• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.31-44
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• 2009

The objective of this study was to measure backscattering coefficients of paddy rice using a L-, C-, and X-band scatterometer system with full polarization and various angles during the rice growth period and to relate backscattering coefficients to rice growth parameters. Radar backscattering measurements of paddy rice field using multifrequency (L, C, and X) and full polarization were conducted at an experimental field located in National Academy of Agricultural Science (NAAS), Suwon, Korea. The scatterometer system consists of dual-polarimetric square horn antennas, HP8720D vector network analyzer ($20\;MHz{\sim}20\;GHz$), RF cables, and a personal computer that controls frequency, polarization and data storage. The backscattering coefficients were calculated by applying radar equation for the measured at incidence angles between $20^{\circ}$ and $60^{\circ}$ with $5^{\circ}$ interval for four polarization (HH, VV, HV, VH), respectively. We measured the temporal variations of backscattering coefficients of the rice crop at L-, C-, X-band during a rice growth period. In three bands, VV-polarized backscattering coefficients were higher than hh-polarized backscattering coefficients during rooting stage (mid-June) and HH-polarized backscattering coefficients were higher than VV-, HV/VH-polarized backscattering coefficients after panicle initiation stage (mid-July). Cross polarized backscattering coefficients in X-band increased towards the heading stage (mid-Aug) and thereafter saturated, again increased near the harvesting season. Backscattering coefficients of range at X-band were lower than that of L-, C-band. HH-, VV-polarized ${\sigma}^{\circ}$ steadily increased toward panicle initiation stage and thereafter decreased, and again increased near the harvesting season. We plotted the relationship between backscattering coefficients with L-, C-, X-band and rice growth parameters. Biomass was correlated with L-band hh-polarization at a large incident angle. LAI (Leaf Area Index) was highly correlated with C-band HH- and cross-polarizations. Grain weight was correlated with backscattering coefficients of X-band VV-polarization at a large incidence angle. X-band was sensitive to grain maturity during the post heading stage.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.835-848
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• 2021

In Jeju Island which has peculiarity for its geological features and hydrology system, hydrological factor analysis for the effective water management is necessary. Because in-situ hydro-meteorological data is affected by surrounding environment, the in-situ dataset could not be the spatially representative for the study area. For this reason, remote sensing data may be used to overcome the limit of the in-situ data. In this study, applicability assessment of MOD16 evapotranspiration data, Globas Land Data Assimilation System (GLDAS) based evapotranspiration/soil moisture data, and Advanced SCATterometer (ASCAT) soil moisture product which were evaluated their applicability on other study areas was conducted. In the case of evapotranspiration, comparison with total precipitation and flux-tower based evapotranspiration were conducted. And for soil moisture, 6 in-situ data and ASCAT soil moisture product were compared on each site. As a result, 57% of annual precipitation was calculated as evapotranspiration, and the correlation coefficient between MOD16 evapotranspiration and GLDAS evapotranspiration was 0.759, which was a robust value. The correlation coefficient was 0.434, indicating a relatively low fit. In the case of soil moisture, in the case of the GLDAS data, the RMSE value was less than 0.05 at all sites compared to the in-situ data, and a statistically significant result was obtained as a result of the significance test of the correlation coefficient. However, for satellite data, RMSE over than 0.05 were found at Wolgak and there was no correlation at Sehwa and Handong points. It is judged that the above results are due to insufficient quality control and spatial representation of the evapotranspiration and soil moisture sensors installed in Jeju Island. It is estimated as the error that appears when adjacent to the coast. Through this study, the necessity of improving the existing ground observation data of hydrometeorological factors is emphasized.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.325-338
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• 2023

Korean fir (Abies koreana Wilson) is one of the most important environmental indicator tree species for assessing climate change impacts on coniferous forests in the Korean Peninsula. However, due to the nature of alpine and subalpine regions, it is difficult to conduct regular field surveys of Korean fir, which is mainly distributed in regions with altitudes greater than 1,000 m. Therefore, this study analyzed the vegetation change trend of Korean fir using regularly observed remote sensing data. Specifically, normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS), land surface temperature (LST), and precipitation data from Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievalsfor GPM from September 2003 to 2020 for Hallasan and Jirisan were used to analyze vegetation changes and their association with environmental variables. We identified a decrease in NDVI in 2020 compared to 2003 for both sites. Based on the NDVI difference maps, areas for healthy vegetation and high mortality of Korean fir were selected. Long-term NDVI time-series analysis demonstrated that both Hallasan and Jirisan had a decrease in NDVI at the high mortality areas (Hallasan: -0.46, Jirisan: -0.43). Furthermore, when analyzing the long-term fluctuations of Korean fir vegetation through the Hodrick-Prescott filter-applied NDVI, LST, and precipitation, the NDVI difference between the Korean fir healthy vegetation and high mortality sitesincreased with the increasing LST and decreasing precipitation in Hallasan. Thissuggests that the increase in LST and the decrease in precipitation contribute to the decline of Korean fir in Hallasan. In contrast, Jirisan confirmed a long-term trend of declining NDVI in the areas of Korean fir mortality but did not find a significant correlation between the changes in NDVI and environmental variables (LST and precipitation). Further analyses of environmental factors, such as soil moisture, insolation, and wind that have been identified to be related to Korean fir habitats in previous studies should be conducted. This study demonstrated the feasibility of using satellite data for long-term monitoring of Korean fir ecosystems and investigating their changes in conjunction with environmental conditions. Thisstudy provided the potential forsatellite-based monitoring to improve our understanding of the ecology of Korean fir.

• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.501-508
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• 2012

Albedo is known as a factor that directly impacts on the surface energy balance one of the elements of earth radiation balance. The change of albedo includes the change of soil moisture, vegetation, solar zenith angle, snow, and so on. In addition, it operates as a crucial path to understanding feedback mechanisms between radiation balance and its influence on climate and vegetation dynamics and therefore, observing the variation of albedo is a one of the essential procedures for anticipating climate change. In this study, we used MODIS 16-Day composited Albedo data from 2001 to 2011 years with the purpose of observing the change of albedo over Northeast Asia. According to the tendency of albedo for 11 years, albedo in the area of an active vegetation has increased in near-infrared (NIR) domain and decreased in visible (VIS) domain. On the basis of local changes in vegetation in 2002, the both area of the Gobi Desert and the Manchuria was enormously changed and chosen the research area and furthermore, the vegetation of both regions had deteriorated due to the change of the minimum value since 2010.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.743-754
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• 2014

In this present paper, we, for the first time, calculated $SO_2$ inflow from China to Korea peninsula based on OMI $SO_2$ products and HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory Model) backward trajectory calculations. The major factors used to estimate $SO_2$ flux are long range transported $SO_2$ concentration, transport speed of air mass, and thickness of transported air mass layer. The mean and maximum $SO_2$ fluxes are estimated to be 0.81 and $2.11g{\cdot}m^{-2}{\cdot}h^{-1}$, respectively based on OMI products while, those of $SO_2$ fluxes are 0.50 and $1.18g{\cdot}m^{-2}{\cdot}h^{-1}$ respectively using insitu data obtained at the surface. For most cases, larger $SO_2$ inflow values were found at the surface than those estimated for the air mass layer which extends from surface up to 1.5 km. However, increased transport speed of air mass leads to the enhanced $SO_2$ flux at the altitude up to 1.5 km at the receptor sites. Additionally, we calculate uncertainties of $SO_2$ flux using error propagation method.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.947-960
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• 2017

Soil moisture plays an important role to affect the Earth's radiative energy balance and water cycle. In general, satellite observations are useful for estimating the soil moisture content. Passive microwave satellites have an advantage of direct sensitivity on surface soil moisture. However, their coarse spatial resolutions (10-36 km) are not suitable for regional-scale hydrological applications. Meanwhile, in-situ ground observations of point-based soil moisture content have the disadvantage of spatially discontinuous information. This paper presents an experimental soil moisture retrieval using Sentinel-1 SAR (Synthetic Aperture Radar) with 10m spatial resolution for cropland in South Korea. We developed a soil moisture retrieval algorithm based on the technique of linear regression and SVR (support vector regression) using the ground observations at five in-situ sites and Sentinel-1 SAR data from April to October in 2015-2017 period. Our results showed the polarization dependency on the different soil sensitivities at backscattered signals, but no polarization dependence on the accuracies. No particular seasonal characteristics of the soil moisture retrieval imply that soil moisture is generally more affected by hydro-meteorology and land surface characteristics than by phenological factors. At the narrower range of incidence angles, the relationship between the backscattered signal and soil moisture content was more distinct because the decreasing surface interference increased the retrieval accuracies under the condition of evenly distributed soil moisture (during the raining period or on the paddy field). We had an overall error estimate of RMSE (root mean square error) of approximately 6.5%. Our soil moisture retrieval algorithm will be improved if the effects of surface roughness, geomorphology, and soil properties would be considered in the future works.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.73-86
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• 2016

In this study, an algorithm to estimate Aerosol Optical Thickness (AOT) over small cities during nighttime has been developed by using the radiance from artificial light sources in small cities measured from Visible Infrared Imaging Radiometer Suite (VIIRS) sensor's Day/Night Band (DNB) aboard the Suomi-National Polar Partnership (Suomi-NPP) satellite. The algorithm is based on Beer's extinction law with the light sources from the artificial lights over small cities. AOT is retrieved for cloud-free pixels over individual cities, and cloud-screening was conducted by using the measurements from M-bands of VIIRS at infrared wavelengths. The retrieved nighttime AOT is compared with the aerosol products from MODerate resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites. As a result, the correlation coefficients over individual cities range from around 0.6 and 0.7 between the retrieved nighttime AOT and MODIS AOT with Root-Mean-Squared Difference (RMSD) ranged from 0.14 to 0.18. In addition, sensitivity tests were conducted for the factors affecting the nighttime AOT to estimate the range of uncertainty in the nighttime AOT retrievals. The results of this study indicate that it is promising to infer AOT using the DNB measaurements over small cities in Korea at night. After further development and refinement in the future, the developed retrieval algorithm is expected to produce nighttime aerosol information which is not operationally available over Korea.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.235-241
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• 2013

$NO_2$ vertical column densities were retrieved via ground based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements for the first time for 6 months over the spring season in 2007 and 2008 in Seoul, one the megacities in the Northeast Asia. The retrieved $NO_2$ vertical column densities were compared with those obtained from space borneOzone Monitoring Instrument (OMI). Over the entire measurement period, the $NO_2$ vertical column densities measured by MAX-DOAS ranged from $1.0{\times}10^{15}molec{\cdot}cm^{-2}$ to $6.0{\times}10^{16}molec{\cdot}cm^{-2}$ while those obtained by OMI ranged $1.0{\times}10^{15}molec{\cdot}cm^{-2}$ to $7.0{\times}10^{16}molec{\cdot}cm^{-2}$. The correlation coefficient between $NO_2$ vertical column densities obtained from MAX-DOAS and OMI is 0.73 for the entire measurement period whereas the correlation coefficient of 0.85 is found for the dates under the clear sky condition. The cloudy condition is thought to play a major role in increase in uncertainty of the retrieved OMI $NO_2$ vertical column densities since air mass factor may induce high uncertainty due to the lack of cloud and aerosol vertical distribution information.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.749-762
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• 2020

Precipitation is closely related to various hydrometeorological phenomena, such as runoff and evapotranspiration. In Korean Peninsula, observing rainfall intensity using weather radar and rain gauge network is dominating due to their accurate, intuitive and precise detecting power. However,since these methods are not suitable at ungauged regions, rainfall detection using satellite is required. Satellite-based rainfall data has coarse spatial resolution (10 km, 25 km), and has a limited range of usage due to its reliability of data. The aim of this study is to obtain finer scale precipitation. Especially, to make the applicability of satellite higher at ungauged regions, 10 km satellite-based rainfall data was downscaled to 1 km data using MODerate Resolution Imaging Spectroradiometer (MODIS) based cloud property. Downscaled precipitation was verified in urban region, which has complex topographical and environmental characteristics. Correlation coefficient was similar in summer (+0), decreased in spring (-0.08) and autumn (-0.01), and increased in winter (+0.04) season compared to Global Precipitation Measurement (GPM) based precipitation. Downscaling without calibration using in situ data could be useful in areas where rain gauge system is not sufficient or ground observations are rarely available.

• The Korean Journal of Petroleum Geology
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• v.11 no.1 s.12
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• pp.9-17
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• 2005

In the main target area of the block II, Targe-scale faults occur below the unconformity developed around 1 km in depth. The contrast of seismic velocity around the unconformity is generally so large that the strong multiples and the radical velocity variation would deteriorate the quality of migrated section due to serious distortion. More than 15 kinds of data processing techniques have been applied to improve the image resolution for the structures farmed from this active crustal activity. The bad and noisy traces were edited on the common shot gathers in the first step to get rid of acquisition problems which could take place from unfavorable conditions such as climatic change during data acquisition. Correction of amplitude attenuation caused from spherical divergence and inelastic attenuation has been also applied. Mild F/K filter was used to attenuate coherent noise such as guided waves and side scatters. Predictive deconvolution has been applied before stacking to remove peg-leg multiples and water reverberations. The velocity analysis process was conducted at every 2 km interval to analyze migration velocity, and it was iterated to get the high fidelity image. The strum noise caused from streamer was completely removed by applying predictive deconvolution in time space and ${\tau}-P$ domain. Residual multiples caused from thin layer or water bottom were eliminated through parabolic radon transform demultiple process. The migration using curved ray Kirchhoff-style algorithm has been applied to stack data. The velocity obtained after several iteration approach for MVA (migration velocity analysis) was used instead or DMO for the migration velocity. Using various testing methods, optimum seismic processing parameter can be obtained for structural and stratigraphic interpretation in the Block II, Yellow Sea Basin.