• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.118-121
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• 2007

In recent years, the hyperspectral instruments with high spatial and high spectral resolution have become an important component of wide variety of earth science applications. The primary mission of the proposed Compact Airborne Imaging Spectrometer System (CAISS) in this study is to acquire and provide full contiguous spectral information with high quality spectral and spatial resolution for advanced applications in the field of remote sensing. The CAISS will also be used as the vicarious calibration equipment for the cross-calibration of satellite image data. The CAISS consists of six physical units: the camera system, the Jig, the GPS/INS, the gyro-stabilized mount, the operating system, and the power inverter and distributor. Additionally, the calibration instruments such as the integrated sphere and spectral lamps are also prepared for the radiometric and spectral calibration of the CAISS. The CAISS will provide high quality calibrated image data that can support evaluation of satellite application products. This paper summarizes the design, development and major characteristic of the CAISS.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.209-215
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• 2002

Much effort has been made in the radiometric calibration of the ocean scanning multispectral imager (OSMI) since after the successful launch of KOMPSAT-1 in 1999. A series of calibration coefficients for OSMI detectors were obtained in collaboration with the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary (SIMBIOS) project office. In this study, we compare the OSMI level-2 products (e.g., chlorophyll-a concentration) calculated from the NASA cross-calibration coefficients with the SeaWiFS counterparts. Sample study areas are some of diagonostic data sites recommended by the SIMBIOS working group. We will present the preliminary results of this comparative study.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.201-208
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• 2003

Much effort has been made in the radiometric calibration of the ocean scanning multispectral imager (OSMI) since after the successful launch of KOMPSAT-1 in 1999. A series of calibration coefficients for OSMI detectors were obtained in collaboration with the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary (SIMBIOS) project office. In this study, we ompare the OSMI level-2 products (e.g., chorophyll-a concentration) calculated from the NASA cross-calibration coefficients with the SeaWiFS counterparts. Sample study areas are some of diagonostic data sites recommended by the SIMBIOS working group. Results of this study show that the OSMl-derived chlorophyll-a concentration agrees well with the SeaWiFS counterpart in Case 1 water; however, differences become larger in Case 2 water.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.251-262
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• 2010

In order to provide quantitative control of the standard products of Geostationary Ocean Color Imager (GOCI), on-board radiometric correction, atmospheric correction, and bio-optical algorithm are obtained continuously by comprehensive and consistent calibration and validation procedures. The calibration/validation for radiometric, atmospheric, and bio-optical data of GOCI uses temperature, salinity, ocean optics, fluorescence, and turbidity data sets from buoy and platform systems, and periodic oceanic environmental data. For calibration and validation of GOCI, we compared radiometric data between in-situ measurement and HyperSAS data installed in the Ieodo ocean research station, and between HyperSAS and SeaWiFS radiance. HyperSAS data were slightly different in in-situ radiance and irradiance, but they did not have spectral shift in absorption bands. Although all radiance bands measured between HyperSAS and SeaWiFS had an average 25% error, the 11% absolute error was relatively lower when atmospheric correction bands were omitted. This error is related to the SeaWiFS standard atmospheric correction process. We have to consider and improve this error rate for calibration and validation of GOCI. A reference target site around Dokdo Island was used for studying calibration and validation of GOCI. In-situ ocean- and bio-optical data were collected during August and October, 2009. Reflectance spectra around Dokdo Island showed optical characteristic of Case-1 Water. Absorption spectra of chlorophyll, suspended matter, and dissolved organic matter also showed their spectral characteristics. MODIS Aqua-derived chlorophyll-a concentration was well correlated with in-situ fluorometer value, which installed in Dokdo buoy. As we strive to solv the problems of radiometric, atmospheric, and bio-optical correction, it is important to be able to progress and improve the future quality of calibration and validation of GOCI.

• Proceedings of the KSRS Conference
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• v.1
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• pp.274-277
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• 2006

KARI is currently developing a geostationary ocean color imager (GOCI) for COMS. We report the progress in integrated optical modeling and analysis for stray light suppression and the end-to-end instrument performance verification including in-orbit calibration. The Sun is modeled as the emitting light source and the selected area around Korean peninsular as the observation target that scatters the sun light towards GOCI in orbit. The optical ray tracing employing active geometric scaling was then used for precise characterization of the spatial and radiometric performance at the instrument focal plane. The analysis results show positive reduction in the simulated stray light level with the design improvement including baffles. It also indicates that the ray traced in-orbit radiometric performances are effective tools for the independent assessment of more traditional linear and quadratic equation based estimation of water leaving radiance. The concept of integrated GOCI optical model and the computational method are presented.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1629-1634
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• 2020

It is essential to convert the Digital Number (DN) measured from Earth observing satellites into the physical parameter of radiance when deriving the geophysical parameter such as surface temperature in the satellite data processing. The purpose of this study is to update the DN·Radiance equation established from lab measurements, using the KOMPSAT-3A mid-wave infrared data and the MODTRAN radiative transfer model. Results of this study show that the improved DN·Radiance equation allows us to produce the realistic values of radiance. We expect in the forthcoming study that the radiances calculated as such should be more quantitatively validated with the use of relevant in-situ measurements and a radiative transfer model.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1071-1081
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• 2021

Remote Sensing using unmanned aerial vehicles(UAV) can acquire images with higher time resolution and spatial resolution than aerial and satellite remote sensing. However, UAV images are photographed at low altitude and the area covered by one image isrelatively narrow. Therefore multiple images must be processed to monitor large area. Since UAV images are photographed under different exposure conditions, there is difference in brightness values between adjacent images. When images are mosaicked, unnatural seamlines are generated because of the brightness difference. Therefore, in order to generate seamless mosaic image, a radiometric processing for correcting difference in brightness value between images is essential. This paper proposes a relative radiometric calibration and image blending technique. In order to analyze performance of the proposed method, mosaic images of UAV images in agricultural and mountainous areas were generated. As a result, mosaic images with mean brightness difference of 5 and root mean square difference of 7 were avchieved.

• Korean Journal of Remote Sensing
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• v.32 no.1
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• pp.49-60
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• 2016

This paper presents a set of methods to evaluate the image quality of smartphone cameras as compared with that of a DSLR camera. In recent years, smartphone cameras have been used broadly for many purposes. As the performance of smartphone cameras has been enhanced considerably, they can be considered to be used for precise mapping instead of metric cameras. To evaluate the possibility, we tested the quality of one DSLR camera and 3 smartphone cameras. In the first step, we compare the amount of lens distortions inherent in each camera using camera calibration sheet images. Then, we acquired target sheet images, extracted reference lines from them and evaluated the geometric quality of smartphone cameras based on the amount of errors occurring in fitting a straight line to observed points. In addition, we present a method to evaluate the radiometric quality of the images taken by each camera based on planar fitting errors. Also, we propose a method to quantify the geometric quality of the selected camera using edge displacements observed in target sheet images. The experimental results show that the geometric and radiometric qualities of smartphone cameras are comparable to those of a DSLR camera except lens distortion parameters.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1406-1408
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• 2003

KOMPSAT-1 (KOrea Multi-Purpose SATellite ? 1) EOC (Electro Optic Camera) raw images are radiometrically corrected on ground based on the characteristics of EOC. They consist of each CCD (Charge?Coupled Device) pixel’s calibration slope which was measured on ground, electrical gains which are applied to amplify for increasing output pixel counts. Currently, radio-metrically corrected EOC images with calibration slope have still shown defective features by residual stripes. So, it should be compensated by adjusting the calibration slope. In this paper, the adjustment of current calibration slope for de-striping EOC images is addressed and test results are shown.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.