to that of the CHM; (2) the local maximum algorithm with the optimal window size could be used to segment individual trees and obtain optimal single-tree segmentation accuracy and detection rate results; and (3) compared with the original watershed algorithm, the improved watershed algorithm significantly increased the accuracy of canopy area extraction. In conclusion, the proposed VPCDM may provide an innovative data segmentation model for light detection and ranging (LiDAR)-based high-density point clouds and enhance the accuracy of parameter extraction.


2017 ◽  
Vol 70 (6) ◽  
pp. 1276-1292
Author(s):  
Chong Yu ◽  
Jiyuan Cai ◽  
Qingyu Chen

To achieve more accurate navigation performance in the landing process, a multi-resolution visual positioning technique is proposed for landing assistance of an Unmanned Aerial System (UAS). This technique uses a captured image of an artificial landmark (e.g. barcode) to provide relative positioning information in the X, Y and Z axes, and yaw, roll and pitch orientations. A multi-resolution coding algorithm is designed to ensure the UAS will not lose the detection of the landing target due to limited visual angles or camera resolution. Simulation and real world experiments prove the performance of the proposed technique in positioning accuracy, detection accuracy, and navigation effect. Two types of UAS are used to verify the generalisation of the proposed technique. Comparison experiments to state-of-the-art techniques are also included with the results analysis.


Author(s):  
Matthew B. Creasy ◽  
Wade Travis Tinkham ◽  
Chad M. Hoffman ◽  
Jody C. Vogeler

Characterization of forest structure is important for management-related decision making, monitoring, and adaptive management. Increasingly, observations of forest structure are needed at both finer resolutions and across greater extents to support spatially explicit management planning. Unmanned aerial system (UAS)-based photogrammetry provides an airborne method of forest structure data acquisition at a significantly lower cost and time commitment than existing methods such as airborne laser scanning (LiDAR). This study utilizes nearly 5,000 stem-mapped trees in ponderosa pine-dominated forests to evaluate several algorithms for detecting individual tree locations and characterizing crown area across tree sizes. Our results indicate that adaptive variable-window detection methods with UAS-based canopy height models have greater tree detection rates compared to fixed window analysis across a range of tree sizes. Using the UAS approach, probability of detecting individual trees decreases from 97% for dominant overstory to 67% for suppressed understory trees. Additionally, crown radii were correctly determined within 0.5 m for approximately two-thirds of sampled trees. These findings highlight the potential for UAS photogrammetry to characterize forest structure through the detection of trees and tree groups in open-canopy ponderosa pine forests. Further work should investigate how these methods transfer to more diverse species compositions and forest structures.


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