scholarly journals ANALYSIS AND CORRECTION OF SYSTEMATIC HEIGHT MODEL ERRORS

2016 ◽  
Vol XLI-B1 ◽  
pp. 333-339 ◽  
Author(s):  
K. Jacobsen
Keyword(s):  
Bias Correction ◽  
Low Frequency ◽  
Ground Control ◽  
Control Points ◽  
Base Length ◽  
Model Errors ◽  
Ground Control Points ◽  
Small Base ◽  
Image Orientation ◽  
Height Model

The geometry of digital height models (DHM) determined with optical satellite stereo combinations depends upon the image orientation, influenced by the satellite camera, the system calibration and attitude registration. As standard these days the image orientation is available in form of rational polynomial coefficients (RPC). Usually a bias correction of the RPC based on ground control points is required. In most cases the bias correction requires affine transformation, sometimes only shifts, in image or object space. For some satellites and some cases, as caused by small base length, such an image orientation does not lead to the possible accuracy of height models. As reported e.g. by Yong-hua et al. 2015 and Zhang et al. 2015, especially the Chinese stereo satellite ZiYuan-3 (ZY-3) has a limited calibration accuracy and just an attitude recording of 4 Hz which may not be satisfying. Zhang et al. 2015 tried to improve the attitude based on the color sensor bands of ZY-3, but the color images are not always available as also detailed satellite orientation information. There is a tendency of systematic deformation at a Pléiades tri-stereo combination with small base length. The small base length enlarges small systematic errors to object space. But also in some other satellite stereo combinations systematic height model errors have been detected. The largest influence is the not satisfying leveling of height models, but also low frequency height deformations can be seen. <br><br> A tilt of the DHM by theory can be eliminated by ground control points (GCP), but often the GCP accuracy and distribution is not optimal, not allowing a correct leveling of the height model. In addition a model deformation at GCP locations may lead to not optimal DHM leveling. Supported by reference height models better accuracy has been reached. As reference height model the Shuttle Radar Topography Mission (SRTM) digital surface model (DSM) or the new AW3D30 DSM, based on ALOS PRISM images, are satisfying. They allow the leveling and correction of low frequency height errors and lead to satisfying correction of the DSM based on optical satellite images. <br><br> The potential of DHM generation, influence of systematic model deformation and possibilities of improvement has been investigated.

scholarly journals ANALYSIS AND CORRECTION OF SYSTEMATIC HEIGHT MODEL ERRORS

2016 ◽  
Vol XLI-B1 ◽  
pp. 333-339
Author(s):  
K. Jacobsen
Keyword(s):  
Bias Correction ◽  
Low Frequency ◽  
Ground Control ◽  
Control Points ◽  
Base Length ◽  
Model Errors ◽  
Ground Control Points ◽  
Small Base ◽  
Image Orientation ◽  
Height Model

The geometry of digital height models (DHM) determined with optical satellite stereo combinations depends upon the image orientation, influenced by the satellite camera, the system calibration and attitude registration. As standard these days the image orientation is available in form of rational polynomial coefficients (RPC). Usually a bias correction of the RPC based on ground control points is required. In most cases the bias correction requires affine transformation, sometimes only shifts, in image or object space. For some satellites and some cases, as caused by small base length, such an image orientation does not lead to the possible accuracy of height models. As reported e.g. by Yong-hua et al. 2015 and Zhang et al. 2015, especially the Chinese stereo satellite ZiYuan-3 (ZY-3) has a limited calibration accuracy and just an attitude recording of 4 Hz which may not be satisfying. Zhang et al. 2015 tried to improve the attitude based on the color sensor bands of ZY-3, but the color images are not always available as also detailed satellite orientation information. There is a tendency of systematic deformation at a Pléiades tri-stereo combination with small base length. The small base length enlarges small systematic errors to object space. But also in some other satellite stereo combinations systematic height model errors have been detected. The largest influence is the not satisfying leveling of height models, but also low frequency height deformations can be seen. <br><br> A tilt of the DHM by theory can be eliminated by ground control points (GCP), but often the GCP accuracy and distribution is not optimal, not allowing a correct leveling of the height model. In addition a model deformation at GCP locations may lead to not optimal DHM leveling. Supported by reference height models better accuracy has been reached. As reference height model the Shuttle Radar Topography Mission (SRTM) digital surface model (DSM) or the new AW3D30 DSM, based on ALOS PRISM images, are satisfying. They allow the leveling and correction of low frequency height errors and lead to satisfying correction of the DSM based on optical satellite images. <br><br> The potential of DHM generation, influence of systematic model deformation and possibilities of improvement has been investigated.

scholarly journals Accuracy of 3D Landscape Reconstruction without Ground Control Points Using Different UAS Platforms

Drones ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 13 ◽  
Author(s):  
Margaret Kalacska ◽  
Oliver Lucanus ◽  
J. Pablo Arroyo-Mora ◽  
Étienne Laliberté ◽  
Kathryn Elmer ◽  
...  
Keyword(s):  
Low Cost ◽  
Ground Control ◽  
Unmanned Aerial Systems ◽  
Control Points ◽  
Model Errors ◽  
Positional Accuracy ◽  
Ground Control Points ◽  
Digital Elevation ◽  
High Level ◽  
Aerial Systems

The rapid increase of low-cost consumer-grade to enterprise-level unmanned aerial systems (UASs) has resulted in the exponential use of these systems in many applications. Structure from motion with multiview stereo (SfM-MVS) photogrammetry is now the baseline for the development of orthoimages and 3D surfaces (e.g., digital elevation models). The horizontal and vertical positional accuracies (x, y and z) of these products in general, rely heavily on the use of ground control points (GCPs). However, for many applications, the use of GCPs is not possible. Here we tested 14 UASs to assess the positional and within-model accuracy of SfM-MVS reconstructions of low-relief landscapes without GCPs ranging from consumer to enterprise-grade vertical takeoff and landing (VTOL) platforms. We found that high positional accuracy is not necessarily related to the platform cost or grade, rather the most important aspect is the use of post-processing kinetic (PPK) or real-time kinetic (RTK) solutions for geotagging the photographs. SfM-MVS products generated from UAS with onboard geotagging, regardless of grade, results in greater positional accuracies and lower within-model errors. We conclude that where repeatability and adherence to a high level of accuracy are needed, only RTK and PPK systems should be used without GCPs.

scholarly journals GEOREFERENCING ACCURACY ANALYSIS OF A SINGLE WORLDVIEW-3 IMAGE COLLECTED OVER MILAN

2016 ◽  
Vol XLI-B1 ◽  
pp. 429-434 ◽  
Author(s):  
L. Barazzetti ◽  
F. Roncoroni ◽  
R. Brumana ◽  
M. Previtali
Keyword(s):  
Bias Correction ◽  
Rational Functions ◽  
The Other ◽  
Ground Control ◽  
Control Points ◽  
Accuracy Analysis ◽  
Camera Model ◽  
Ground Control Points ◽  
High Resolution Satellite Imagery ◽  
Very High

The use of rational functions has become a standard for very high-resolution satellite imagery (VHRSI). On the other hand, the overall geolocalization accuracy via direct georeferencing from on board navigation components is much worse than image ground sampling distance (predicted < 3.5 m CE90 for WorldView-3, whereas GSD = 0.31 m for panchromatic images at nadir). <br><br> This paper presents the georeferencing accuracy results obtained from a single WorldView-3 image processed with a bias compensated RPC camera model. Orientation results for an image collected over Milan are illustrated and discussed for both direct and indirect georeferencing strategies as well as different bias correction parameters estimated from a set of ground control points. Results highlight that the use of a correction based on two shift parameters is optimal for the considered dataset.

scholarly journals GEOREFERENCING UAS DERIVATIVES THROUGH POINT CLOUD REGISTRATION WITH ARCHIVED LIDAR DATASETS

2016 ◽  
Vol IV-2/W1 ◽  
pp. 195-199 ◽  
Author(s):  
M. S. L. Y. Magtalas ◽  
J. C. L. Aves ◽  
A. C. Blanco
Keyword(s):  
Point Cloud ◽  
Spatial Information ◽  
Aerial Images ◽  
Ground Control ◽  
Control Points ◽  
Model Errors ◽  
Validation Data ◽  
Positioning Systems ◽  
Ground Control Points ◽  
Skeleton Point

Georeferencing gathered images is a common step before performing spatial analysis and other processes on acquired datasets using unmanned aerial systems (UAS). Methods of applying spatial information to aerial images or their derivatives is through onboard GPS (Global Positioning Systems) geotagging, or through tying of models through GCPs (Ground Control Points) acquired in the field. Currently, UAS (Unmanned Aerial System) derivatives are limited to meter-levels of accuracy when their generation is unaided with points of known position on the ground. The use of ground control points established using survey-grade GPS or GNSS receivers can greatly reduce model errors to centimeter levels. However, this comes with additional costs not only with instrument acquisition and survey operations, but also in actual time spent in the field. This study uses a workflow for cloud-based post-processing of UAS data in combination with already existing LiDAR data. The georeferencing of the UAV point cloud is executed using the Iterative Closest Point algorithm (ICP). It is applied through the open-source CloudCompare software (Girardeau-Montaut, 2006) on a ‘skeleton point cloud’. This skeleton point cloud consists of manually extracted features consistent on both LiDAR and UAV data. For this cloud, roads and buildings with minimal deviations given their differing dates of acquisition are considered consistent. Transformation parameters are computed for the skeleton cloud which could then be applied to the whole UAS dataset. In addition, a separate cloud consisting of non-vegetation features automatically derived using CANUPO classification algorithm (Brodu and Lague, 2012) was used to generate a separate set of parameters. Ground survey is done to validate the transformed cloud. An RMSE value of around 16 centimeters was found when comparing validation data to the models georeferenced using the CANUPO cloud and the manual skeleton cloud. Cloud-to-cloud distance computations of CANUPO and manual skeleton clouds were obtained with values for both equal to around 0.67 meters at 1.73 standard deviation.

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 GEOREFERENCING ACCURACY ANALYSIS OF A SINGLE WORLDVIEW-3 IMAGE COLLECTED OVER MILAN

2016 ◽  
Vol XLI-B1 ◽  
pp. 429-434 ◽  
Author(s):  
L. Barazzetti ◽  
F. Roncoroni ◽  
R. Brumana ◽  
M. Previtali
Keyword(s):  
Bias Correction ◽  
Rational Functions ◽  
The Other ◽  
Ground Control ◽  
Control Points ◽  
Accuracy Analysis ◽  
Camera Model ◽  
Ground Control Points ◽  
High Resolution Satellite Imagery ◽  
Very High

The use of rational functions has become a standard for very high-resolution satellite imagery (VHRSI). On the other hand, the overall geolocalization accuracy via direct georeferencing from on board navigation components is much worse than image ground sampling distance (predicted &lt; 3.5 m CE90 for WorldView-3, whereas GSD = 0.31 m for panchromatic images at nadir). &lt;br&gt;&lt;br&gt; This paper presents the georeferencing accuracy results obtained from a single WorldView-3 image processed with a bias compensated RPC camera model. Orientation results for an image collected over Milan are illustrated and discussed for both direct and indirect georeferencing strategies as well as different bias correction parameters estimated from a set of ground control points. Results highlight that the use of a correction based on two shift parameters is optimal for the considered dataset.

Sign in / Sign up

Export Citation Format

Share Document