scholarly journals The Role of Unmanned Aerial Vehicles (UAVs) In Monitoring Rapidly Occuring Landslides

2018 ◽  
Author(s):  
Servet Yaprak ◽  
Omer Yildirim ◽  
Tekin Susam ◽  
Samed Inyurt ◽  
Irfan Oguz
Keyword(s):  
Image Sensors ◽  
Control Points ◽  
Ground Sample ◽  
New Approach ◽  
Location Data ◽  
Ground Control Points ◽  
Surface Models ◽  
Aerial Vehicle ◽  
Height Model

Abstract. This study used the Unmanned Aerial Vehicle (UAV), which was designed and produced to monitor rapidly occurring landslides in forest areas. It was aimed to determine the location data for the study area using image sensors integrated into the UAV. The study area was determined as the landslide sites located in the Taşlıçiftlik Campus of Gaziosmanpaşa University, Turkey. It was determined that landslide activities were on going in the determined study area and data was collected regarding the displacement of materials. Additionally, it was observed that data about landslides may be collected in a fast and sensitive way using UAVs, and this method is proposed as a new approach. Flights took place over a total of five different periods. In order to determine the direction and coordinate variables for the developed model, eight Ground Control Points (GCPs), whose coordinates were obtained with the GNSS method, were placed on the study area. In each period, approximately 190 photographs were investigated. The photos obtained were analysed using the PIX4D software. At the end of each period, the RMS and Ground Sample Distance (GSD) values of the GCPs were calculated. Orthomosaic and Digital Surface Models (DSM) were produced for the location and height model. The results showed that max RMS = ±3.3 cm and max GSD = 3.57 cm/1.40 in. When the first and fifth periods are compared; the highest spatial displacement value ΔS = 111.0 cm, the highest subsidence value Δh = 37.3 cm and the highest swelling value Δh = 28.6 cm as measured.

scholarly journals Accuracy of Unmanned Aerial Vehicle (UAV) and SfM Photogrammetry Survey as a Function of the Number and Location of Ground Control Points Used

2018 ◽  
Vol 10 (10) ◽  
pp. 1606 ◽  
Author(s):  
Enoc Sanz-Ablanedo ◽  
Jim Chandler ◽  
José Rodríguez-Pérez ◽  
Celestino Ordóñez
Keyword(s):  
Critical Role ◽  
Bundle Adjustment ◽  
Ground Control ◽  
Control Points ◽  
Ground Sample ◽  
Ground Control Points ◽  
Check Points ◽  
Aerial Vehicle

The geometrical accuracy of georeferenced digital surface models (DTM) obtained from images captured by micro-UAVs and processed by using structure from motion (SfM) photogrammetry depends on several factors, including flight design, camera quality, camera calibration, SfM algorithms and georeferencing strategy. This paper focusses on the critical role of the number and location of ground control points (GCP) used during the georeferencing stage. A challenging case study involving an area of 1200+ ha, 100+ GCP and 2500+ photos was used. Three thousand, four hundred and sixty-five different combinations of control points were introduced in the bundle adjustment, whilst the accuracy of the model was evaluated using both control points and independent check points. The analysis demonstrates how much the accuracy improves as the number of GCP points increases, as well as the importance of an even distribution, how much the accuracy is overestimated when it is quantified only using control points rather than independent check points, and how the ground sample distance (GSD) of a project relates to the maximum accuracy that can be achieved.

scholarly journals IMPROVING VERTICAL ACCURACY OF UAV DIGITAL SURFACE MODELS BY INTRODUCING TERRESTRIAL LASER SCANS ON A POINT-CLOUD LEVEL

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 457-463
Author(s):  
T. Ivelja ◽  
B. Bechor ◽  
O. Hasan ◽  
S. Miko ◽  
D. Sivan ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Scene Reconstruction ◽  
Control Points ◽  
Ground Control Points ◽  
Surface Models ◽  
Aerial Vehicle ◽  
Vertical Accuracy ◽  
3D Scene ◽  
3D Scene Reconstruction

Abstract. Digital Surface Models (DSM) generated by image-based scene reconstruction from Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanning (TLS)point clouds are highly distinguished in terms of resolution and accuracy. This leads to a situation where users have to choose the most beneficial product to fulfill their needs. In the current study, these techniques no longer compete but complement each other. Experiments were implemented to verify the improvement of vertical accuracy by introducing different amounts and configurations of Terrestrial Laser scans in the photogrammetric Structure from Motion (SfM) workflow for high-resolution 3D-scene reconstruction. Results show that it is possible to significantly improve (∼ 49% ) the vertical accuracy of DSMs by introducing a TLS point clouds. However, accuracy improvement is highly associated with the number of introduced Ground Control Points (GCP) in the SfM workflow procedure.

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 The role of national and international geospatial data sources in the management of natural disasters

2014 ◽  
Vol XL-8 ◽  
pp. 47-51 ◽  
Author(s):  
A. Kayi ◽  
M. Erdogan ◽  
A. Yilmaz
Keyword(s):  
Natural Disasters ◽  
Armed Forces ◽  
Geospatial Data ◽  
City Centre ◽  
Control Points ◽  
Van Earthquake ◽  
Ground Sample ◽  
Aerial Photos ◽  
Ground Control Points

An earthquake occurred at Van City on 23 October 2011 at 13:41 local time. The magnitude, moment magnitude and depth of earthquake were respectively MI:6.7, Mw:7.0 and 19.07 km. Van city centre and its surrounding villages were affected from this destructive earthquake. Many buildings were ruined and approximately 600 people died. Acquisition and use of geospatial data is very important and crucial for the management of such kind of natural disasters. In this paper, the role of national and international geospatial data in the management of Van earthquake is investigated.. With an international collaboration with Charter, pre and post-earthquake satellite images were acquired in 24 hours following the Earthquake. Also General Command of Mapping (GCM), the national mapping agency of Turkey, produced the high resolution multispectral orthophotos of the region. Charter presented the orthophotos through 26&ndash;28 October 2012. Just after the earthquake with a quick reaction, GCM made the flight planning of the 1296 km<sup>2</sup> disaster area to acquire aerial photos. The aerial photos were acquired on 24 October 2012 (one day after the earthquake) by UltraCamX large format digital aerial camera. 152 images were taken with 30 cm ground sample distance (GSD) by %30 sidelap and %60 overlap. In the evening of same flight day, orthophotos were produced without ground control points by direct georeferencing and GCM supplied the orthophotos to the disaster management authorities. Also 45 cm GSD archive orthophotos, acquired in 2010, were used as a reference in order to find out the effects of the disaster. The subjects written here do not represent the ideas of Turkish Armed Forces.

scholarly journals Evaluation of the Georeferencing Accuracy of a Photogrammetric Model Using a Quadrocopter with Onboard GNSS RTK

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2318 ◽  
Author(s):  
Martin Štroner ◽  
Rudolf Urban ◽  
Tomáš Reindl ◽  
Jan Seidl ◽  
Josef Brouček
Keyword(s):  
Vertical Component ◽  
Satellite System ◽  
Bundle Adjustment ◽  
Ground Control ◽  
Control Points ◽  
Ground Sample ◽  
Ground Control Points ◽  
Aerial Vehicle ◽  
Global Navigation Satellite ◽  
Orientation Parameters

Using a GNSS RTK (Global Navigation Satellite System Real Time Kinematic) -equipped unmanned aerial vehicle (UAV) could greatly simplify the construction of highly accurate digital models through SfM (Structure from Motion) photogrammetry, possibly even avoiding the need for ground control points (GCPs). As previous studies on this topic were mostly performed using fixed-wing UAVs, this study aimed to investigate the results achievable by a quadrocopter (DJI Phantom 4 RTK). Three image acquisition flights were performed for two sites of a different character (urban and rural) along with three calculation variants for each flight: georeferencing using ground-surveyed GCPs only, onboard GNSS RTK only, and a combination thereof. The combined and GNSS RTK methods provided the best results (at the expected level of accuracy of 1–2 GSD (Ground Sample Distance)) for both the vertical and horizontal components. The horizontal positioning was also accurate when georeferencing directly based on the onboard GNSS RTK; the vertical component, however, can be (especially where the terrain is difficult for SfM evaluation) burdened with relatively high systematic errors. This problem was caused by the incorrect identification of the interior orientation parameters calculated, as is customary for non-metric cameras, together with bundle adjustment. This problem could be resolved by using a small number of GCPs (at least one) or quality camera pre-calibration.

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 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 ACCURACY ASSESSMENT OF A UAV-BASED LANDSLIDE MONITORING SYSTEM

2016 ◽  
Vol XLI-B5 ◽  
pp. 895-902 ◽  
Author(s):  
M. V. Peppa ◽  
J. P. Mills ◽  
P. Moore ◽  
P. E. Miller ◽  
J. E. Chambers
Keyword(s):  
Image Matching ◽  
Accuracy Assessment ◽  
Bundle Adjustment ◽  
Landslide Monitoring ◽  
Control Points ◽  
Error Assessment ◽  
Ground Sample ◽  
Ground Control Points ◽  
Pixel Image ◽  
Spatio Temporal

Landslides are hazardous events with often disastrous consequences. Monitoring landslides with observations of high spatio-temporal resolution can help mitigate such hazards. Mini unmanned aerial vehicles (UAVs) complemented by structure-from-motion (SfM) photogrammetry and modern per-pixel image matching algorithms can deliver a time-series of landslide elevation models in an automated and inexpensive way. This research investigates the potential of a mini UAV, equipped with a Panasonic Lumix DMC-LX5 compact camera, to provide surface deformations at acceptable levels of accuracy for landslide assessment. The study adopts a self-calibrating bundle adjustment-SfM pipeline using ground control points (GCPs). It evaluates misalignment biases and unresolved systematic errors that are transferred through the SfM process into the derived elevation models. To cross-validate the research outputs, results are compared to benchmark observations obtained by standard surveying techniques. The data is collected with 6 cm ground sample distance (GSD) and is shown to achieve planimetric and vertical accuracy of a few centimetres at independent check points (ICPs). The co-registration error of the generated elevation models is also examined in areas of stable terrain. Through this error assessment, the study estimates that the vertical sensitivity to real terrain change of the tested landslide is equal to 9 cm.

scholarly journals PRECISION OF VISUAL LOCALIZATION USING DYNAMIC GROUND CONTROL POINTS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 363-370
Author(s):  
P. Trusheim ◽  
C. Heipke
Keyword(s):  
Rapid Development ◽  
Sliding Window ◽  
Bundle Adjustment ◽  
Ground Control ◽  
Visual Localization ◽  
Control Points ◽  
Automated Driving ◽  
Sliding Windows ◽  
Ground Control Points

Abstract. Localization is one of the first steps in navigation. Especially due to the rapid development in automated driving, a precise and reliable localization becomes essential. In this paper, we report an investigation of the usage of dynamic ground control points (GCP) in visual localization in an automotive environment. Instead of having fixed positions, dynamic GCPs move together with the camera. As a measure of quality, we employ the precision of the bundle adjustment results. In our experiments, we simulate and investigate different realistic traffic scenarios. After investigating the role of tie points, we compare an approach using dynamic GCPs to an approach with static GCPs to answer the question how a comparable precision can be reached for visual localization. We show, that in our scenario, where two dynamic GCPs move together with a camera, similar results are indeed obtained to using a number of static GCPs distributed over the whole trajectory. In another experiment, we take a closer look at sliding window bundle adjustments. Sliding windows make it possible to work with an arbitrarily large number of images and to still obtain near real-time results. We investigate this approach in combination with dynamic GCPs and vary the no. of images per window.

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