• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.237-248
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• 2018

The vertical distribution of hydrometeor before precipitation near the cloud base has been analyzed using a scanning lidar, rawinsonde data, and Cloud-Resolving Storm Simulator (CReSS). This study mostly focuses on 13 Desember 2016 only. The typical synoptic pattern of lake-effect snowstorm induced easterly in the Yeongdong region. Clouds generated due to high temperature difference between 850 hPa and sea surface (SST) penentrated in the Yeongdong region along with northerly and northeasterly, which eventually resulted precipitation. The cloud base height before the precipitation changed from 750 m to 1,280 m, which was in agreement with that from ceilometer at Sokcho. However, ceilometer tended to detect the cloud base 50 m ~ 100 m below strong signal of lidar backscattering coefficient. As a result, the depolarization ratio increased vertically while the backscattering coefficient decreased about 1,010 m~1,200 m above the ground. Lidar signal might be interpreted to be attenuated with the penetration depth of the cloud layer with of nonspherical hydrometeor (snow, ice cloud). An increase in backscattering signal and a decrease in depolarization ratio occured in the layer of 800 to 1,010 m, probably being associated with an increase in non-spherical particles. There seemed to be a shallow liquid layer with a low depolarization ratio (<0.1) in the layer of 850~900 m. As the altitude increases in the 680 m~850 m, the backscattering coefficient and depolarization ratio increase at the same time. In this range of height, the maximum value (0.6) is displayed. Such a result can be inferred that the nonspherical hydrometeor are distributed by a low density. At this time, the depolarization ratio and the backscattering coefficient did not increase under observed melting layer of 680 m. The lidar has a disadvantage that it is difficult for its beam to penetrate deep into clouds due to attenuation problem. However it is promising to distinguish hydrometeor morphology by utilizing the depolarization ratio and the backscattering coefficient, since its vertical high resolution (2.5 m) enable us to analyze detailed cloud microphysics. It would contribute to understanding cloud microphysics of cold clouds and snowfall when remote sensings including lidar, radar, and in-situ measurements could be timely utilized altogether.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.499-506
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• 2019

NDSM (Normalized Digital Surface Model) is key information for the detailed analysis of remote sensing data. Although NDSM can be simply obtained by subtracting a DTM (Digital Terrain Model) from a DSM (Digital Surface Model), in case of UAV (Unmanned Aerial Vehicle) data, it is difficult to get an accurate DTM due to high resolution characteristics of UAV data containing a large number of complex objects on the ground such as vegetation and urban structures. In this study, RGB-based UAV vegetation index, ExG (Excess Green) was used to extract initial seed points having low ExG values for region growing such that a DTM can be generated cost-effectively based on high resolution UAV data. For this process, local window analysis was applied to resolve the problem of erroneous seed point extraction from local low ExG points. Using the DSM values of seed points, region growing was applied to merge neighboring terrain pixels. Slope criteria were adopted for the region growing process and the seed points were determined as terrain points in case the size of segments is larger than 0.25 ㎡. Various slope criteria were tested to derive the optimized value for UAV data-based NDSM generation. Finally, the extracted terrain points were evaluated and interpolation was performed using the terrain points to generate an NDSM. The proposed method was applied to agricultural area in order to extract the above ground heights of crops and check feasibility of agricultural monitoring.

• Atmosphere
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• v.15 no.2
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• pp.101-118
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• 2005

Atmospheric ozone changes temporally and spatially according to both anthropogenic and natural causes. It is essential to quantify the natural contributions to total ozone variations for the estimation of trend caused by anthropogenic processes. The aims of this study are to understand the intrinsic natural variability of long-term total ozone changes and to estimate more reliable ozone trend caused by anthropogenic ozone-depleting materials. For doing that, long-term time series for Seoul of monthly total ozone which were measured from both ground-based Dobson Spectrophotometer (Beck #124)(1985-2004) and satellite TOMS (1979-1984) are analyzed for selected period, after dividing the whole period (1979~2004) into two periods; the former period (1979~1991) and the latter period (1992~2004). In this study, ozone trends for the time series are calculated using multiple regression models with explanatory natural oscillations for the Arctic Oscillation(AO), North Atlantic Oscillation(NAO), North Pacific Oscillation(NPO), Pacific Decadal Oscillation(PDO), Quasi Biennial Oscillation(QBO), Southern Oscillation(SO), and Solar Cycle(SC) including tropopause pressure(TROPP). Using the developed models, more reliable anthropogenic ozone trend is estimated than previous studies that considered only QBO and SC as natural oscillations (eg; WMO, 1999). The quasi-anthropogenic ozone trend in Seoul is estimated to -0.12 %/decade during the whole period, -2.39 %/decade during the former period, and +0.10 %/decade during the latter period, respectively. Consequently, the net forcing mechanism of the natural oscillations on the ozone variability might be noticeably different in two time intervals with positive forcing for the former period (1979-1991) and negative forcing for the latter period (1992-2004). These results are also found to be consistent with those analyzed from the data observed at ground stations (Sapporo, Tateno) of Japan. In addition, the recent trend analyses for Seoul show positive change-in-trend estimates of +0.75 %/decade since 1997 relative to negative trend of -1.49 %/decade existing prior to 1997, showing -0.74 %/decade for the recent 8-year period since 1997. Also, additional supporting evidence for a slowdown in ozone depletion in the upper stratosphere has been obtained by Newchurch et al.(2003).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.9
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• pp.914-923
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• 2009

Helix antennas have been widely applied to satellite TT&C, data communication and GPS receiver systems onboard military, remote sensing and communication purpose satellites. The helix antennas are known to be convenient to control impedance and radiation coverage characteristics with a maximum directivity in satellite z-axis. Waveguide horn is commonly used for radar system that needs ultra-wideband pulse for exploration ground radar and electromagnetic disability measurement etc. It has high efficiency and low reflection characteristics provided by the low-profile shape and suppressed radiation distortion. In this paper, a waveguide horn structure incorporated with helix antenna design is proposed for satellite applications that require ultra-wideband pulse radar and high rate RF data communication link to ground station over wide coverage area. The main design concern is to synthesize variable beam forming pattern based on modified horn-helix combination helicone structure such that multi-mission antenna is implemented applicable for TT&C, earth observation, high data rate transmission. Waveguide horn helps to reduce the overall antenna structure size by introduction fold type reflector connected to the tapered helix antenna. The next generation KOMPSAT satellite currently under development requires high-performance precision attitude control system. We present an initial design of a hybrid hern-helix antenna structure suitable for efficient RF communication module design of multi-purpose satellite systems.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.127-134
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• 2012

Microwave remote sensing can help monitor the land surface water cycle, crop growth and soil moisture. A ground-based polarimetric scatterometer has an advantage for continuous crop using multi-polarization and multi-frequencies and various incident angles have been used extensively in a frequency range expanding from L-band to Ka-band. In this study, we analyzed the relationships between L-, C- and X-band signatures and soil moisture content over the whole soybean growth period. Polarimetric backscatter data at L-, C- and X-bands were acquired every 10 minutes. L-band backscattering coefficients were higher than those observed using C- or X-band over the period. Backscattering coefficients for all frequencies and polarizations increased until Day Of Year (DOY) 271 and then decreased until harvesting stage (DOY 294). Time serious of soil moisture content was not a corresponding with backscattering over the whole growth stage, although it increased relatively until early August (R2, DOY 224). We conducted the relationship between the backscattering coefficients of each band and soil moisture content. Backscattering coefficients for all frequencies were not correlated with soil moisture content when considered over the entire stage ($r{\leq}0.50$). However, we found that L-band HH polarization was correlated with soil moisture content (r=0.90) when Leaf Area Index (LAI)<2. Retrieval equations were developed for estimating soil moisture content using L-band HH polarization. Relation between L-HH and soil moisture shows exponential pattern and highly related with soil moisture content ($R^2=0.92$). Results from this study show that backscattering coefficients of radar scatterometer appear effective to estimate soil moisture content.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.109-126
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• 2014

We improved the Land Surface Emissivity (LSE) data (Kongju National University LSE v.2: KNULSE_v2) over the Communication, Ocean and Meteorological Satellite (COMS) observation region using recent(2009-2012) Moderate Resolution Imaging Spectroradiometer (MODIS) data. The surface emissivity was derived using the Vegetation Cover Method (VCM) based on the assumption that the pixel is only composed of ground and vegetation. The main issues addressed in this study are as follows: 1) the impacts of snow cover are included using Normalized Difference Snow Index (NDSI) data, 2) the number of channels is extended from two (11, 12 ${\mu}m$) to four channels (3.7, 8.7, 11, 12 ${\mu}m$), 3) the land cover map data is also updated using the optimized remapping of the five state-of-the-art land cover maps, and 4) the latest look-up table for the emissivity of land surface according to the land cover is used. The updated emissivity data showed a strong seasonal variation with high and low values for the summer and winter, respectively. However, the surface emissivity over the desert or evergreen tree areas showed a relatively weak seasonal variation irrespective of the channels. The snow cover generally increases the emissivity of 3.7, 8.7, and 11 ${\mu}m$ but decreases that of 12 ${\mu}m$. As the results show, the pattern correlation between the updated emissivity data and the MODIS LSE data is clearly increased for the winter season, in particular, the 11 ${\mu}m$. However, the differences between the two emissivity data are slightly increased with a maximum increase in the 3.7 ${\mu}m$. The emissivity data updated in this study can be used for the improvement of accuracy of land surface temperature derived from the infrared channel data of COMS.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.451-463
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• 2018

The empirical/statistical models to estimate the ground Particulate Matter ($PM_{2.5}$) concentration from Geostationary Ocean Color Imager (GOCI) Aerosol Optical Depth (AOD) product were developed and analyzed for the period of 2015 in Seoul, South Korea. In the model construction of AOD-$PM_{2.5}$, two vertical correction methods using the planetary boundary layer height and the vertical ratio of aerosol, and humidity correction method using the hygroscopic growth factor were applied to respective models. The vertical correction for AOD and humidity correction for $PM_{2.5}$ concentration played an important role in improving accuracy of overall estimation. The multiple linear regression (MLR) models with additional meteorological factors (wind speed, visibility, and air temperature) affecting AOD and $PM_{2.5}$ relationships were constructed for the whole year and each season. As a result, determination coefficients of MLR models were significantly increased, compared to those of empirical models. In this study, we analyzed the seasonal, monthly and diurnal characteristics of AOD-$PM_{2.5}$model. when the MLR model is seasonally constructed, underestimation tendency in high $PM_{2.5}$ cases for the whole year were improved. The monthly and diurnal patterns of observed $PM_{2.5}$ and estimated $PM_{2.5}$ were similar. The results of this study, which estimates surface $PM_{2.5}$ concentration using geostationary satellite AOD, are expected to be applicable to the future GK-2A and GK-2B.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.679-692
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• 2020

We coupled a CFD model to the WRF-Chem model (WRF-CFD model) and investigated the characteristics of flows and carbon monoxide (CO) distributions in a building-congested district. We validated the simulated results against the measured wind speeds, wind directions, and CO concentrations. The WRF-Chem model simulated the winds from southwesterly to southeasterly, overestimating the measured wind speeds. The statistical validation showed that the WRF-CFD model simulated the measured wind speeds more realistically than the WRF-Chem model. The WRF-Chem model significantly underestimated the measured CO concentrations, and the WRF-CFD model improved the CO concentration prediction. Based on the statistical validation results, the WRF-CFD model improved the performance in predicting the CO concentrations by taking complicatedly distributed buildings and mobiles sources of CO into account. At 04 KST on May 22, there was a downdraft around the AQMS, and airflow with a relatively low CO concentration was advected from the upper layer. Resultantly, the CO concentration was lower at the AQMS than the surrounding area. At 15 KST on May 22, there was an updraft around the AQMS. This resulted in a slightly higher CO concentration than the surroundings. The WRF-CFD model transported CO emitted from the mobile sources to the AQMS measurement altitude, well reproducing the measured CO concentration. At 18 KST on May 22, the WRF-CFD model simulated high CO concentrations because of high CO emission, broad updraft area, and an increase in turbulent diffusion cause by wind-shear increase near the ground.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.467-480
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• 2011

Spatial and temporal variabilities of NPP(Net Primary Production) retrieved from two satellite instruments, AVHRR(Advanced Very High Resolution Radiometer, 1981-2000) and MODIS(MODerate-resolution Imaging Spectroradiometer, 2000-2006), were investigated. The range of mean NPP from A VHRR and MODIS were estimated to be 894-1068 $g{\cdot}C/m^2$/yr and 610-694.90 $g{\cdot}C/m^2$/yr, respectively. The discrepancy of NPP between the two instruments is about 325 $g{\cdot}C/m^2$/yr, and MODIS product is generally closer to the ground measurement than AVHRR despite the limitation in direct comparison such as spatial resolution and vegetation classification. The higher NPP values over South Korea are related to the regions with higher biomass (e.g., mountains) and higher annual temperature. The interannual NPP trends from the two satellite products were computed, and both mean annual trends show continuous NPP increase; 2.14 $g{\cdot}C/m^2$/yr from AVHRR(1981-2000) and 6.08 $g{\cdot}C/m^2$/yr from MODIS (2000-2006) over South Korea. Specifically, the higher increasing trends over the Southwestern region are likely due to the increasing productivity of crop fields from sufficient irrigation and fertilizer use. The retrieved NPP shows a closer relationship between monthly temperature and precipitation, which results in maximum correlation during summer monsoons. The difference in the detection wavelength and model schemes during the retrieval can make a significant difference in the satellite products, and a better accuracy in the meterological and land use data and modeling applications will be necessary to improve the satellite-based NPP data.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.933-944
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• 2019

This study analyzes the tide deformation of land boundary regions on the east (Region A) and west (Region B) sides of the Ross Ice Shelf in Antarctica using Double-Differential Interferometric Synthetic Aperture Radar (DDInSAR). A total of seven Sentinel-1A SAR images acquired in 2015-2016 were used to estimate the accuracy of tide prediction model and Young's modulus of ice shelf. First, we compared the Ross Sea Height-based Tidal Inverse (Ross_Inv) model, which is a representative tide prediction model for the Antarctic Ross Sea, with the tide deformation of the ice shelf extracted from the DDInSAR image. The accuracy was analyzed as 3.86 cm in the east region of Ross Ice Shelf and it was confirmed that the inverse barometric pressure effect must be corrected in the tide model. However, in the east, it is confirmed that the tide model may be inaccurate because a large error occurs even after correction of the atmospheric effect. In addition, the Young's modulus of the ice was calculated on the basis of the one-dimensional elastic beam model showing the correlation between the width of the hinge zone where the tide strain occurs and the ice thickness. For this purpose, the grounding line is defined as the line where the displacement caused by the tide appears in the DDInSAR image, and the hinge line is defined as the line to have the local maximum/minimum deformation, and the hinge zone as the area between the two lines. According to the one-dimensional elastic beam model assuming a semi-infinite plane, the width of the hinge region is directly proportional to the 0.75 power of the ice thickness. The width of the hinge zone was measured in the area where the ground line and the hinge line were close to the straight line shown in DDInSAR. The linear regression analysis with the 0.75 power of BEDMAP2 ice thickness estimated the Young's modulus of 1.77±0.73 GPa in the east and west of the Ross Ice Shelf. In this way, more accurate Young's modulus can be estimated by accumulating Sentinel-1 images in the future.