Estimation and improvement in the geolocation accuracy of rational polynomial coefficients with minimum GCPs using KOMPSAT-3A
In this paper, we propose a method to regenerate Rational Polynomial Coefficients (RPCs) using KOMPSAT-3A imagery and to reduce the geolocation error using minimum ground control points (GCPs). To estimate the new RPCs, the physical sensor model fitted to KOMPSAT-3A imagery was utilized and virtual...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-08-01
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| Series: | GIScience & Remote Sensing |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/15481603.2020.1791499 |
| _version_ | 1797679082373120000 |
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| author | Namhoon Kim Yoonjo Choi Junsu Bae Hong-Gyoo Sohn |
| author_facet | Namhoon Kim Yoonjo Choi Junsu Bae Hong-Gyoo Sohn |
| author_sort | Namhoon Kim |
| collection | DOAJ |
| description | In this paper, we propose a method to regenerate Rational Polynomial Coefficients (RPCs) using KOMPSAT-3A imagery and to reduce the geolocation error using minimum ground control points (GCPs). To estimate the new RPCs, the physical sensor model fitted to KOMPSAT-3A imagery was utilized and virtual GCPs over the study area were created. The size of the virtual grid used was 20x20x20. To remove the sensor-related errors in physical sensor model, three different image correction models (image coordinate translation model, shift and drift model, and affine transformation model) were additionally applied. We evaluated our proposed method in two areas within Korea, one in urban (Seoul) and one in rural (Goheung) areas. The results showed that there was a significant improvement after applying the suggested approach in the two areas. The image coordinate translation model is suggested in terms of GCP requirement and expected errors estimated from the error propagation analysis using Gauss–Markov Model (GMM). |
| first_indexed | 2024-03-11T23:09:16Z |
| format | Article |
| id | doaj.art-3d924dea287042d28ea81b0891dfbbd6 |
| institution | Directory Open Access Journal |
| issn | 1548-1603 1943-7226 |
| language | English |
| last_indexed | 2024-03-11T23:09:16Z |
| publishDate | 2020-08-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | GIScience & Remote Sensing |
| spelling | doaj.art-3d924dea287042d28ea81b0891dfbbd62023-09-21T12:34:16ZengTaylor & Francis GroupGIScience & Remote Sensing1548-16031943-72262020-08-0157671973410.1080/15481603.2020.17914991791499Estimation and improvement in the geolocation accuracy of rational polynomial coefficients with minimum GCPs using KOMPSAT-3ANamhoon Kim0Yoonjo Choi1Junsu Bae2Hong-Gyoo Sohn3Yonsei UniversityYonsei UniversityYonsei UniversityYonsei UniversityIn this paper, we propose a method to regenerate Rational Polynomial Coefficients (RPCs) using KOMPSAT-3A imagery and to reduce the geolocation error using minimum ground control points (GCPs). To estimate the new RPCs, the physical sensor model fitted to KOMPSAT-3A imagery was utilized and virtual GCPs over the study area were created. The size of the virtual grid used was 20x20x20. To remove the sensor-related errors in physical sensor model, three different image correction models (image coordinate translation model, shift and drift model, and affine transformation model) were additionally applied. We evaluated our proposed method in two areas within Korea, one in urban (Seoul) and one in rural (Goheung) areas. The results showed that there was a significant improvement after applying the suggested approach in the two areas. The image coordinate translation model is suggested in terms of GCP requirement and expected errors estimated from the error propagation analysis using Gauss–Markov Model (GMM).http://dx.doi.org/10.1080/15481603.2020.1791499kompsat-3arational functional modelrational polynomial coefficientimage space correctiongeo-positioning accuracy |
| spellingShingle | Namhoon Kim Yoonjo Choi Junsu Bae Hong-Gyoo Sohn Estimation and improvement in the geolocation accuracy of rational polynomial coefficients with minimum GCPs using KOMPSAT-3A GIScience & Remote Sensing kompsat-3a rational functional model rational polynomial coefficient image space correction geo-positioning accuracy |
| title | Estimation and improvement in the geolocation accuracy of rational polynomial coefficients with minimum GCPs using KOMPSAT-3A |
| title_full | Estimation and improvement in the geolocation accuracy of rational polynomial coefficients with minimum GCPs using KOMPSAT-3A |
| title_fullStr | Estimation and improvement in the geolocation accuracy of rational polynomial coefficients with minimum GCPs using KOMPSAT-3A |
| title_full_unstemmed | Estimation and improvement in the geolocation accuracy of rational polynomial coefficients with minimum GCPs using KOMPSAT-3A |
| title_short | Estimation and improvement in the geolocation accuracy of rational polynomial coefficients with minimum GCPs using KOMPSAT-3A |
| title_sort | estimation and improvement in the geolocation accuracy of rational polynomial coefficients with minimum gcps using kompsat 3a |
| topic | kompsat-3a rational functional model rational polynomial coefficient image space correction geo-positioning accuracy |
| url | http://dx.doi.org/10.1080/15481603.2020.1791499 |
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