Improvement of VHR Satellite Image Geometry with High Resolution Elevation Models
The number of high and very high resolution (VHR) optical satellite sensors, as well as the number of medium resolution satellites is continuously growing. However, not all high-resolution optical satellite imaging cameras have a sufficient and stable calibration in time. Due to their high agility i...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/10/2303 |
| _version_ | 1797496070612189184 |
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| author | Ana-Maria Loghin Johannes Otepka-Schremmer Camillo Ressl Norbert Pfeifer |
| author_facet | Ana-Maria Loghin Johannes Otepka-Schremmer Camillo Ressl Norbert Pfeifer |
| author_sort | Ana-Maria Loghin |
| collection | DOAJ |
| description | The number of high and very high resolution (VHR) optical satellite sensors, as well as the number of medium resolution satellites is continuously growing. However, not all high-resolution optical satellite imaging cameras have a sufficient and stable calibration in time. Due to their high agility in rotation, a quick change in viewing direction can lead to satellite attitude oscillation, causing image distortions and thus affecting image geometry and geo-positioning accuracy. This paper presents an approach based on re-projection of regularly distributed 3D ground points from object in image space, to detect and estimate the periodic distortions of Pléiades tri-stereo imagery caused by satellite attitude oscillations. For this, a hilly region was selected as a test site. Consequently, we describe a complete processing pipeline for computing the systematic height errors (deformations, waves) of the satellite-based digital elevation model by using a Lidar high resolution terrain model. Ground points with fixed positions, but with two elevations (actual and corrected) are then re-projected to the satellite images with the aid of the Rational Polynomial Coefficients (RPCs) provided with the imagery. Therefore, image corrections (displacements) are determined by computing the differences between the distinct positions of corresponding points in image space. Our experimental results in Allentsteig (Lower Austria) show that the systematic height errors of satellite-based elevation models cannot be compensated with an usual or even high number of Ground Control Points (GCPs) for RPC bias correction, due to insufficiently known image orientations. In comparison to a reference Lidar Digital Terrain Model (DTM), the computed elevation models show undulation effects with a maximum height difference of 0.88 m in along-track direction. With the proposed method, image distortions in-track direction with amplitudes of less than 0.15 pixels were detected. After applying the periodic distortion compensation to all three images, the systematic elevation discrepancies from the derived elevation models were successfully removed and the overall accuracy in open areas improved by 33% in the RMSE. Additionally, we show that a coarser resolution reference elevation model (AW3D30) is not feasible for improving the geometry of the Pléiades tri-stereo satellite imagery. |
| first_indexed | 2024-03-10T01:58:24Z |
| format | Article |
| id | doaj.art-f8eda2287f2047918ce7ed7fafe7d00d |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T01:58:24Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-f8eda2287f2047918ce7ed7fafe7d00d2023-11-23T12:53:53ZengMDPI AGRemote Sensing2072-42922022-05-011410230310.3390/rs14102303Improvement of VHR Satellite Image Geometry with High Resolution Elevation ModelsAna-Maria Loghin0Johannes Otepka-Schremmer1Camillo Ressl2Norbert Pfeifer3Department of Geodesy and Geoinformation, Technische Universität Wien, Wiedner Hauptstraße 8-10, 1040 Vienna, AustriaDepartment of Geodesy and Geoinformation, Technische Universität Wien, Wiedner Hauptstraße 8-10, 1040 Vienna, AustriaDepartment of Geodesy and Geoinformation, Technische Universität Wien, Wiedner Hauptstraße 8-10, 1040 Vienna, AustriaDepartment of Geodesy and Geoinformation, Technische Universität Wien, Wiedner Hauptstraße 8-10, 1040 Vienna, AustriaThe number of high and very high resolution (VHR) optical satellite sensors, as well as the number of medium resolution satellites is continuously growing. However, not all high-resolution optical satellite imaging cameras have a sufficient and stable calibration in time. Due to their high agility in rotation, a quick change in viewing direction can lead to satellite attitude oscillation, causing image distortions and thus affecting image geometry and geo-positioning accuracy. This paper presents an approach based on re-projection of regularly distributed 3D ground points from object in image space, to detect and estimate the periodic distortions of Pléiades tri-stereo imagery caused by satellite attitude oscillations. For this, a hilly region was selected as a test site. Consequently, we describe a complete processing pipeline for computing the systematic height errors (deformations, waves) of the satellite-based digital elevation model by using a Lidar high resolution terrain model. Ground points with fixed positions, but with two elevations (actual and corrected) are then re-projected to the satellite images with the aid of the Rational Polynomial Coefficients (RPCs) provided with the imagery. Therefore, image corrections (displacements) are determined by computing the differences between the distinct positions of corresponding points in image space. Our experimental results in Allentsteig (Lower Austria) show that the systematic height errors of satellite-based elevation models cannot be compensated with an usual or even high number of Ground Control Points (GCPs) for RPC bias correction, due to insufficiently known image orientations. In comparison to a reference Lidar Digital Terrain Model (DTM), the computed elevation models show undulation effects with a maximum height difference of 0.88 m in along-track direction. With the proposed method, image distortions in-track direction with amplitudes of less than 0.15 pixels were detected. After applying the periodic distortion compensation to all three images, the systematic elevation discrepancies from the derived elevation models were successfully removed and the overall accuracy in open areas improved by 33% in the RMSE. Additionally, we show that a coarser resolution reference elevation model (AW3D30) is not feasible for improving the geometry of the Pléiades tri-stereo satellite imagery.https://www.mdpi.com/2072-4292/14/10/2303very high resolution (VHR)image geometryrational polynomial coefficients (RPCs)attitude oscillations |
| spellingShingle | Ana-Maria Loghin Johannes Otepka-Schremmer Camillo Ressl Norbert Pfeifer Improvement of VHR Satellite Image Geometry with High Resolution Elevation Models Remote Sensing very high resolution (VHR) image geometry rational polynomial coefficients (RPCs) attitude oscillations |
| title | Improvement of VHR Satellite Image Geometry with High Resolution Elevation Models |
| title_full | Improvement of VHR Satellite Image Geometry with High Resolution Elevation Models |
| title_fullStr | Improvement of VHR Satellite Image Geometry with High Resolution Elevation Models |
| title_full_unstemmed | Improvement of VHR Satellite Image Geometry with High Resolution Elevation Models |
| title_short | Improvement of VHR Satellite Image Geometry with High Resolution Elevation Models |
| title_sort | improvement of vhr satellite image geometry with high resolution elevation models |
| topic | very high resolution (VHR) image geometry rational polynomial coefficients (RPCs) attitude oscillations |
| url | https://www.mdpi.com/2072-4292/14/10/2303 |
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