• Journal of the Korean earth science society
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• v.33 no.2
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• pp.113-125
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• 2012

The estimations of the surface rain intensity and rain-related physical variables derived from two independent Tropical Rainfall Measuring Mission (TRMM) satellite sensors, TRMM Microwave Imager (TMI) and Precipitation Radar (PR), were compared over four different oceans. The precipitating clouds developed most frequently in the warmest sea surface temperature (SST) region of the west Pacific, which is 1.5 times more frequent than in the east Pacific and the tropical Atlantic oceans. However, the east Pacific exhibited the most intense rain intensity for the convective and mixed rain types while the tropical Atlantic showed the most intense rain intensity for all TMI rainy pixels. It was found that the deviation of TMI-derived rain rate yielded a big difference in region-to-region and rain type-to-type if the PR rain intensity value is assumed to be closer to the truth. Furthermore, the deviation by rain types showed opposite signs between convective and non-convective rain types. It was found that the region-to-region deviation differences reached more than 200% even though the selected tropical oceans have relatively similar geophysical environments. Therefore, the validation for the microwave rain estimation needs to be performed according to both rain types and climate regimes, and it also requires more sophisticated TMI algorithm which reflects the locality of rainfall characteristics.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.487-501
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• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.1
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• pp.18-26
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• 2001

Landsat TM band ratio algorithms were made by in-water optical measurement data of each sampling points for water quality monitoring of coastal area using Landsat TM satellite data. The algorithm was derived from in-water optical reflectance data which was measuring by the PRR(profiling reflectance radiometer). And, in-water optical reflectance data were applied to Landsat TM bands. Relationship between in-water optical reflectance and pigments proposed by the ratio of TM band 1 and band 2 showed to as follows; $Y=3.8352{\times}(R(band\;1)/R(band\;2))^{-2.1978}$ ($R^2$=0.7069) and, relationship of the ratio of TM band 1 and band 3 as follows; $Y=23.288{\times}(R(band\;1)/R(band\;3))^{-1.5243}$ ($R^2$=0.8062). Calculated the upwelling radiance of water surface and radiance of TM showed the ratio of atmospheric effect. In the coastal area Rayleigh and Mie scattering of atmosphere is to make over 80% of normalized radiance of Landsat TM. In order to apply in-water algorithm obtained by PRR, we had to calculate the atmospheric effects at sampling site. And, the quantitative analysis of in-water components using Landsat TM data need the calibration of in-water algorithm and effective method of atmospheric correction.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.1
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• pp.56-64
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• 2008

Although the EGSE (Electrical Ground Support Equipment) and MCS (Mission Control System) have many similar or even identical functions, the EGSE used for assembly, integration and validation phase and the MCS for the mission operations phase are normally developed separately and used by different groups of engineers. However, the common ground system for EGSE and MCS has developed and many space missions such as PROBA (PRoject for On-Board Autonomy), ROSETTA, MARS EXPRESS, CRYOSAT (Cryosphere Satellite), GOCE (Gravity field and steady state Ocean Circulation Explorer), and GALILEO have used or will use it to minimize risk, reduce cost and improve overall product quality. It is based on ECSS (European Cooperation for Space Standards) E70 which is the international standard for ground systems and operations published by ECSS E70 Working Group. The ECSS E70 contains the basic rules, principles and requirements applied to the engineering of the ground systems and the execution of mission operations. This paper introduces standardization policy, organization and standard documentation in ECSS. The overview of ECSS E70 such as status, purpose and contents is also described in this paper.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.2
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• pp.231-243
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• 2016

This study presents the applicability of two-dimensional (2D) flood inundation model by applying to real irrigation reservoir failure with limited available data. The study area is Sandae Reservoir placed in Gyeongju and downstream area of it and the reservoir was failured by piping in 2013. The breach hydrograph was estimated from one-dimensional (1D) hydrodynamic model and the discharge was employed for upstream boundary of 2D flood inundation model. Topography of study area was generated by integrating digital contour map and satellite data, and Cartesian grids with 3m resolution to consider geometry of building, road and public stadium were used for 2D flood inundation analysis. The model validation was carried out by comparing predictions with field survey data including reservoir breach outflow, flood extent, flood height and arrival time, and identifying rational ranges with allowed error. In addition, the applicability of 2D model is examined using different simulation conditions involving grid size, building and roughness coefficient. This study is expected to contributed to analysis of irrigation reservoirs were at risk of a failure and setting up Emergency Action Plan (EAP) against irrigation reservoir failure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.658-663
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• 2018

Current measuring methods for air quality are based on ground measurement networks and satellite data. New methods of collecting evidence with advanced sensors are needed because current methods have limitations in collecting evidence for the illegal emission of air pollutants at narrow areas or specific sites. This study analyzed the possibility of using an ultraviolet hyperspectral sensor to measure the concentration of nitrogen dioxide and sulfur dioxide. Two types of spectra were used: simulated spectra for gases with various concentrations using a radiative transfer model and observed spectra for each gas for a concentration. To understand the possibility of using a hyperspectral sensor, the differences between the simulated spectra and the observed spectra were analyzed, and the variation of simulated spectra were then analyzed according to the concentration. The results showed good agreement between observed spectra and simulated spectra. In addition, the absorption depth at specific wavelengths in the simulated spectra had a very strong correlation with the gas concentration. The gas concentration could be estimated using the hyperspectral sensor. In the future, validation would be needed to estimate the gas concentration through observations of various concentrations of gases using a hyperspectral sensor.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.523-535
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• 2011

The precipitable water vapor (PW) was estimated using Global Navigation Satellite System (GNSS) from several GNSS stations within the Korean Peninsula. Nearby radiosonde sites covering the GNSS stations were used for the comparison and validation of test results. GNSS data recorded under typical and severe weather conditions were used to generalize our approach. Based on the analysis, we have confirmed that the derived PW values from the GNSS observables were well agreed on the estimates from the radiosonde observables within 10 mm level. Assuming that the GNSS observables could be a good weather monitoring tool, we further tested the performance of the current WAAS tropospheric delay model, UNB3, in the Korean Peninsula. Especially, the wet zenith delays estimated from the GNSS observables and from UNB3 delay model were compared. Test results showed that the modelled approach for the troposphere (i.e., UNB3) did not perform well especially under the wet weather conditions in the Korean Peninsula. It was suggested that a new model or a near real-time model (e.g., based on regional model from GNSS or numerical weather model) would be highly desirable for the Korean WA-DGNSS to minimize the effects of the tropospheric delay and hence to achieve high precision vertical navigation solutions.

• Atmosphere
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• v.26 no.1
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• pp.111-126
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• 2016

In the numerical weather model, surface properties can be defined by various parameters such as terrain height, landuse, surface albedo, soil moisture, surface emissivity, roughness length and so on. And these parameters need to be improved in the Seoul metropolitan area that established high-rise and complex buildings by urbanization at a recent time. The surface roughness length map is developed from digital elevation model (DEM) and it is implemented to the high-resolution numerical weather (WISE-WRF) model. Simulated results from WISE-WRF model are analyzed the relationship between meteorological variables to changes in the surface roughness length. Friction speed and wind speed are improved with various surface roughness in urban, these variables affected to temperature and relative humidity and hence the surface roughness length will affect to the precipitation and Planetary Boundary Layer (PBL) height. When surface variables by the WISE-WRF model are validated with Automatic Weather System (AWS) observations, NEW experiment is able to simulate more accurate than ORG experiment in temperature and wind speed. Especially, wind speed is overestimated over $2.5m\;s^{-1}$ on some AWS stations in Seoul and surrounding area but it improved with positive correlation and Root Mean Square Error (RMSE) below $2.5m\;s^{-1}$ in whole area. There are close relationship between surface roughness length and wind speed, and the change of surface variables lead to the change of location and duration of precipitation. As a result, the accuracy of WISE-WRF model is improved with the new surface roughness length retrieved from DEM, and its surface roughness length is important role in the high-resolution WISE-WRF model. By the way, the result in this study need various validation from retrieved the surface roughness length to numerical weather model simulations with observation data.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1307-1315
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• 2021

The Changjiang Diluted Water (CDW) spreads over the East China Sea every summer and significantly affects the sea surface salinity changes in the seas around Jeju Island and the southern coast of Korea peninsula. Sometimes its effect extends to the eastern coast of Korea peninsula through the Korea Strait. Specifically, the CDW has a significant impact on marine physics and ecology and causes damage to fisheries and aquaculture. However, due to the limited field surveys, continuous observation of the CDW in the East China Sea is practically difficult. Many studies have been conducted using satellite measurements to monitor CDW distribution in near-real time. In this study, an algorithm for estimating Sea Surface Salinity (SSS) in the East China Sea was developed using the Geostationary Ocean Color Imager (GOCI). The Multilayer Perceptron Neural Network (MPNN) method was employed for developing an algorithm, and Soil Moisture Active Passive (SMAP) SSS data was selected for the output. In the previous study, an algorithm for estimating SSS using GOCI was trained by 2016 observation data. By comparison, the train data period was extended from 2015 to 2020 to improve the algorithm performance. The validation results with the National Institute of Fisheries Science (NIFS) serial oceanographic observation data from 2011 to 2019 show 0.61 of coefficient of determination (R²) and 1.08 psu of Root Mean Square Errors (RMSE). This study was carried out to develop an algorithm for monitoring the surface salinity of the East China Sea using GOCI and is expected to contribute to the development of the algorithm for estimating SSS by using GOCI-II.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1329-1350
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• 2018

There have been many applications to observe Earth using synthetic aperture radar (SAR) since it could acquire Earth observation data without reference to weathers or local times. However researches about digital map generation using SAR have hardly been performed due to complex raw data processing. In this study, we suggested feasibility of producing digital map using SAR stereo images. We collected two sets, which include an ascending and a descending orbit acquisitions respectively, of KOMPSAT-5 stereo dataset. In order to suggest the feasibility of digital map generation from SAR stereo images, we performed 1) rational polynomial coefficient transformation from radar geometry, 2) digital resititution using KOMPSAT-5 stereo images, and 3) validation using digital-map-derived reference points and check points. As the results of two models, root mean squared errors of XY and Z direction were less than 1m for each model. We discussed that KOMPSAT-5 stereo image could generated 1:25,000 digital map which meets a standard of the digital map. The proposed results would contribute to generate and update digital maps for inaccessible areas and wherever weather conditions are unstable such as North Korea or Polar region.