Performance evaluation according to virtual grid size in the rational function model generation for KOMPSAT-5 SAR imagery

Yoonjo Choi; Seunghwan Hong; Ilsuk Park; Mohammad Gholami Farkoushi; Hong Gyoo Sohn

Performance evaluation according to virtual grid size in the rational function model generation for KOMPSAT-5 SAR imagery

Yoonjo Choi, Seunghwan Hong, Ilsuk Park, Mohammad Gholami Farkoushi, Hong Gyoo Sohn

Department of Civil and Environmental Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

In utilizing satellite imagery, the Rational Function Model(RFM) simplifies the geometric relationship between image coordinates and ground targets. In this study, the RFM model for KOMPSAT-5 was generated and evaluated. The general least squares adjustment and Tikhonov regularization in the RFM generation process were applied to calculate the RFM coefficients. The virtual grid was generated using the physical sensor model for KOMPSAT-5 and used as control points to calculate the RFM coefficients. As a results, the virtual grid size did not show significant improvement from 7x7. In addition, the analysis result according to the number of the elevation layer was obtained sufficiently stable result even at 10x10x5.

Original language	English
Publication status	Published - 2020 Jan 1
Event	40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019 - Daejeon, Korea, Republic of Duration: 2019 Oct 14 → 2019 Oct 18

Conference

Conference	40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019
Country/Territory	Korea, Republic of
City	Daejeon
Period	19/10/14 → 19/10/18

All Science Journal Classification (ASJC) codes

Information Systems

Cite this

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title = "Performance evaluation according to virtual grid size in the rational function model generation for KOMPSAT-5 SAR imagery",

abstract = "In utilizing satellite imagery, the Rational Function Model(RFM) simplifies the geometric relationship between image coordinates and ground targets. In this study, the RFM model for KOMPSAT-5 was generated and evaluated. The general least squares adjustment and Tikhonov regularization in the RFM generation process were applied to calculate the RFM coefficients. The virtual grid was generated using the physical sensor model for KOMPSAT-5 and used as control points to calculate the RFM coefficients. As a results, the virtual grid size did not show significant improvement from 7x7. In addition, the analysis result according to the number of the elevation layer was obtained sufficiently stable result even at 10x10x5.",

author = "Yoonjo Choi and Seunghwan Hong and Ilsuk Park and Farkoushi, {Mohammad Gholami} and Sohn, {Hong Gyoo}",

year = "2020",

month = jan,

day = "1",

language = "English",

note = "40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019 ; Conference date: 14-10-2019 Through 18-10-2019",

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Performance evaluation according to virtual grid size in the rational function model generation for KOMPSAT-5 SAR imagery. / Choi, Yoonjo; Hong, Seunghwan; Park, Ilsuk et al.
2020. Paper presented at 40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019, Daejeon, Korea, Republic of.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - Performance evaluation according to virtual grid size in the rational function model generation for KOMPSAT-5 SAR imagery

AU - Choi, Yoonjo

AU - Hong, Seunghwan

AU - Park, Ilsuk

AU - Farkoushi, Mohammad Gholami

AU - Sohn, Hong Gyoo

PY - 2020/1/1

Y1 - 2020/1/1

N2 - In utilizing satellite imagery, the Rational Function Model(RFM) simplifies the geometric relationship between image coordinates and ground targets. In this study, the RFM model for KOMPSAT-5 was generated and evaluated. The general least squares adjustment and Tikhonov regularization in the RFM generation process were applied to calculate the RFM coefficients. The virtual grid was generated using the physical sensor model for KOMPSAT-5 and used as control points to calculate the RFM coefficients. As a results, the virtual grid size did not show significant improvement from 7x7. In addition, the analysis result according to the number of the elevation layer was obtained sufficiently stable result even at 10x10x5.

AB - In utilizing satellite imagery, the Rational Function Model(RFM) simplifies the geometric relationship between image coordinates and ground targets. In this study, the RFM model for KOMPSAT-5 was generated and evaluated. The general least squares adjustment and Tikhonov regularization in the RFM generation process were applied to calculate the RFM coefficients. The virtual grid was generated using the physical sensor model for KOMPSAT-5 and used as control points to calculate the RFM coefficients. As a results, the virtual grid size did not show significant improvement from 7x7. In addition, the analysis result according to the number of the elevation layer was obtained sufficiently stable result even at 10x10x5.

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M3 - Paper

T2 - 40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019

Y2 - 14 October 2019 through 18 October 2019

ER -

Performance evaluation according to virtual grid size in the rational function model generation for KOMPSAT-5 SAR imagery

Abstract

Conference

All Science Journal Classification (ASJC) codes

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