• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.135-147
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• 2017

We, for the first time, estimated daily and monthly surface nitrogen dioxide ($NO_2$) volume mixing ratio (VMR) using three regression models with $NO_2$ tropospheric vertical column density (OMIT-rop $NO_2$ VCD) data obtained from Ozone Monitoring Instrument (OMI) in Seoul in South Korea at OMI overpass time (13:45 local time). First linear regression model (M1) is a linear regression equation between OMI-Trop $NO_2$ VCD and in situ $NO_2$ VMR, whereas second linear regression model (M2) incorporates boundary layer height (BLH), temperature, and pressure obtained from Atmospheric Infrared Sounder (AIRS) and OMI-Trop $NO_2$ VCD. Last models (M3M & M3D) are a multiple linear regression equations which include OMI-Trop $NO_2$ VCD, BLH and various meteorological data. In this study, we determined three types of regression models for the training period between 2009 and 2011, and the performance of those regression models was evaluated via comparison with the surface $NO_2$ VMR data obtained from in situ measurements (in situ $NO_2$ VMR) in 2012. The monthly mean surface $NO_2$ VMRs estimated by M3M showed good agreements with those of in situ measurements(avg. R = 0.77). In terms of the daily (13:45LT) $NO_2$ estimation, the highest correlations were found between the daily surface $NO_2$ VMRs estimated by M3D and in-situ $NO_2$ VMRs (avg. R = 0.55). The estimated surface $NO_2$ VMRs by three modelstend to be underestimated. We also discussed the performance of these empirical modelsfor surface $NO_2$ VMR estimation with respect to otherstatistical data such asroot mean square error (RMSE), mean bias, mean absolute error (MAE), and percent difference. This present study shows a possibility of estimating surface $NO_2$ VMR using the satellite measurement.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1181-1189
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• 2022

Clouds are composed of tiny water droplets, ice crystals, or mixtures suspended in the atmosphere and cover about two-thirds of the Earth's surface. Cloud detection in satellite images is a very difficult task to separate clouds and non-cloud areas because of similar reflectance characteristics to some other ground objects or the ground surface. In contrast to thick clouds, which have distinct characteristics, thin transparent clouds have weak contrast between clouds and background in satellite images and appear mixed with the ground surface. In order to overcome the limitations of transparent clouds in cloud detection, this study conducted cloud detection focusing on transparent clouds using machine learning techniques (Random Forest [RF], Convolutional Neural Networks [CNN]). As reference data, Cloud Mask and Cirrus Mask were used in MOD35 data provided by MOderate Resolution Imaging Spectroradiometer (MODIS), and the pixel ratio of training data was configured to be about 1:1:1 for clouds, transparent clouds, and clear sky for model training considering transparent cloud pixels. As a result of the qualitative comparison of the study, bothRF and CNN successfully detected various types of clouds, including transparent clouds, and in the case of RF+CNN, which mixed the results of the RF model and the CNN model, the cloud detection was well performed, and was confirmed that the limitations of the model were improved. As a quantitative result of the study, the overall accuracy (OA) value of RF was 92%, CNN showed 94.11%, and RF+CNN showed 94.29% accuracy.

• Korean Journal of Environmental Biology
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• v.37 no.3
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• pp.299-308
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• 2019

The occurrence patterns of Acartia(Copepoda; Calanoida) species, A. erythraea, A. hongi, A. hudsonica, A. ohtsukai, and A. sinjiensis, were examined in the southern coastal waters of Korea in the summer in August 2012. The Acartia species had different spatial distribution according to environmental factors. A. erythraea showed higher density in a semi-closed bay (Gamak, Masan) where the dissolved oxygen was low (<2 mg L^-1). A. sinjiensis showed a high density in a semi-closed bay when the chlorophyll-a concentration was >2 ㎍ L^-1. A. ohtsukai showed a high density at water temperatures >26℃ and low salinity <30. A. hongi and A. hudsonica showed at water temperatures <27℃ and high dissolved oxygen (>5 mg L^-1). These results suggest that environmental factors (temperature, salinity, dissolved oxygen, and chlorophyll-a concentration) may affect the spatial distribution of Acartia species dominant in the southern coasts of Korea in summer.

• Journal of Korean Society of Forest Science
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• v.95 no.3
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• pp.240-249
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• 2006

Recently, dispersion of damaged forest by pine wilt disease has been regarded as a serious social issue. Damages by pine wilt disease have been spreaded by natural area expansion of the vectors in the damaged area, while the national wide damage spread has induced by human-involved carrying infected trees out of damaged area. In this study, damaged trees were detected and located on the digital map by aerial photograph and terrestrial surveys. The spatial distribution pattern of damaged trees, and the relationship of spatial distribution of damaged trees and some geomorphological factors were geostatistically analysed. Finally, we maked natural spread pattern map of pine wilt disease using geostatistical CART(Classification and Regression Trees) model. This study verified that geostatistical analysis and CART model are useful tools for understanding spatial distribution and natural spread pattern of pine wilt diseases.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.169-176
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• 2021

The Global Space-based Inter-Calibration System (GSICS) is an international partnership sponsored by World Meteorological Organization (WMO) to continue and improve climate monitoring and to ensure consistent accuracy between observation data from meteorological satellites operating around the world. The objective for GSICS is to inter-calibration from pairs of satellites observations, which includes direct comparison of collocated Geostationary Earth Orbit (GEO)-Low Earth Orbit (LEO) observations. One of the GSICS inter-calibration methods, the Ray-matching technique, is a surrogate approach that uses matched, co-angled and co-located pixels to transfer the calibration from a well calibrated satellite sensor to another sensor. In Korea, the first GEO satellite, Communication Ocean and Meteorological Satellite (COMS), is used to participate in the GSICS program. The National Meteorological Satellite Center (NMSC), which operated COMS/MI, calculated the Radiative Transfer Model (RTM)-based GSICS coefficient coefficients. The L1P reproduced through GSICS correction coefficient showed lower RMSE and Bias than L1B without GSICS correction coefficient applied. The calculation cycles of the GSICS correction coefficients for COMS/MI visible channel are provided annual and diurnal (2, 5, 10, 14-day), but long-term evaluation according to these cycles was not performed. The purpose of this paper is to perform evaluation depending on the annual/diurnal cycles of COMS/MI GSICS correction coefficients based on the ray-matching technique using Suomi-NPP/Visible Infrared Imaging Radiometer Suite (VIIRS) data as reference data. As a result of evaluation, the diurnal cycle had a higher coincidence rate with the reference data than the annual cycle, and the 14-day diurnal cycle was the most suitable for use as the GSICS correction coefficient.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.5
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• pp.223-232
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• 2021

The spatial variation characteristics of seismic motions at the nuclear power plant's site and structures were analyzed using earthquake records obtained at the Fukushima nuclear power plant during the Great East Japan Earthquake. The ground responses amplified as they approached the soil surface from the lower rock surface, and the amplification occurred intensively at about 50 m near the ground. Due to the soil layer's nonlinear characteristics caused by the strong seismic motion, the ground's natural frequency derived from the response spectrum ratio appeared to be smaller than that calculated from the shear wave velocity profile. The spatial variation of the peak ground acceleration at the ground surface of the power plant site showed a significant difference of about 0.6 g at the maximum. As a result of comparing the response spectrums at the basement of the structure with the design response spectrum, there was a large variability by each power plant unit. The difference was more significant in the Fukushima Daiichi site record, which showed larger peak ground acceleration at the surface. The earthquake motions input to the basement of the structure amplified according to the structure's height. The natural frequency obtained from the recorded results was lower than that indicated in the previous research. Also, the floor response spectrum change according to the location at the same height was investigated. The vertical response on the foundation surface showed a significant difference in spectral acceleration depending on the location. The amplified response in the structure showed a different variability depending on the type of structure and the target frequency.

• Journal of Communications and Networks
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• v.8 no.4
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• pp.401-409
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• 2006

Orthogonal frequency division multiplexing (OFDM) and multiple input multiple output (MIMO) technologies provide additional dimensions of freedom with spectral and spatial resources for radio resource management. Multi-dimensional radio resource management has recently been identified to exploit the full dimensions of freedom for more flexible and efficient utilization of scarce radio spectrum while provide diverse quality of service (QoS) guarantees. In this work, a multi-dimensional radio resource scheduling scheme is proposed to achieve above goals in hybrid orthogonal frequency division multiple access (OFDMA) and space division multiple access (SDMA) systems. Cochannel interference (CCI) introduced by frequency reuse under SDMA is eliminated by frequency division and time division between highly interfered users. This scheme maximizes system throughput subjected to the minimum data rate guarantee. for heterogeneous users and transmit power constraint. By numerical examples, system throughput and fairness superiority of the our scheduling scheme are verified.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1221-1233
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• 2019

Estimating damage in each sector that can be caused by volcanic ash deposition, is very important to prepare the volcanic ash disaster. In this study, we showed predicted-Korean-volcanic-ash damage of each sector by using volcanic ash diffusion simulation and spatial-data-based volcanic ash damage sector in previous study. To this end, volcanic ash related base maps were generated by collecting and processing spatial information data. Finally, we showed Korean-volcanic-ash-deposition damages by sector using the collected Mt. Aso volcanic ash scenarios via overlapping analysis. As a result, volcanic-ash-related damages were expected to occur in the 162 and 134 districts for each Aso volcanic ash scenarios, since those districts exceeds the minimum volcanic ash damage criterion of 0.01 mm. Finally, we compared possible volcanic ash damages by sectors using collected and processed spatial data, after selecting administrative districts(Scenario 190805- Kangwon-do, Kyungsangbuk-do; Scenario 190811-Chuncheon-si, Hongcheon-si) with the largest amount of volcanic ash deposition.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.155-165
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• 2004

Hydrological model which is proper to watershed characteristics and analysis purpose must be used when we analyze water resources. But, although proper model is used, if objectivity and reasonability of data is low it is difficult to get good results from the model. So it is very important to decide the data which is used in selected model and estimate parameters by using the applied data. In this study, temporal and spatial data was constructed as standard data of test site and stored in HyGIS (Hydrological Geographic Information System) DB. A system which extracts temporal and spatial data required to run hydrological model from HyGIS DB by connecting TOPMODEL with HyGIS was developed. In this system, we can extract temporal and spatial data which is needed to run TOPMODEL from HyGIS DB and estimate model parameters by using genetic algorithm. We found that HyGIS and the system connected with TOPMODEL was effective to make temporal and spatial data used in TOPMODEL and estimate model parameters. From this study, we suggested the possibility that HyGIS could be applied properly to another hydrological model, too.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1505-1515
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• 2023

As extreme weather events caused by climate change are occurring around the world, blue carbon has recently been gaining attention as a carbon sink. Blue carbon has been officially recognized by the Intergovernmental Panel on Climate Change (IPCC) as a means of reducing greenhouse gases, and various studies are underway to discover new blue carbon sources both domestically and internationally. Domestic blue carbon research is centered on carbon absorption and storage in tidal flats, which account for most of the coastal wetlands, but there is a lack of research on spatial information. This study utilized the carbon storage of tidal flats from previous studies and converted it into location and spatial information for each basin of the Geumgang and Nakdong rivers. In addition, a proxy value of carbon storage per area by basin was calculated to compare and analyze the total carbon storage of various tidal flats in Korea and abroad. As a result of the analysis, both the Geumgang and Nakdong River basins showed different amounts of carbon storage depending on the tidal flats data, with the highest amount in the Geumgang basin coming from the National Ocean Survey (469,810.1 Mg C) and the highest amount in the Nakdong River basin coming from the Ministry of Environment (217,145.01 Mg C). The results of this study can be used as a basis for future research on the establishment of domestic blue carbon spatial information.