Error budget analysis of geocoding and geometric correction for KOMPSAT-5 SAR imagery
Geocoding geometrically rectifies a remote sensing image according to a specific map projection, and is an essential process for utilizing synthetic aperture radar (SAR) satellite images. The accuracy of geocoding is affected by various intercorrelated error sources. In this study, we propose a fram...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | GIScience & Remote Sensing |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/15481603.2022.2142669 |
| _version_ | 1797679039760039936 |
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| author | Eunkwan Lee Seunghwan Hong Yoonjo Choi Suhong Yoo Hong-Gyoo Sohn |
| author_facet | Eunkwan Lee Seunghwan Hong Yoonjo Choi Suhong Yoo Hong-Gyoo Sohn |
| author_sort | Eunkwan Lee |
| collection | DOAJ |
| description | Geocoding geometrically rectifies a remote sensing image according to a specific map projection, and is an essential process for utilizing synthetic aperture radar (SAR) satellite images. The accuracy of geocoding is affected by various intercorrelated error sources. In this study, we propose a framework for improving the geocoding accuracy of SAR images. Our framework consists of two major theoretical and computational steps: 1) calculating and setting the error budget of the SAR image geocoding accuracy and checking their quality and 2) applying a geometric correction model if the quality is lower than the predefined threshold. Error budget analysis was performed by utilizing the law of variance propagation, considering the correlations among the primary error sources. During the second (geometric correction) step, the non-multicollinearity (N-MC) model, a ground control point (GCP)-based geometric correction model without multicollinearity, was proposed. Experiments were conducted using two KOMPSAT-5 SAR images from Daejeon City, Korea to verify the framework. The geocoding accuracy of SAR images #1 and #2 exceeded the error budgets of all confidence levels, except for the row direction of SAR image #2, despite the vendor’s internal calibration. In the second step, two SAR images were geometrically corrected by applying the N-MC model. The use of geometric correction improved the geocoding accuracy of the two SAR images by approximately two to five pixels in the row and column directions. The final geocoding accuracy of the SAR images was within the error budget. |
| first_indexed | 2024-03-11T23:08:38Z |
| format | Article |
| id | doaj.art-a66edce402da4a35b2e15085ea758e8b |
| institution | Directory Open Access Journal |
| issn | 1548-1603 1943-7226 |
| language | English |
| last_indexed | 2024-03-11T23:08:38Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | GIScience & Remote Sensing |
| spelling | doaj.art-a66edce402da4a35b2e15085ea758e8b2023-09-21T12:43:09ZengTaylor & Francis GroupGIScience & Remote Sensing1548-16031943-72262022-12-015911938195510.1080/15481603.2022.21426692142669Error budget analysis of geocoding and geometric correction for KOMPSAT-5 SAR imageryEunkwan Lee0Seunghwan Hong1Yoonjo Choi2Suhong Yoo3Hong-Gyoo Sohn4Yonsei UniversityCorporation of Kakao MobilityCorporation of Kakao MobilityYonsei UniversityYonsei UniversityGeocoding geometrically rectifies a remote sensing image according to a specific map projection, and is an essential process for utilizing synthetic aperture radar (SAR) satellite images. The accuracy of geocoding is affected by various intercorrelated error sources. In this study, we propose a framework for improving the geocoding accuracy of SAR images. Our framework consists of two major theoretical and computational steps: 1) calculating and setting the error budget of the SAR image geocoding accuracy and checking their quality and 2) applying a geometric correction model if the quality is lower than the predefined threshold. Error budget analysis was performed by utilizing the law of variance propagation, considering the correlations among the primary error sources. During the second (geometric correction) step, the non-multicollinearity (N-MC) model, a ground control point (GCP)-based geometric correction model without multicollinearity, was proposed. Experiments were conducted using two KOMPSAT-5 SAR images from Daejeon City, Korea to verify the framework. The geocoding accuracy of SAR images #1 and #2 exceeded the error budgets of all confidence levels, except for the row direction of SAR image #2, despite the vendor’s internal calibration. In the second step, two SAR images were geometrically corrected by applying the N-MC model. The use of geometric correction improved the geocoding accuracy of the two SAR images by approximately two to five pixels in the row and column directions. The final geocoding accuracy of the SAR images was within the error budget.http://dx.doi.org/10.1080/15481603.2022.2142669sargeocodingerror budgetgeometric correctionkompsat-5 |
| spellingShingle | Eunkwan Lee Seunghwan Hong Yoonjo Choi Suhong Yoo Hong-Gyoo Sohn Error budget analysis of geocoding and geometric correction for KOMPSAT-5 SAR imagery GIScience & Remote Sensing sar geocoding error budget geometric correction kompsat-5 |
| title | Error budget analysis of geocoding and geometric correction for KOMPSAT-5 SAR imagery |
| title_full | Error budget analysis of geocoding and geometric correction for KOMPSAT-5 SAR imagery |
| title_fullStr | Error budget analysis of geocoding and geometric correction for KOMPSAT-5 SAR imagery |
| title_full_unstemmed | Error budget analysis of geocoding and geometric correction for KOMPSAT-5 SAR imagery |
| title_short | Error budget analysis of geocoding and geometric correction for KOMPSAT-5 SAR imagery |
| title_sort | error budget analysis of geocoding and geometric correction for kompsat 5 sar imagery |
| topic | sar geocoding error budget geometric correction kompsat-5 |
| url | http://dx.doi.org/10.1080/15481603.2022.2142669 |
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