Geometric Calibration and Validation of Kompsat-3A AEISS-A Camera

Seo, Doochun; Oh, Jaehong; Lee, Changno; Lee, Dong Hoon; Choi, Hae-Jin

doi:10.3390/s16101776

Cited by 16 publications

(7 citation statements)

References 4 publications

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“…The geolocation accuracy assessment will include the effects from focal length deviation. If the focal length deviates from the nominal designed value, it should be corrected by putting the focal length as a geolocation parameter in a look-up table (Tilton et al, 2019;Seo et al, 2016;Wang, et al, 2014).…”

Section: Geometric Calibration and Assessmentmentioning

confidence: 99%

Calibration and Validation for the Surface Biology and Geology (SBG) Mission Concept: Challenges of a Multi-Sensor System for Imaging Spectroscopy and Thermal Imagery

Turpie¹,

Casey²,

Crawford³

et al. 2023

Preprint

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The primary objective of the NASA Surface Biology and Geology (SBG) mission is to measure biological, physical, chemical, and mineralogical features of the Earth's surface, realizing the conceptual component of the envisioned NASA Earth System Observatory (ESO). SBG is planned to launch as a two-platform mission in the late 2020s, the first of the ESO satellites. Targeted science and applications objectives based on observations of the Earth's surface biology and geology helped to define the mission architecture and instrument capabilities for the SBG mission concept. These objectives further drove the need for enabling change detection and trending of surface biological and geological features. These needs implied fundamental Journal of Geophysical Research -Biogeosciences calibration goals to achieve the necessary science data quality characteristics. To meet those goals, calibration and validation pre-launch and on-orbit methods formed a basis of the calibration and validation concept, including the combined use of on-board references, vicarious techniques, and routine lunar imaging. International collaboration with space agencies in other countries, an important feature of the recommended SBG mission architecture, uncovered and emphasized the need for inter-calibration techniques that underscored the importance of collaborative instrument characterization data sharing and the use of common calibration references that are International System of Units (SI) traceable in pre-launch and post-launch on orbit calibration mission phases. International collaboration through the use of terrestrial and aquatic networks on six continents for vicarious calibration and validation activities will produce unprecedented data quality. Table 2 Example reference data sets and models, each supporting geometric calibration (Geo Cal), radiometric calibration (Rad Cal), surface reflectance (Reflectance) or the generation of certain science data products (Science Data), with some supporting more than one. Reference Data Set or Model Purpose Star catalog and planetary ephemeris data Geo Cal Leap second and polar wander that includes (UT1-UTC) Geo Cal Ground Control Point (GCP) database or Global Reference Image (GRI) Geo Cal Time-dependent calibration adjustments Rad Cal Lunar irradiance model (e.g., ROLO, GIRO or LIME)* Rad Cal Solar irradiance spectrum* Rad Cal, Reflectance Instrument char. data (e.g., radiometric, spectral and polarization responses) Rad Cal, Reflectance Vicarious calibration adjustments Reflectance Spectral transmission of absorbing gases (e.g., H2O, O3, NO2). Reflectance Meteorological data (e.g., wind, relative humidity, pressure and temperature) Reflectance Aerosol models Reflectance BRDF models of vicarious calibration sites Reflectance Digital Elevation Model (DEM) and Earth Gravitational Model (e.g., EGM96) Geo Cal Inland water body masks or land/water masks Reflectance Land/sea masks Reflectance Bathymetry Reflectance, Science Data Global shoreline vector data set Science Data Sea surface temperature clima...

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Section: Geometric Calibration and Assessmentmentioning

confidence: 99%

Calibration and Validation for the Surface Biology and Geology (SBG) Mission Concept: Challenges of a Multi-Sensor System for Imaging Spectroscopy and Thermal Imagery

Turpie¹,

Casey²,

Crawford³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The sensor modeling approach tends to show higher accuracy, though the rigorous physical modeling process is more complicated and requires the calibration of both the camera and ephemeris models. Currently, the Korea Aerospace Research Institute (KARI) uses image-matching approaches for pan-sharpening image fusion to show mismatch lower than half a pixel in Root Mean Square Error (RMSE) [12], and seeks a rigorous method to reduce the mismatch.…”

Section: Introductionmentioning

confidence: 99%

Rigorous Co-Registration of KOMPSAT-3 Multispectral and Panchromatic Images for Pan-Sharpening Image Fusion

Lee

2020

Sensors

Self Cite

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KOMPSAT-3, a Korean earth observing satellite, provides the panchromatic (PAN) band and four multispectral (MS) bands. They can be fused to obtain a pan-sharpened image of higher resolution in both the spectral and spatial domain, which is more informative and interpretative for visual inspection. In KOMPSAT-3 Advanced Earth Imaging Sensor System (AEISS) uni-focal camera system, the precise sensor alignment is a prerequisite for the fusion of MS and PAN images because MS and PAN Charge-Coupled Device (CCD) sensors are installed with certain offsets. In addition, exterior effects associated with the ephemeris and terrain elevation lead to the geometric discrepancy between MS and PAN images. Therefore, we propose a rigorous co-registration of KOMPSAT-3 MS and PAN images based on physical sensor modeling. We evaluated the impacts of CCD line offsets, ephemeris, and terrain elevation on the difference in image coordinates. The analysis enables precise co-registration modeling between MS and PAN images. An experiment with KOMPSAT-3 images produced negligible geometric discrepancy between MS and PAN images.

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“…Therefore, the coefficients should also be adjusted by performing a new vicarious calibration for consistent radiance values. Although most studies related to these satellites have focused on the verification and calibration of the imaging sensors [23][24][25][26][27][28][29][30], efforts to improve and conserve the quality of satellite images must be maintained. Therefore, this study performs an absolute radiometric calibration of KOMPSAT-3 and -3A multispectral images from electro-optical imaging sensors to obtain the latest DN to radiance coefficients.…”

Section: Introductionmentioning

confidence: 99%

Updating Absolute Radiometric Characteristics for KOMPSAT-3 and KOMPSAT-3A Multispectral Imaging Sensors Using Well-Characterized Pseudo-Invariant Tarps and Microtops II

Yeom

Hwang

et al. 2018

Remote Sensing

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Radiometric calibration of satellite imaging sensors should be performed periodically to account for the effect of sensor degradation in the space environment on image accuracy. In this study, we performed vicarious radiometric calibrations (relying on in situ data) of multispectral imaging sensors on the Korea multi-purpose satellite-3 and -3A (KOMPSAT-3 and -3A) to adjust the existing radiometric conversion coefficients according to time delay integration (TDI) adjustments and sensor degradation over time. The Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer model was used to obtain theoretical top of atmosphere radiances for both satellites. As input parameters for the 6S model, surface reflectance values of well-characterized pseudo-invariant tarps were measured using dual ASD FieldSpec ® 3 hyperspectral radiometers, and atmospheric conditions were measured using Microtops II ® Sunphotometer and Ozonometer. We updated the digital number (DN) of the radiance coefficients of the satellites; these had been used to calibrate the sensors during in-orbit test periods in 2013 and 2015. The coefficients of determination, R 2 , values between observed DNs of the sensors, and simulated radiances for the tarps were more than 0.999. The calibration errors were approximately 5.7% based on manifested error sources. We expect that the updated coefficients will be an important reference for KOMPSAT-3 and -3A users.

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Geometric Calibration and Validation of Kompsat-3A AEISS-A Camera

Cited by 16 publications

References 4 publications

Calibration and Validation for the Surface Biology and Geology (SBG) Mission Concept: Challenges of a Multi-Sensor System for Imaging Spectroscopy and Thermal Imagery

Calibration and Validation for the Surface Biology and Geology (SBG) Mission Concept: Challenges of a Multi-Sensor System for Imaging Spectroscopy and Thermal Imagery

Rigorous Co-Registration of KOMPSAT-3 Multispectral and Panchromatic Images for Pan-Sharpening Image Fusion

Updating Absolute Radiometric Characteristics for KOMPSAT-3 and KOMPSAT-3A Multispectral Imaging Sensors Using Well-Characterized Pseudo-Invariant Tarps and Microtops II

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