• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.214-218
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• 1999

The aim of our study is to develop new algorism for sea fog detection by using Geostational Meteorological Satellite-5(GMS-5) and suggest the techniques of its continuous detection. So as to detect daytime sea fog/stratus(00UTC, May 10, 1999), visible accumulated histogram method and surface albedo method are used. The characteristic value during daytime showed A(min) > 20％ and DA < 10％ when visble accumulated histogram method was applied. And the sea fog region which detected is of similarity in composite image and surface albedo method. In case of nighttime sea fog(18UTC, May 10, 1999), infrared accumulated histogram method and maximum brightness temperature method are used, respectively. Maximum brightness temperature method(T_max method) detected sea fog better than IR accumulated histogram method. In case of T_max method, when infrared value is larger than T_max, fog is detected, where T_max is an unique value, maximum infrared value in each pixel during one month. Then T_max is beneath 700hpa temperature of GDAPS(Global Data Assimilation and Prediction System). Sea fog region which detected by T_max method was similar to the result of National Oceanic and Atmosheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) DCD(Dual Channel Difference). But inland visibility and relative humidity didn't always agreed well.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.04a
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• pp.193-196
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• 2007

The motor case for the KSLV-I KM is the first satellite launch vehicle ever to be developed by Korea to deliver the 100 kg class satellite into Earth's low orbit. This SLV is made of two stages, and the 2nd stage is made of solid rocket motor. The motor case of the KM is made of all composite materials except for the interface structures. Manufacturing process for the motor case such as insulation, filament winding for the motor case, fabrications for the interface structures will be discussed in this paper.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.560-565
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• 2007

Motivated by needs such as those in the aerospace industry, this paper demonstrates ability to significantly increase buckling loads of perforated composite laminated plates by synergizing FEM and a genetic optimization algorithm (GA). Plate geometry is discretized into specially-developed 3D degenerated eight-node shell isoparametric layered composite elements. General shell theory, involving incremental nonlinear finite element equilibrium equation, is employed. Fiber orientation within individual plies of each element is controlled independently by the genetic algorithm. Eigen buckling analysis is performed using the subspace iteration method. Available results demonstrate the approach is superior to more conventional methodologies such as modifying ply thickness or the stacking sequence of individual rectilinear plies having common fiber orientation through the plate.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.228-232
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• 2002

본 연구에서는 다목적 실용위성 2호기에 적용된 금속 구조물 중 알루미늄 샌드위치 패널 구조인 탑재체 플랫폼과 튜브 스트럿(tube strut) 구조에 복합재료 응용기술을 적용하였다. 복합재료 구조로의 대체 설계에서도 관성하중 및 음향진동등과 같은 극심한 발사환경과 더불어 운용하게 될 우주 열환경을 고려하였다. 연구의 목적은 금속소재보다 비강도, 비강성이 우수한 복합재료를 위성 구조물에 사용함으로써 무게를 경량화함에 있다.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2005.11a
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• pp.35-38
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• 2005

The Objective of this work was to design Composite Antenna Structures (CAS) and investigate impact behavior of CAS which was various curvature. This term, CAS, indicates that structural surface becomes antenna. Constituent materials were selected considering electrical properties, dielectric constants and tangent loss as well as mechanical properties. For the antenna performance, microstrip antenna layers inserted into structural layers were designed for satellite communication at the resonant frequency of 12.5 GHz and final demonstration article was. After making five kinds of curved CAS, which radii of curvature are flat, 200, 150, 100, 50 mm. The antenna performance changed in accordance with variation of curvature. The Reflection coefficient was independent of curvature but the gain decreased with the radius of curvature. The impact test equipment was Dyna-8250 drop weight tester. The impact characteristic in accordance with curvature is maximum absorb energy is same each other. The impact energy was 8.5 J. For various Impact energy test, five energy levels 3 J, 5 J, 7 J, 10 J, 20 J were used. The performance of impact damaged antenna was estimated by measuring the return loss and the radiation pattern. It was revealed that the performance of antenna was not related to the impact damage. Because the impactor did not damage the patch directly. CAS have good impact stability for the antenna performance.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.3
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• pp.493-507
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• 2018

Due to high spatio-temporal variability of amount and optical/microphysical properties of atmospheric aerosols, satellite-based observations have been demanded for spatiotemporal monitoring the major aerosols. Observations of the heavy aerosol episodes and determination on the dominant aerosol types from a geostationary satellite can provide a chance to prepare in advance for harmful aerosol episodes as it can repeatedly monitor the temporal evolution. A new geostationary observation sensor, namely the Advanced Himawari Imager (AHI), onboard the Himawari-8 platform, has been observing high spatial and temporal images at sixteen wavelengths from 2016. Using observed spectral visible reflectance and infrared brightness temperature (BT), the algorithm to find major aerosol type such as volcanic ash (VA), desert dust (DD), polluted aerosol (PA), and clean aerosol (CA), was developed. RGB color composite image shows dusty, hazy, and cloudy area then it can be applied for comparing aerosol detection product (ADP). The CALIPSO level 2 vertical feature mask (VFM) data and MODIS level 2 aerosol product are used to be compared with the Himawari-8/AHI ADP. The VFM products can deliver nearly coincident dataset, but not many match-ups can be returned due to presence of clouds and very narrow swath. From the case study, the percent correct (PC) values acquired from this comparisons are 0.76 for DD, 0.99 for PA, 0.87 for CA, respectively. The MODIS L2 Aerosol products can deliver nearly coincident dataset with many collocated locations over ocean and land. Increased accuracy values were acquired in Asian region as POD=0.96 over land and 0.69 over ocean, which were comparable to full disc region as POD=0.93 over land and 0.48 over ocean. The Himawari-8/AHI ADP algorithm is going to be improved continuously as well as the validation efforts will be processed by comparing the larger number of collocation data with another satellite or ground based observation data.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.939-946
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• 2021

Monitoring of post wildfire provides important information for vegetation restoration. In particular, remote sensing data are known to provide useful information necessary for monitoring. However, there are insufficient research results which is monitoring the vegetation recovery using remote sensing data. This study is directed to monitoring post-wildfire vegetation restoration. It proposes a method for monitoring vegetation restoration using Sentinel-2 satellite data by compositing Tasseled Cap linear regression trend in a post wildfire study sites. Although it is a simple visualization technique using satellite images, it was able to confirm the possibility of effective monitoring.

• Composites Research
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• v.28 no.5
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• pp.311-315
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• 2015

Measuring fiber volume fraction properly is very important in designing composite materials because the fiber volume fraction mainly determines mechanical and thermal properties. Conventional Ignition methods are effective for ceramic fiber reinforcing composite materials. However, these methods are not proper for applying to carbon fiber reinforcing composites because of the venerable characteristic against oxidation of carbon fiber. In the research, fiber volume fraction of carbon fiber composites was obtained by a thermogravimetric analysis considering oxidation characteristic of the carbon fiber and the method was compared and verified with the results from microscopic cross section images.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.859-873
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• 2023

Wildfires cause a lot of environmental and economic damage to the Earth over time. Various experiments have examined the harmful effects of wildfires. Also, studies for detecting wildfires and pollutant emissions using satellite remote sensing have been conducted for many years. The wildfire product for the Geostationary Environmental Monitoring Spectrometer (GEMS), Korea's first environmental satellite sensor, has not been provided yet. In this study, a false-color composite for better expression of wildfire smoke was created from GEMS and used in a U-Net model for wildfire detection. Then, a classification model was constructed to distinguish yellow dust from the wildfire smoke candidate pixels. The proposed method can contribute to disaster monitoring using GEMS images.