• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.785-791
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• 2020

The radiance measured from satellite has noise due to atmospheric effect. Atmospheric correction is the process of calculating surface reflectance by removing atmospheric effect and surface reflectance is calculated by the Radiative Transfer Model (RTM)-based Look-Up Table (LUT). In general, studies using a LUT make LUT for each channel with the same atmospheric and geometric conditions. However, atmospheric effect of atmospheric factors do not react sensitively in the same channel. In this study, the LUT for each channel of Korea Multi-Purpose SATellite (KOMPSAT)-3/3A was made under the same atmospheric·geometric conditions. And, the accuracy of the LUT was verified by using the simulated Top of Atmosphere radiation and surface reflectance in the RTM. As a result, the relative error of the surface reflectance in the blue channel that sensitive to the aerosol optical depth was 81.14% at the maximum, and 42.67% in the NIR (Near Infrared) channel.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.181-186
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• 2006

Geostationary Orbit satellite, unlike other sun-synchronous polar-orbit satellites, will be able to take a picture of a large region several times a day (almost with everyone hour interval). For geostationary satellite, the target region is fixed though the location of sun is changed always. However, Sun-synchronous polar-orbit satellites able to take a picture of target region same time a everyday. Thus Ocean signal is almost same. Accordingly, the ocean signal of a given target point is largely dependent on time. In other words, the ocean signal detected by geostationary satellite sensor must translate to the signal of target when both sun and satellite are located in nadir, using another correction model. This correction is performed with a standardization of signal throughout relative geometric relationship among satellite-sun-target points. This relative ratio called bidirectional factor. To find relationship between time and $[L_w]_N$/Bidirectional Factor differences, we are calculate solar position, geometry parameters. And reflectance, total radiance at the top of atmosphere(). And water leaving radiance, normalized water leaving radiance. And calculate bidirectional factor, that is the ratio of $[L_w]_N$ between target region and aiming the point. Then, we can make the bidirectional factor lookup table for one year imaging. So, we suggested for necessary to simulation experiment bidirectional factor in more various condition(wavelength and ocean/air condition).

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.449-461
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• 2021

Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.

• Atmosphere
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• v.20 no.4
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• pp.415-426
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• 2010

A Land cover map over East Asian region (Kongju national university Land Cover map: KLC) is classified by using support vector machine (SVM) and evaluated with ground truth data. The basic input data are the recent three years (2006-2008) of MODIS (MODerate Imaging Spectriradiometer) NDVI (normalized difference vegetation index) data. The spatial resolution and temporal frequency of MODIS NDVI are 1km and 16 days, respectively. To minimize the number of cloud contaminated pixels in the MODIS NDVI data, the maximum value composite is applied to the 16 days data. And correction of cloud contaminated pixels based on the spatiotemporal continuity assumption are applied to the monthly NDVI data. To reduce the dataset and improve the classification quality, 9 phenological data, such as, NDVI maximum, amplitude, average, and others, derived from the corrected monthly NDVI data. The 3 types of land cover maps (International Geosphere Biosphere Programme: IGBP, University of Maryland: UMd, and MODIS) were used to build up a "quasi" ground truth data set, which were composed of pixels where the three land cover maps classified as the same land cover type. The classification results show that the fractions of broadleaf trees and grasslands are greater, but those of the croplands and needleleaf trees are smaller compared to those of the IGBP or UMd. The validation results using in-situ observation database show that the percentages of pixels in agreement with the observations are 80%, 77%, 63%, 57% in MODIS, KLC, IGBP, UMd land cover data, respectively. The significant differences in land cover types among the MODIS, IGBP, UMd and KLC are mainly occurred at the southern China and Manchuria, where most of pixels are contaminated by cloud and snow during summer and winter, respectively. It shows that the quality of raw data is one of the most important factors in land cover classification.

• Journal of The Korean Astronomical Society
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• v.42 no.6
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• pp.161-174
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• 2009

Observation of standard stars is of crucial importance in stellar photometry. We have studied the standard transformation relations of the UBV RI CCD photometric system at the Maidanak Astronomical Observatory in Uzbekistan. All observations were made with the AZT-22 1.5m telescope, SITe 2k CCD or Fairchild 486 CCD, and standard Bessell UBV RI filters from 2003 August to 2007 September. We observed many standard stars around the celestial equator observed by SAAO astronomers. The atmospheric extinction coefficients, photometric zero points, and time variation of photometric zero points of each night were determined. Secondary extinction coefficients and photometric zero points were very stable, while primary extinction coefficients showed a distinct seasonal variation. We also determined the transformation coefficients for each filter. For B, V, R, and I filters, the transformation to the SAAO standard system could be achieved with a straight line or a combination of two straight lines. However, in the case of the U filter and Fairchild 486 CCD combination, a significant non-linear correction term - related to the size of Balmer jump or the strength of the Balmer lines - of up to 0:08 mags was required. We found that our data matched well the SAAO photometry in V, B - V, V - I, and R - I. But in U - B, the difference in zero point was about 3.6 mmag and the scatter was about 0.02 mag. We attribute the relatively large scatter in U -B to the larger error in U of the SAAO photometry. We confirm the mostly small differences between the SAAO standard UBV RI system and the Landolt standard system. We also attempted to interpret the seasonal variation of the atmospheric extinction coefficients in the context of scattering sources in the earth's atmosphere.

• Korean Journal of Remote Sensing
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• v.16 no.1
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• pp.37-45
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• 2000

Since being launched for ocean observing in 1997, the SeaWiFS sensor has supplied data on ocean chlorophyll distribution and environmental conditions of the atmosphere. Until now, a lot of SeaWiFS data have been archived and utilized for ocean monitoring and land observation. The SeaWiFS sensor has 1km spatial resolution, therefore, it is difficult to obtain data at the coastal zone. Since atmospheric correction algorithms at the coastal area have not been confirmed for chlorophyll algorithm, the ocean color data analysis for coastal zone is not common. In particular, domestic coastal areas have high suspended sediments concentrations and higher absorption influence of colored dissolved organic matter (CDOM), released from in-land, than open-sea. Thus, a useful algorithm for analysis of chlorophyll distribution in domestic coastal areas has not been developed. In this study, empirical algorithms, using data from the ocean color sensor, were developed for monitoring of chlorophyll distribution of coastal areas. In the process of the development of the algorithms, we can find that the red band (665nm) should be used for analyzing of domestic coastal areas near the Yellow Sea.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1923-1929
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• 2021

Earth observation satellites are being used in various field and are being developed in many countries due to their high utility and marketability. Korea is developing various Earth observation satellites according to National Space Development Plan. Among them, the Korea Multi-Purpose Satellite(KOMPSAT) series is the most representative low-orbit satellite. So far, a total of five KOMPSAT have been launched to meet the national image demand and have been used in various fields, including national institutions. This special issue introduces research related to data processing, analysis, and utilization using various image data from the KOMPSAT series. Meanwhile, for the uninterrupted utilization of the subsequent KOMPSAT image data, data processing and utilization research suitable for high-resolution images must be continued, and related research contents will be continuously shared through a special issue.

• Atmosphere
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• v.31 no.1
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• pp.85-100
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• 2021

The necessity of accurate high-resolution meteorological forecasts becomes increasing in socio-economical applications and disaster risk management. The Korea Meteorological Administration Post-Processing (KMAPP) system has been operated to provide high-resolution meteorological forecasts of 100 m over the South Korea region. This study evaluates and improves the KMAPP performance in simulating wind speeds over complex terrain areas using the ICE-POP 2018 field campaign measurements. The mountainous measurements give a unique opportunity to evaluate the operational wind speed forecasts over the complex terrain area. The one-month wintertime forecasts revealed that the operational Local Data Assimilation and Prediction System (LDAPS) has systematic errors over the complex mountainous area, especially in deep valley areas, due to the orographic smoothing effect. The KMAPP reproduced the orographic height variation over the complex terrain area but failed to reduce the wind speed forecast errors of the LDAPS model. It even showed unreasonable values (~0.1 m s-1) for deep valley sites due to topographic overcorrection. The model's static parameters have been revised and applied to the KMAPP-Wind system, developed newly in this study, to represent the local topographic characteristics better over the region. Besides, sensitivity tests were conducted to investigate the effects of the model's physical correction methods. The KMAPP-Wind system showed better performance in predicting near-surface wind speed during the ICE-POP period than the original KMAPP version, reducing the forecast error by 21.2%. It suggests that a realistic representation of the topographic parameters is a prerequisite for the physical downscaling of near-ground wind speed over complex terrain areas.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.21-32
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• 2022

The importance of the classical theme of how the Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance of high-resolution satellite images match the actual atmospheric reflectance and surface reflectance has been emphasized. Based on the Radiometric Calibration Network (RadCalNet) BTCN and BSCN data, this study compared the accuracy of TOA and TOC reflectance products of the currently available optical satellites, including KOMPSAT-3, WorldView-2, and Pléiades-1A image sets calculated using the absolute atmospheric correction function of the Orfeo Toolbox (OTB) tool. The comparison experiment used data in 2018 and 2019, and the Landsat-8 image sets from the same period were applied together. The experiment results showed that the product of TOA and TOC reflectance obtained from the three sets of images were highly consistent with RadCalNet data. It implies that any imagery may be applied when high-resolution reflectance products are required for a certain application. Meanwhile, the processed results of the OTB tool and those by the Apparent Reflection method of another tool for WorldView-2 images were nearly identical. However, in some cases, the reflectance products of Landsat-8 images provided by USGS sometimes showed relatively low consistency than those computed by the OTB tool, with the reference of RadCalNet BTCN and BSCN data. Continuous experiments on active vegetation areas in addition to the RadCalNet sites are necessary to obtain generalized results.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.32-40
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• 2022

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.