Geometric Correction for the Geostationary Ocean Color Imager from a Combination of Shoreline Matching and Frequency Matching

Geometric correction is fundamental in producing high quality satellite data products. However, the geometric correction for ocean color sensors, e.g., Geostationary Ocean Color Imager (GOCI), is challenging because the traditional method based on ground control points (GCPs) cannot be applied when...

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Main Authors: Han-Gyeol Kim, Jong-Hwan Son, Taejung Kim
Format: Article
Language:English
Published: MDPI AG 2018-10-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/18/11/3599
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spelling doaj-1f74a3a0dfc747ca9544629a5e90dca82020-11-25T02:11:16ZengMDPI AGSensors1424-82202018-10-011811359910.3390/s18113599s18113599Geometric Correction for the Geostationary Ocean Color Imager from a Combination of Shoreline Matching and Frequency MatchingHan-Gyeol Kim0Jong-Hwan Son1Taejung Kim23DLabs Co. Ltd., 100 Inharo, Michuhol-Gu, Incheon 22212, KoreaDepartment of Geoinformatic Engineering, Inha University, 100 Inharo, Michuhol-Gu, Incheon 22212, KoreaDepartment of Geoinformatic Engineering, Inha University, 100 Inharo, Michuhol-Gu, Incheon 22212, KoreaGeometric correction is fundamental in producing high quality satellite data products. However, the geometric correction for ocean color sensors, e.g., Geostationary Ocean Color Imager (GOCI), is challenging because the traditional method based on ground control points (GCPs) cannot be applied when the shoreline is absent. In this study, we develop a hybrid geometric correction method, which applies shoreline matching and frequency matching on slots with shorelines and without shorelines, respectively. Frequency matching has been proposed to estimate the relative orientation between GOCI slots without a shoreline. In this paper, we extend our earlier research for absolute orientation and geometric correction by combining frequency matching results with shoreline matching ones. The proposed method consists of four parts: Initial sensor modeling of slots without shorelines, precise sensor modeling through shoreline matching, relative orientation modeling by frequency matching, and generation of geometric correction results using a combination of the two matching procedures. Initial sensor modeling uses the sensor model equation for GOCI and metadata in order to remove geometric distortion due to the Earth’s rotation and curvature in the slots without shorelines. Precise sensor modeling is performed with shoreline matching and random sample consensus (RANSAC) in the slots with shorelines. Frequency matching computes position shifts for slots without shorelines with respect to the precisely corrected slots with shorelines. GOCI Level 1B scenes are generated by combining the results from shoreline matching and frequency matching. We analyzed the accuracy of shoreline matching alone against that of the combination of shoreline matching and frequency matching. Both methods yielded a similar accuracy of 1.2 km, which supports the idea that frequency matching can replace traditional shoreline matching for slots without visible shorelines.https://www.mdpi.com/1424-8220/18/11/3599GOCIgeometric correctionsensor modelingshoreline matchingfrequency matching
collection DOAJ
language English
format Article
sources DOAJ
author Han-Gyeol Kim
Jong-Hwan Son
Taejung Kim
spellingShingle Han-Gyeol Kim
Jong-Hwan Son
Taejung Kim
Geometric Correction for the Geostationary Ocean Color Imager from a Combination of Shoreline Matching and Frequency Matching
Sensors
GOCI
geometric correction
sensor modeling
shoreline matching
frequency matching
author_facet Han-Gyeol Kim
Jong-Hwan Son
Taejung Kim
author_sort Han-Gyeol Kim
title Geometric Correction for the Geostationary Ocean Color Imager from a Combination of Shoreline Matching and Frequency Matching
title_short Geometric Correction for the Geostationary Ocean Color Imager from a Combination of Shoreline Matching and Frequency Matching
title_full Geometric Correction for the Geostationary Ocean Color Imager from a Combination of Shoreline Matching and Frequency Matching
title_fullStr Geometric Correction for the Geostationary Ocean Color Imager from a Combination of Shoreline Matching and Frequency Matching
title_full_unstemmed Geometric Correction for the Geostationary Ocean Color Imager from a Combination of Shoreline Matching and Frequency Matching
title_sort geometric correction for the geostationary ocean color imager from a combination of shoreline matching and frequency matching
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2018-10-01
description Geometric correction is fundamental in producing high quality satellite data products. However, the geometric correction for ocean color sensors, e.g., Geostationary Ocean Color Imager (GOCI), is challenging because the traditional method based on ground control points (GCPs) cannot be applied when the shoreline is absent. In this study, we develop a hybrid geometric correction method, which applies shoreline matching and frequency matching on slots with shorelines and without shorelines, respectively. Frequency matching has been proposed to estimate the relative orientation between GOCI slots without a shoreline. In this paper, we extend our earlier research for absolute orientation and geometric correction by combining frequency matching results with shoreline matching ones. The proposed method consists of four parts: Initial sensor modeling of slots without shorelines, precise sensor modeling through shoreline matching, relative orientation modeling by frequency matching, and generation of geometric correction results using a combination of the two matching procedures. Initial sensor modeling uses the sensor model equation for GOCI and metadata in order to remove geometric distortion due to the Earth’s rotation and curvature in the slots without shorelines. Precise sensor modeling is performed with shoreline matching and random sample consensus (RANSAC) in the slots with shorelines. Frequency matching computes position shifts for slots without shorelines with respect to the precisely corrected slots with shorelines. GOCI Level 1B scenes are generated by combining the results from shoreline matching and frequency matching. We analyzed the accuracy of shoreline matching alone against that of the combination of shoreline matching and frequency matching. Both methods yielded a similar accuracy of 1.2 km, which supports the idea that frequency matching can replace traditional shoreline matching for slots without visible shorelines.
topic GOCI
geometric correction
sensor modeling
shoreline matching
frequency matching
url https://www.mdpi.com/1424-8220/18/11/3599
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AT taejungkim geometriccorrectionforthegeostationaryoceancolorimagerfromacombinationofshorelinematchingandfrequencymatching
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