scholarly journals PRECISE AERIAL IMAGE ORIENTATION USING SAR GROUND CONTROL POINTS FOR MAPPING OF URBAN LANDMARKS

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 61-66
Author(s):  
F. Kurz ◽  
T. Krauß ◽  
H. Runge ◽  
D. Rosenbaum ◽  
P. d’Angelo
Keyword(s):  
Image Data ◽  
Bundle Adjustment ◽  
Aerial Image ◽  
Ground Control ◽  
Data Sets ◽  
Control Points ◽  
Ground Control Points ◽  
Autonomous Cars ◽  
New Applications ◽  
Image Orientation

<p><strong>Abstract.</strong> Highly precise ground control points, which are globally available, can be derived from the SAR satellite TerraSAR-X. This opens up many new applications like for example the precise aerial image orientation. In this paper, we propose a method for precise aerial image orientation using spaceborne geodetic Synthetic Aperture Radar Ground Control Points (SAR-GCPs). The precisely oriented aerial imagery can then be used e.g. for mapping of urban landmarks, which support the ego-positioning of autonomous cars. The method for precise image orientation was validated based on two aerial image data sets. SAR-GCPs were measured in images, then the image orientation has been improved by a bundle-adjustment. Results based on check points show, that the accuracy of the image orientation is better than 5&amp;thinsp;cm in X and Y coordinates.</p>

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.

scholarly journals CORRECTION OF MOBILE MAPPING TRAJECTORIES IN GNSS-DENIED ENVIRONMENTS USING AERIAL NADIR AND AERIAL OBLIQUE IMAGES

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1649-1654
Author(s):  
P. Fanta-Jende ◽  
F. Nex ◽  
M. Gerke ◽  
J. Lijnen ◽  
G. Vosselman
Keyword(s):  
High Speed ◽  
Low Cost ◽  
Image Data ◽  
City Centre ◽  
Ground Control ◽  
Control Points ◽  
Mobile Mapping ◽  
Ground Control Points ◽  
Before And After ◽  
Oblique Images

<p><strong>Abstract.</strong> Mobile mapping enables highly accurate as well as high-resolution image data capture at low cost and high speed. As a terrestrial acquisition technique predominately employed in urban, and thus built-up areas, non-line-of-sight and multipath effects challenge its absolute positioning capabilities provided by GNSS. In conjunction with IMU drift, the platform’s trajectory has an unknown accuracy, which influences the quality of the data product. By employing a highly accurate co-registration technique for identifying tie correspondences between mobile mapping images and aerial nadir as well as aerial oblique images, reliable ground control can be introduced into an adjustment solution. We exemplify the performance of our registration results by showcasing adjusted mobile mapping trajectories in four different test areas, each with about 100 consecutive recording locations (approx. 500&amp;thinsp;m length) in the city centre of Rotterdam, The Netherlands. The mobile mapping data has been adjusted in different configurations, i.e. with nadir or oblique aerial correspondences only and if possible in conjunction. To compare the horizontal as well as the vertical accuracy before and after the respective adjustments, more than 30 ground control points were surveyed for these experiments. In general, the aim of our technique is not only to correct mobile mapping trajectories in an automated fashion but also to verify their accuracy without the need to acquire ground control points. In most of our test cases, the overall accuracy of the mobile mapping image positions in the trajectory could be improved. Depending on the test area, an RMSE in 3D between 15 and 21&amp;thinsp;cm and an RMSE in 2D between 11 and 18&amp;thinsp;cm is achievable.</p>

scholarly journals AUTOMATIC KAPPA ANGLE ESTIMATION FOR AIR PHOTOS BASED ON PHASE ONLY CORRELATION

2016 ◽  
Vol XLI-B3 ◽  
pp. 131-135
Author(s):  
Z. Xiong ◽  
D. Stanley ◽  
Y. Xin
Keyword(s):  
Bundle Adjustment ◽  
Ground Control ◽  
Correlation Technique ◽  
Control Points ◽  
Initial Value ◽  
Ground Control Points ◽  
Attitude Angle ◽  
Camera Position ◽  
Air Photo ◽  
Orientation Parameters

The approximate value of exterior orientation parameters is needed for air photo bundle adjustment. Usually the air borne GPS/IMU can provide the initial value for the camera position and attitude angle. However, in some cases, the camera’s attitude angle is not available due to lack of IMU or other reasons. In this case, the kappa angle needs to be estimated for each photo before bundle adjustment. The kappa angle can be obtained from the Ground Control Points (GCPs) in the photo. Unfortunately it is not the case that enough GCPs are always available. In order to overcome this problem, an algorithm is developed to automatically estimate the kappa angle for air photos based on phase only correlation technique. This function has been embedded in PCI software. Extensive experiments show that this algorithm is fast, reliable, and stable.

scholarly journals UAV AND LIDAR IMAGE REGISTRATION: A SURF-BASED APPROACH FOR GROUND CONTROL POINTS SELECTION

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 413-418 ◽  
Author(s):  
B. Kalantar ◽  
N. Ueda ◽  
H. A. H. Al-Najjar ◽  
H. Moayedi ◽  
A. A. Halin ◽  
...  
Keyword(s):  
Image Registration ◽  
Water Resource Management ◽  
Feature Matching ◽  
Image Data ◽  
Ground Control ◽  
Control Points ◽  
Speeded Up Robust Features ◽  
Ground Control Points ◽  
Edge Detectors ◽  
Edge Features

<p><strong>Abstract.</strong> Multisource remote sensing image data provides synthesized information to support many applications including land cover mapping, urban planning, water resource management, and GIS modelling. Effectively utilizing such images however requires proper image registration, which in turn highly relies on accurate ground control points (GCP) selection. This study evaluates the performance of the interest point descriptor SURF (Speeded-Up Robust Features) for GCPs selection from UAV and LiDAR images. The main motivation for using SURF is due to it being invariant to scaling, blur and illumination, and partially invariant to rotation and view point changes. We also consider features generated by the Sobel and Canny edge detectors as complements to potentially increase the accuracy of feature matching between the UAV and LiDAR images. From our experiments, the red channel (Band-3) produces the most accurate and practical results in terms of registration, while adding the edge features seems to produce lacklustre results.</p>

scholarly journals Mining Ground Surface Information Extraction and Topographic Analysis Using UAV Video Data

2020 ◽  
Vol 194 ◽  
pp. 05030
Author(s):  
Yin Yaqiu ◽  
Jiang Cunhao ◽  
Lv Jing ◽  
Wang Jie ◽  
Ju Xing ◽  
...  
Keyword(s):  
Land Surface ◽  
Image Data ◽  
Video Data ◽  
Shanxi Province ◽  
Ground Control ◽  
Surface Model ◽  
Control Points ◽  
Topographic Analysis ◽  
Ground Control Points ◽  
Data Source

Taking the Xiangwang bauxite mining of Xiaoyi City, Shanxi Province as the research object, the DJi “Wu”inspire2 model Unmanned aerial vehicle (UAV) was used to obtain the video data, image data and Ground control points (GCP) data of a typical pit in the study area. Based on the two kinds of data source (video data and image data), the Digital surface model (DSM) of the research area was acquired with or without ground control points through aerial triangulation and block adjustment. Using the DSM obtained by the two data source, the distribution of elevation, slope, slope direction, surface fluctuation and surface roughness was extracted and compared. Research shows that the DSM, acquired by the ContextCapture software without GCP, using video data obtained by aerial shooting around one interest point, can qualitatively reflect the topographic distribution of the land surface. The DSM got by the video data with the GCP can achieve the similar accuracy with the result obtained by image data, and the topographic information acquired by the two kinds of data source has highly similar characteristics in spatial and numerical distribution. It can be concluded through comparison and analysis of the topographical factors that steep slopes with complex topography and large elevation difference distributes in the northwest-central of the pit, of which northwest and southwest slopes can be easily eroded by wind and rain, so attention should be paid to slop stability monitoring and disaster prevention in this area. As a whole, the results show that video data obtained by UAV can not only reflect the dynamic changes of the land surface qualitatively, but also can describe the distribution of surface topography quantitatively through processing to get the DSM. It has great application potential in the field of disaster emergency monitoring and geological hazard risk assessment in mining areas.

scholarly journals 3-D modelling and visualization of large building using photogrammetric approach

2021 ◽  
Author(s):  
Raad Awad Kattan ◽  
◽  
Farsat Heeto Abdulrahman ◽  
Sami Mamlook Gilyana ◽  
Yousif Youkhna Zaya ◽  
...  
Keyword(s):  
Bundle Adjustment ◽  
Ground Control ◽  
Control Points ◽  
Distance Measurements ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Elevation Model ◽  
College Of Engineering ◽  
User Friendly ◽  
D Model

The progress in modern technologies such as precise lightweight cameras mounted on unmanned aerial vehicles (UAV) and the more user-friendly software in the photogrammetric field, allows for 3-D model construction of any structure or shape. Software now achieves in sequence the processes of matching, generating tie points, block bundle adjustment, and generating digital elevation models.The aim of this study is to make a virtual 3-D model of the college of engineering /University of Duhok. Kurdistan Region, Iraq. The data input is vertical and oblique imagery acquired by UAV, ground control points distributed on the surrounded ground, facades, and roof. Ground control points were measured by the GPS RTK system in addition to the reflectorless total station instrument. The data is processed mainly using Agisoft PhotoScan software as well as the Global Mapper and the ReCap software. The output is a 3-D model, digital elevation model, and orthomosaic.Geometric and visual inspections were carried out. Some imperfections appeared on the sharp edges and parapets of the building. In the geometric accuracy of selected points on the building, the maximum standard deviation in the coordinates was ±4cm. The relative accuracy in distance measurements were in the range of 0.72% to 4.92 %

The Possibility of Using Navigation GPS Devices in the Survey Engineering

2018 ◽  
Vol 7 (4.20) ◽  
pp. 293
Author(s):  
Haidar Abbas Neam Al_ dami ◽  
Isaraa Riyadh Abdulridha
Keyword(s):  
Statistical Analysis ◽  
Random Error ◽  
Distance Measurement ◽  
Ground Control ◽  
Information Revolution ◽  
Control Points ◽  
Ground Control Points ◽  
Gps Devices ◽  
New Applications ◽  
Electronic Distance Measurement

As a result of the tremendous development in the field of computer technologies, communications and information revolution, new applications which has seen a tremendous development in terms of devices and technologies used in various applications such as a device Electronic Distance Measurement (EDM), Total Station, GPS (Surveyor and Navigational)… etc. In this study, five-ground control points (BM) were made to provide traverse, and these points observed by using three different navigation GPS devices, and observed by using TOTALSTATION device, and using spatial and statistical analysis functions in GIS.  The study showed that the error in these devices is a random error varies from one device to another. In addition, it showed that the error varies from time to time. Cannot be determined the spread of readings to the observed point (by navigation GPS) in a particular direction or specific frame, as well as the central distance of the readings are changing from one device to another and from point to point.The study recommends that should not be used navigation GPS devices in the survey work.  In addition, re-survey all areas are observed or defined its borders by using this device (navigation GPS) by serving GPS devices with the required accuracy.  

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 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.

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