Accuracy evaluation of digital terrain model based on different flying altitudes and conditional of terrain using UAV LiDAR technology

Fuad, N. Ahmad; Ismail, Zamri; Majid, Zulkepli; Darwin, Norhadija; Ariff, Mohd Farid Mohd; Idris, Khairulnizam M.; Yusoff, Ahmad Razali

doi:10.1088/1755-1315/169/1/012100

Cited by 18 publications

(9 citation statements)

References 11 publications

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“…Incorrect filtering of the point cloud may remove too many terrain points and/or leave non-terrain points, leading to inaccurate Z estimates. Nevertheless, the obtained RMSE of 15 cm is similar to that obtained in Reference [22] and better than that estimated in Reference [23]. If strip adjustment were executed with ground control points, this figure would be reduced, as stated in Reference [17], where it was shown that altimetric accuracy was reduced from 10 to 4 cm (in an area of 0.02 km 2 , nine ground control points were used).…”

Section: Resultssupporting

confidence: 78%

Quality Control of Outsourced LiDAR Data Acquired with a UAV: A Case Study

et al. 2021

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Over the last few decades, we witnessed a revolution in acquiring very high resolution and accurate geo-information. One of the reasons was the advances in photonics and LiDAR, which had a remarkable impact in applications requiring information with high accuracy and/or elevated completeness, such as flood modelling, forestry, construction, and mining. Also, miniaturization within electronics played an important role as it allowed smaller and lighter aerial cameras and LiDAR systems to be carried by unmanned aerial vehicles (UAV). While the use of aerial imagery acquired with UAV is becoming a standard procedure in geo-information extraction for several applications, the use of LiDAR for this purpose is still in its infancy. In several countries, companies have started to commercialize products derived from LiDAR data acquired using a UAV but not always with the necessary expertise and experience. The LIDAR-derived products’ price has become very attractive, but their quality must meet the contracted specifications. Few studies have reported on the quality of outsourced LiDAR data acquired with UAV and the problems that need to be handled during production. There can be significant differences between the planning and execution of a commercial project and a research field campaign, particularly concerning the size of the surveyed area, the volume of the acquired data, and the strip processing. This work addresses the quality control of LiDAR UAV data through outsourcing to develop a modelling-based flood forecast and alert system. The contracted company used the Phoenix Scout-16 from Phoenix LiDAR Systems, carrying a Velodyne VLP-16 and mounted on a DJI Matrice 600 PRO Hexacopter for an area of 560 ha along a flood-prone area of the Águeda River in Central Portugal.

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Section: Resultssupporting

confidence: 78%

Quality Control of Outsourced LiDAR Data Acquired with a UAV: A Case Study

et al. 2021

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“…Potential parameters are typically estimated from objects with a defined geometric shape. Fuad et al [32] for example analyzed the accuracy of estimated DEM models with different flight parameters. Furthermore, several studies investigated the quality for the calculation of forest structural attributes (e.g., stem diameter, volume) in forestry [33][34][35].…”

Section: Related Workmentioning

confidence: 99%

Quality Analysis of Direct Georeferencing in Aspects of Absolute Accuracy and Precision for a UAV-Based Laser Scanning System

et al. 2021

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The use of UAV-based laser scanning systems is increasing due to the rapid development in sensor technology, especially in applications such as topographic surveys or forestry. One advantage of these multi-sensor systems is the possibility of direct georeferencing of the derived 3D point clouds in a global reference frame without additional information from Ground Control Points (GCPs). This paper addresses the quality analysis of direct georeferencing of a UAV-based laser scanning system focusing on the absolute accuracy and precision of the system. The system investigated is based on the RIEGL miniVUX-SYS and the evaluation uses the estimated point clouds compared to a reference point cloud from Terrestrial Laser Scanning (TLS) for two different study areas. The precision is estimated by multiple repetitions of the same measurement and the use of artificial objects, such as targets and tables, resulting in a standard deviation of <1.2 cm for the horizontal and vertical directions. The absolute accuracy is determined using a point-based evaluation, which results in the RMSE being <2 cm for the horizontal direction and <4 cm for the vertical direction, compared to the TLS reference. The results are consistent for the two different study areas with similar evaluation approaches but different flight planning and processing. In addition, the influence of different Global Navigation Satellite System (GNSS) master stations is investigated and no significant difference was found between Virtual Reference Stations (VRS) and a dedicated master station. Furthermore, to control the orientation of the point cloud, a parameter-based analysis using planes in object space was performed, which showed a good agreement with the reference within the noise level of the point cloud. The calculated quality parameters are all smaller than the manufacturer’s specifications and can be transferred to other multi-sensor systems.

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“…UAV equipped with a laser sensor has become popular for its capability of real time 3D data capture [ 33 ]. In this study, UAV LIDAR data is used for producing validation data layers and deriving Ground Control Points (GCPs) for UAV images registration and Check Points (CPs) for accuracy assessment of radiometric transformation processes.…”

Section: Methodsmentioning

confidence: 99%

Assessment of DSM Based on Radiometric Transformation of UAV Data

Chaudhry

Ahmad

Gulzar

et al. 2021

Sensors

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Unmanned Aerial Vehicle (UAV) is one of the latest technologies for high spatial resolution 3D modeling of the Earth. The objectives of this study are to assess low-cost UAV data using image radiometric transformation techniques and investigate its effects on global and local accuracy of the Digital Surface Model (DSM). This research uses UAV Light Detection and Ranging (LIDAR) data from 80 meters and UAV Drone data from 300 and 500 meters flying height. RAW UAV images acquired from 500 meters flying height are radiometrically transformed in Matrix Laboratory (MATLAB). UAV images from 300 meters flying height are processed for the generation of 3D point cloud and DSM in Pix4D Mapper. UAV LIDAR data are used for the acquisition of Ground Control Points (GCP) and accuracy assessment of UAV Image data products. Accuracy of enhanced DSM with DSM generated from 300 meters flight height were analyzed for point cloud number, density and distribution. Root Mean Square Error (RMSE) value of Z is enhanced from ±2.15 meters to 0.11 meters. For local accuracy assessment of DSM, four different types of land covers are statistically compared with UAV LIDAR resulting in compatibility of enhancement technique with UAV LIDAR accuracy.

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Accuracy evaluation of digital terrain model based on different flying altitudes and conditional of terrain using UAV LiDAR technology

Cited by 18 publications

References 11 publications

Quality Control of Outsourced LiDAR Data Acquired with a UAV: A Case Study

Quality Control of Outsourced LiDAR Data Acquired with a UAV: A Case Study

Quality Analysis of Direct Georeferencing in Aspects of Absolute Accuracy and Precision for a UAV-Based Laser Scanning System

Assessment of DSM Based on Radiometric Transformation of UAV Data

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