scholarly journals Accuracy assessment of open - pit mine’s digital surface models generated using photos captured by Unmanned Aerial Vehicles in the post - processing kinematic mode

2021 ◽  
Vol 62 (4) ◽  
pp. 38-47
Author(s):  
Long Quoc Nguyen ◽  
Keyword(s):  
Accuracy Assessment ◽  
Open Pit ◽  
Ground Control ◽  
Surface Model ◽  
Control Points ◽  
Post Processing ◽  
Ground Control Points ◽  
Satellite Positioning ◽  
Surface Models ◽  
Aerial Vehicle

To evaluate the accuracy of the digital surface model (DSM) of an open-pit mine produced using photos captured by the unmanned aerial vehicle equipped with the post-processing dynamic satellite positioning technology (UAV/PPK), a DSM model of the Deo Nai open-pit coal mine was built in two cases: (1) only using images taken from UAV/PPK and (2) using images taken from UAV/PPK and ground control points (GCPs). These DSMs are evaluated in two ways: using checkpoints (CPs) and comparing the entire generated DSM with the DSM established by the electronic total station. The obtained results show that if using CPs, in case 1, the errors in horizontal and vertical dimension were 6.8 and 34.3 cm, respectively. When using two or more GCPs (case 2), the horizontal and vertical errors are at the centimetre-level (4.5 cm and 4.7 cm); if using the DSM comparison, the same accuracy as case 2 was also obtained.

scholarly journals UAV Photogrammetry Accuracy Assessment for Corridor Mapping Based on the Number and Distribution of Ground Control Points

2020 ◽  
Vol 12 (15) ◽  
pp. 2447 ◽  
Author(s):  
Ezequiel Ferrer-González ◽  
Francisco Agüera-Vega ◽  
Fernando Carvajal-Ramírez ◽  
Patricio Martínez-Carricondo
Keyword(s):  
Accuracy Assessment ◽  
Multiscale Model ◽  
Bundle Adjustment ◽  
Ground Control ◽  
Control Points ◽  
The Road ◽  
Ground Control Points ◽  
Surface Models ◽  
Aerial Vehicle ◽  
Model Cloud

Unmanned aerial vehicle (UAV) photogrammetry has recently emerged as a popular solution to obtain certain products necessary in linear projects, such as orthoimages or digital surface models. This is mainly due to its ability to provide these topographic products in a fast and economical way. In order to guarantee a certain degree of accuracy, it is important to know how many ground control points (GCPs) are necessary and how to distribute them across the study site. The purpose of this work consists of determining the number of GCPs and how to distribute them in a way that yields higher accuracy for a corridor-shaped study area. To do so, several photogrammetric projects have been carried out in which the number of GCPs used in the bundle adjustment and their distribution vary. The different projects were assessed taking into account two different parameters: the root mean square error (RMSE) and the Multiscale Model to Model Cloud Comparison (M3C2). From the different configurations tested, the projects using 9 and 11 GCPs (4.3 and 5.2 GCPs km−1, respectively) distributed alternatively on both sides of the road in an offset or zigzagging pattern, with a pair of GCPs at each end of the road, yielded optimal results regarding fieldwork cost, compared to projects using similar or more GCPs placed according to other distributions.

scholarly journals Accuracy of DSM By Using Unmanned Aerial Vehicles on the Downstream of Welang Riverbank, District of Pasuruan, Jawa Timur

UKaRsT ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 49
Author(s):  
Dian Wahyu Khaulan ◽  
Entin Hidayah ◽  
Gusfan Halik
Keyword(s):  
High Resolution ◽  
Vertical Direction ◽  
Sufficient Accuracy ◽  
Ground Control ◽  
Surface Model ◽  
Control Points ◽  
Digital Surface Model ◽  
Ground Control Points ◽  
Aerial Vehicle ◽  
Topography Data

The Digital Surface Model (DSM) is commonly used in studies on flood map modeling. The lack of accurate, high-resolution topography data has hindered flood modeling. The use of the Unmanned Aerial Vehicle (UAV) can help data acquisition with sufficient accuracy. This research aims to provide high-resolution DSM-generated maps by Ground Control Points (GCPs) settings. Improvement of the model's accuracy was pursued by distributing 20 GCPs along the edges of the study area. Agrisoft software was used to generate the DSM. The generated DSM can be used for various planning purposes. The model's accuracy is measured in Root Mean Square Error (RMSE) based on the generated DSM. The RMSE values are 0.488 m for x-coordinates and y-coordinates (horizontal direction) and 0.161 m for z-coordinates (vertical direction).

scholarly journals The Evaluation of GPS techniques for UAV-based Photogrammetry in Urban Area

2016 ◽  
Vol XLI-B1 ◽  
pp. 1079-1084 ◽  
Author(s):  
M. L. Yeh ◽  
Y. T. Chou ◽  
L. S. Yang
Keyword(s):  
Land Use ◽  
Unmanned Aerial Vehicle ◽  
Three Dimensional ◽  
High Mobility ◽  
Urban Land Use ◽  
Ground Control ◽  
Surface Model ◽  
Control Points ◽  
Ground Control Points ◽  
Aerial Vehicle

The efficiency and high mobility of Unmanned Aerial Vehicle (UAV) made them essential to aerial photography assisted survey and mapping. Especially for urban land use and land cover, that they often changes, and need UAVs to obtain new terrain data and the new changes of land use. This study aims to collect image data and three dimensional ground control points in Taichung city area with Unmanned Aerial Vehicle (UAV), general camera and Real-Time Kinematic with positioning accuracy down to centimetre. The study area is an ecological park that has a low topography which support the city as a detention basin. A digital surface model was also built with Agisoft PhotoScan, and there will also be a high resolution orthophotos. There will be two conditions for this study, with or without ground control points and both were discussed and compared for the accuracy level of each of the digital surface models. According to check point deviation estimate, the model without ground control points has an average two-dimension error up to 40 centimeter, altitude error within one meter. The GCP-free RTK-airborne approach produces centimeter-level accuracy with excellent to low risk to the UAS operators. As in the case of the model with ground control points, the accuracy of x, y, z coordinates has gone up 54.62%, 49.07%, and 87.74%, and the accuracy of altitude has improved the most.

scholarly journals Improving the Accuracy of Aerial Photography Using Ground Control Points

2021 ◽  
Vol 15 (4) ◽  
pp. 42-47
Author(s):  
R. K. Kurbanov ◽  
N. I. Zakharova ◽  
D. M. Gorshkov
Keyword(s):  
Data Processing ◽  
Unmanned Aerial Vehicle ◽  
High Precision ◽  
Aerial Photography ◽  
Ground Control ◽  
Control Points ◽  
Post Processing ◽  
Standard Data ◽  
Ground Control Points ◽  
Aerial Vehicle

The authors showed that it is possible to quickly collect up-to-date information on the agricultural land condition using an unmanned aerial vehicle. It was noted that the use of ground control points increases the accuracy of project measurements, helps to compare the project post-processing results with the real measurements. (Research purpose) To compare the results of standard and high-precision post-processing of aerial survey data using ground control points. (Materials and methods) Aerial photography was carried out on a 1.1- hectare breeding field. The authors used DJI Matrice 200 v2 unmanned aerial vehicle with a GNSS L1/L2 receiver and a modified DJI X4S camera, five control points sized 50 × 50 centimeters and an EMLID Reach RS2 multi-frequency GNSS receiver. The results of scientific research into the use of ground control points during aerial photography were studied. (Results and discussion) It was found out that the error of georeferencing images obtained by an unmanned aerial vehicle without control points is significantly higher during the standard data processing compared to the high-precision one. The project error when using five control points is 3.9 times higher during the standard data processing. (Conclusions) It was shown that using ground control points it is possible to improve the project measurement accuracy, as well as compare the project post-processing results with the measurements on the ground. It was detected that the high-precision monitoring enables the use of fewer ground control points. It was found out that in order to obtain data with the accuracy of 2-4 centimeters in plan and height, at least 3 ground control points need to be used during the high-precision post-processing.

scholarly journals The Evaluation of GPS techniques for UAV-based Photogrammetry in Urban Area

2016 ◽  
Vol XLI-B1 ◽  
pp. 1079-1084
Author(s):  
M. L. Yeh ◽  
Y. T. Chou ◽  
L. S. Yang
Keyword(s):  
Land Use ◽  
Unmanned Aerial Vehicle ◽  
Three Dimensional ◽  
High Mobility ◽  
Urban Land Use ◽  
Ground Control ◽  
Surface Model ◽  
Control Points ◽  
Ground Control Points ◽  
Aerial Vehicle

The efficiency and high mobility of Unmanned Aerial Vehicle (UAV) made them essential to aerial photography assisted survey and mapping. Especially for urban land use and land cover, that they often changes, and need UAVs to obtain new terrain data and the new changes of land use. This study aims to collect image data and three dimensional ground control points in Taichung city area with Unmanned Aerial Vehicle (UAV), general camera and Real-Time Kinematic with positioning accuracy down to centimetre. The study area is an ecological park that has a low topography which support the city as a detention basin. A digital surface model was also built with Agisoft PhotoScan, and there will also be a high resolution orthophotos. There will be two conditions for this study, with or without ground control points and both were discussed and compared for the accuracy level of each of the digital surface models. According to check point deviation estimate, the model without ground control points has an average two-dimension error up to 40 centimeter, altitude error within one meter. The GCP-free RTK-airborne approach produces centimeter-level accuracy with excellent to low risk to the UAS operators. As in the case of the model with ground control points, the accuracy of x, y, z coordinates has gone up 54.62%, 49.07%, and 87.74%, and the accuracy of altitude has improved the most.

scholarly journals UAV PHOTOGRAMMETRY-BASED FOR OPEN PIT COAL MINE LARGE SCALE MAPPING, CASE STUDIES IN CAM PHA CITY, VIETNAM

2020 ◽  
Vol 12 (4) ◽  
pp. 501-509
Author(s):  
Nguyen Long ◽  
◽  
Le Thi Thu Ha ◽  
Tong Si Son ◽  
Kim Thi Thu Huong ◽  
...  
Keyword(s):  
Large Scale ◽  
Coal Mines ◽  
Open Pit ◽  
Ground Control ◽  
Surface Model ◽  
Control Points ◽  
Aerial Photogrammetry ◽  
Ground Control Points ◽  
Active Coal ◽  
Uav Images

The use of lightweight Unmanned Aerial Vehicle with the aerial photogrammetry approach to construct the Digital Surface Model (DSM) has been effectively applied for various types of topography. However, the ability to carry out this approach for huge active open coal mines is insufficiently investigated, furthermore, the influences of topographical factors on the accuracy of DSM are ambiguous. This experiment attempts to apply the UAV method for the two active coal mines with the total area of 7.99 km2 , exploited at a range from -300 m to 300 m altitude to figure out the effect of topographic factors on the accuracy of DEM constructed from UAV images. A total of 972 UAV images and 17 ground control points have been coupled to construct DSM of the mines. Besides, 16 checking points located at different elevations are used to evaluate the accuracy of DEM and to define the influence. DEMs are generated with the maximum RMSE of 0.086 m, 0.099 m, and 0.170 m corresponding to X, Y, and Z dimensional errors. The results show the unclear correlation between the vertical accuracy of DEM and the relative elevation (R2=0.064), the general slope of the mines, and the number of ground control points using in the coal mines as well.

scholarly journals Experimental Investigation on the Performance of DJI Phantom 4 RTK in the PPK Mode for 3D Mapping Open-Pit Mines

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Le VAN CANH ◽  
Cao XUAN CUONG ◽  
Nguyen QUOC LONG ◽  
Le THI THU HA ◽  
Tran TRUNG ANH ◽  
...  
Keyword(s):  
Coal Mines ◽  
Daily Basis ◽  
Open Pit ◽  
Surface Model ◽  
Test Field ◽  
Open Pit Mines ◽  
Ground Control Points ◽  
Aerial Vehicle ◽  
Topographic Surveys

Open-pit coal mines’ terrain is often complex and quickly and frequently changes. Therefore, topographic surveys of open-pit mines are undertaken on a daily basis. While these tasks are very time-consuming and costly with traditional methods such as total station and GNSS, the unmanned aerial vehicle (UAV) based method can be more efficient. This method is a combination of the “Structure from motion” (SfM) photogrammetry technique and UAV photogrammetry which has been widely used in topographic surveying. With an increasing popularity of RTK-enabled drones, it is becoming even more powerful method. While the important role of ground control points (GCP) in the accuracy of digital surface model (DSM) generated from images acquired by “traditional” UAVs (not RTK-enabled drones) has been proved in many previous studies, it is not clear in the case of RTK-enabled drones, especially for complex terrain in open-pit coal mines. In this study, we experimentally investigated the influence of GCP regarding its numbers and distribution on the accuracy of DSM generation from images acquired by RTK-enabled drones in open-pit coal mines. In addition, the Post Processing Kinematic (PPK) mode was executed over a test field with the same flight altitude. DSM generation was performed with several block control configurations: PPK only, PPK with one GCP, and PPK with two GCPs. Several positions of GCPs were also examined to test the optimal locations for placing GCPs to achieve accurate DSMs. The results show that the horizontal and vertical accuracy given by PPK only were 9.3 and 84.4 cm, respectively. However, when adding at least one GCP, the accuracy was significantly improved in both horizontal and vertical components, with RMSE for XY and Z ranging between 3.8 and 9.8 cm (with one GCP) and between 3.0 and 5.7 cm (with two GCPs), respectively. Also, the GCPs placed in the deep areas of the open-pit mine could ensure the cm-level accuracy.

scholarly journals Geometric Accuracy Study of Orthorectification Based on Sensor Model Refinement in Imagery Subset Using ORFEO Toolbox (OTB)

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Andri Suprayogi ◽  
Nurhadi Bashit
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Ground Control ◽  
Surface Model ◽  
Control Points ◽  
Geometric Accuracy ◽  
Model Refinement ◽  
Full Extent ◽  
Sensor Model ◽  
Ground Control Points

Large scale base map can be obtained by various methods, one of them is orthorectification process of remote sensing satellite imagery to eliminate the relief displacement caused by height variation of earth surface. To obtain a  map images with good quality,  it requires additional data such as sensor model in the form of rational polynomial coefficients (RPC), surface model data, and ground control points Satellite imageries with high resolution  file size are relatively large.  In order to process them,  high specification of hardwares were required. To overcome this by cutting only a portion of the images, based on certain study areas were suffer from of georeference lost so it would not be able to orthorectified. On the other hand,  in several remote sensing software such as ESA SNAP and Orfeo Toolbox (OTB)  subset or pixel extraction from satellite imagery,  preserve the imagery geometric sensor models. This research aimed at geometric accuracy of orthorectification carried out in a single scene of Pleiades Imagery within the Kepahiang Subdistrict, located at Kepahiang Regency, Bengkulu Province, by using DEMNAS and the imagery refined sensor mode, and ground control points taken using GPS Survey. Related with the raw imagery condition which consists of Panchromatic and multispectral bands, this study were separated to assembly, pan sharpening , and sensor model refinement stages prior to orthorectification carried out both in the original or full extent imagery and the result of subset extent imagery. After  these processses taken place, we measure the accuracy of each full and subset imagery.These procedures were carried out using Orfeo toolbox 6.6.0 in the Linux Mint 19 Operating system. From the process log, running time in total  were 7814.518  second for the full extent and 4321.95 seconds for the subset processess. And as a big data process, the total of full extent imageries was 83.15 GB  while the subset size  was  only 30.73 GB.  The relative accuracy of the full extent and its subset imagery were 0.431 meters. Accuracy of the  sensor model refinement process are  1.217 meters and 1.550 meters with GCP added, while the accuracu of  the orthorectifications results were  0.416 meters and 0.751 meters by using ICP.  Variation of execution time may caused by the data input size and complexity of the mathematical process carried out in each stages. Meanwhile,  the variation of accuracy may  caused by the check or control points placements above satellite Imagery which suffer from uncertainty when dealing with  the sub-pixel position or under 0.5 meters.

scholarly journals A METHOD FOR SIMULTANEOUS AERIAL AND TERRESTRIAL GEODATA ACQUISITION FOR CORRIDOR MAPPING

2015 ◽  
Vol XL-1/W4 ◽  
pp. 227-232 ◽  
Author(s):  
P. Molina ◽  
M. Blázquez ◽  
J. Sastre ◽  
I. Colomina
Keyword(s):  
Spatial Configuration ◽  
Critical Role ◽  
Control Point ◽  
Unmanned Aircraft ◽  
Ground Control ◽  
Control Points ◽  
Post Processing ◽  
Simultaneous Operation ◽  
Ground Control Points ◽  
Sensor Orientation

In this paper, we present mapKITE, a new mobile, simultaneous terrestrial and aerial, geodata collection and post-processing method. On one side, the method combines a terrestrial mobile mapping system (TMMS) with an unmanned aerial mapping one, both equipped with remote sensing payloads (at least, a nadir-looking visible-band camera in the UA) by means of which aerial and terrestrial geodata are acquired simultaneously. This tandem geodata acquisition system is based on a terrestrial vehicle (TV) and on an unmanned aircraft (UA) linked by a 'virtual tether', that is, a mechanism based on the real-time supply of UA waypoints by the TV. By means of the TV-to-UA tether, the UA follows the TV keeping a specific relative TV-to-UA spatial configuration enabling the simultaneous operation of both systems to obtain highly redundant and complementary geodata. <br><br> On the other side, mapKITE presents a novel concept for geodata post-processing favoured by the rich geometrical aspects derived from the mapKITE tandem simultaneous operation. The approach followed for sensor orientation and calibration of the aerial images captured by the UA inherits the principles of Integrated Sensor Orientation (ISO) and adds the pointing-and-scaling photogrammetric measurement of a distinctive element observed in every UA image, which is a coded target mounted on the roof of the TV. By means of the TV navigation system, the orientation of the TV coded target is performed and used in the post-processing UA image orientation approach as a Kinematic Ground Control Point (KGCP). The geometric strength of a mapKITE ISO network is therefore high as it counts with the traditional tie point image measurements, static ground control points, kinematic aerial control and the new point-and-scale measurements of the KGCPs. With such a geometry, reliable system and sensor orientation and calibration and eventual further reduction of the number of traditional ground control points is feasible. <br><br> The different technical concepts, challenges and breakthroughs behind mapKITE are presented in this paper, such as the TV-to-UA virtual tether and the use of KGCP measurements for UA sensor orientation. In addition, the use in mapKITE of new European GNSS signals such as the Galileo E5 AltBOC is discussed. Because of the critical role of GNSS technologies and the potential impact on the corridor mapping market, the European Commission and the European GNSS Agency, in the frame of the European Union Framework Programme for Research and Innovation “Horizon 2020,” have recently awarded the “mapKITE” project to an international consortium of organizations coordinated by GeoNumerics S.L.

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