• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1643-1652
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• 2020

To investigate the characteristics of detailed flows in a building-congested district, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. For realistic numerical simulations, we used the meteorological variables such as wind speeds and directions and potential temperatures predicted by LDAPS as the initial and boundary conditions of the CFD model. We trilinearly interpolated the horizontal wind components of LDAPS to provide the initial and boudnary wind velocities to the CFD model. The trilinearly interpolated potential temperatures of LDAPS is converted to temperatures at each grid point of the CFD model. We linearly interpolated the horizontal wind components of LDAPS to provide the initial and boundary wind velocities to the CFD model. The linearly interpolated potential temperatures of LDAPS are converted to temperatures at each grid point of the CFD model. We validated the simulated wind speeds and directions against those measured at the PKNU-SONIC station. The LDAPS-CFD model reproduced similar wind directions and wind speeds measured at the PKNU-SONIC station. At 07 LST on 22 June 2020, the inflow was east-north-easterly. Flow distortion by buildings resulted in the east-south-easterly at the PKNU-SONIC station, which was the similar wind direction to the measured one. At 19 LST when the inflow was southeasterly, the LDAPS-CFD model simulated southeasterly (similar to the measured wind direction) at the PKNU-SONIC station.

• Geophysics and Geophysical Exploration
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• v.24 no.3
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• pp.78-88
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• 2021

Owing to the abnormal weather conditions due to global warming, carbon capture and storage (CCS) technology has attracted global attention as a countermeasure to reduce CO₂ emissions. In the Pohang CCS demonstration project in South Korea, 100 tons of CO₂ were successfully injected into the subsurface CO₂ storage in early 2017. However, after the 2017 Pohang earthquake, the Pohang CCS demonstration project was suspended due to an increase in social concerns about the safety of the CCS project. In this study, to reconfirm the structural suitability of the CO₂ storage site in the Pohang Basin, we employed seismic imaging based on reverse-time migration (RTM) to analyze small-scale ocean-bottom seismic data, which have not been utilized in previous studies. Compared with seismic images using marine streamer data, the continuity of subsurface layers in the RTM image using the ocean-bottom seismic data is improved. Based on the obtained subsurface image, we discuss the structural suitability of the Pohang CO₂ storage site.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.283-298
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• 2022

As Synthetic Aperture Radar (SAR) image can be acquired regardless of the weather and day or night, it is highly recommended to be used for Automatic Target Recognition (ATR) in the fields of surveillance, reconnaissance, and national security. However, there are some limitations in terms of cost and operation to build various and vast amounts of target images for the SAR-ATR system. Recently, interest in the development of an ATR system based on simulated SAR images using a target model is increasing. Attributed Scattering Center (ASC) matching and template matching mainly used in SAR-ATR are applied to target classification. The method based on ASC matching was developed by World View Vector (WVV) feature reconstruction and Weighted Bipartite Graph Matching (WBGM). The template matching was carried out by calculating the correlation coefficient between two simulated images reconstructed with adjacent points to each other. For the performance analysis of the two proposed methods, the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset was used, which has been recently published by the U.S. Defense Advanced Research Projects Agency (DARPA). We conducted experiments under standard operating conditions, partial target occlusion, and random occlusion. The performance of the ASC matching is generally superior to that of the template matching. Under the standard operating condition, the average recognition rate of the ASC matching is 85.1%, and the rate of the template matching is 74.4%. Also, the ASC matching has less performance variation across 10 targets. The ASC matching performed about 10% higher than the template matching according to the amount of target partial occlusion, and even with 60% random occlusion, the recognition rate was 73.4%.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.999-1009
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• 2021

As the frequency and intensity of extreme weather events due to climate change are increasing in recent years, it is very important to evaluate and analyze climate conditions to manage and respond to the negative effects of climate change in advance. In this study, the trends and characteristics of regional climate change were analyzed by calculating the climate indices for the Chungcheong Province. Annual and monthly UNEP-MP, UNEP-PM and MDM indices were calculated using daily data from 1973-2020 collected from 10 synoptic meteorological stations operated by the Korea Meteorological Administration. The normality of climate data was analyzed through the KS test, and the climate change trend was analyzed by applying the Spearman and Pearson methods. The Chungcheongnam-do region had a relatively humid climate than the Chungcheongbuk-do region, and the annual climate indices showed a dry climate trend in Cheongju and Chungju, while the climate of Seosan and Buyeo was becoming humid. Based on the monthly trend change analysis, a humid climate trend was observed in summer and autumn, while a dry climate trend was observed in spring and winter. Comparison of climate indices during the past (2001-2010) and the recent (2011-2020) years showed a higher decrease in the average climate indices during the last 10 years and a gradually drying climate change trend was recorded.

• Atmosphere
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• v.31 no.5
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• pp.577-592
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• 2021

This study evaluates the predictability of the number of days of heat and cold damages by growth stages of rice in South Korea using the hindcast data (1986~2020) produced by Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF) model chain. The predictability is accessed in terms of Root Mean Square Error (RMSE), Normalized Standardized Deviations (NSD), Hit Rate (HR) and Heidke Skill Score (HSS). For the purpose, the model predictability to produce the daily maximum and minimum temperatures, which are the variables used to define heat and cold damages for rice, are evaluated first. The result shows that most of the predictions starting the initial conditions from January to May (01RUN to 05RUN) have reasonable predictability, although it varies to some extent depending on the month at which integration starts. In particular, the ensemble average of 01RUN to 05RUN with equal weighting (ENS) has more reasonable predictability (RMSE is in the range of 1.2~2.6℃ and NSD is about 1.0) than individual RUNs. Accordingly, the regional patterns and characteristics of the predicted damages for rice due to excessive high- and low-temperatures are well captured by the model chain when compared with observation, particularly in regions where the damages occur frequently, in spite that hindcasted data somewhat overestimate the damages in terms of number of occurrence days. In ENS, the HR and HSS for heat (cold) damages in rice is in the ranges of 0.44~0.84 and 0.05~0.13 (0.58~0.81 and -0.01~0.10) by growth stage. Overall, it is concluded that the PNU CGCM-WRF chain of 01RUN~05RUN and ENS has reasonable capability to predict the heat and cold damages for rice in South Korea.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.505-513
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• 2022

Recently, uncertainty in predicting available water resources is gradually increasing due to climate change and extreme weather conditions. Social interest in water management such as flood and drought prevention is also increasing, and after the unification of water management implemented in 2018, domestic water management is facing a major turning point. As part of such strengthening of water management capabilities, various studies are being conducted to utilize a hydropower dam for flood control and water supply purposes, which was mainly operated for hydroelectric power generation. However, since the dam evaluation methods developed based on a multi-purpose dam are being applied to hydropower dams, an additional evaluation approach that can consider the characteristics of hydropower dams is required. In this study, a new water supply capacity evaluation method is presented in consideration of the operational characteristics of hydropower dams in terms of water supply, and a connected reservoir simulation method is proposed to evaluate the comprehensive water supply capacity of a dam group operating in a river basin. The presented method was applied to the hydropower dams located in the Bukhan River basin, and the results of the water supply yield of individual dams and multi-reservoir systems were compared and analyzed. In the future, the role of hydropower dams for water supply during drought is expected to become more important, and this study can be used for sustainable domestic water management research using hydropower dams.

• Microbiology and Biotechnology Letters
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• v.50 no.2
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• pp.165-192
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• 2022

The microbial metagenome characteristics of bioaerosols and particulate matter (PM) in the outdoor atmospheric environment and the effects of climate and environmental factors on the metagenome were analyzed. The concentrations of bacteria and fungi in bioaerosols and PM were determined by sampling different regions with different environmental properties. A variety of culture-independent methods were used to analyze the microbial metagenome in aerosols and PM samples. In addition, the effects of meteorological and environmental factors on the diversity and metagenomes of bacteria and fungi were investigated. The survival, growth, and dispersal of the microorganisms in the atmosphere were markedly affected by local weather conditions and the air pollutant concentration. The concentration of airborne microorganisms increased as the temperature increased, but their concentration decreased in summer, due to the effects of high temperatures and strong ultraviolet rays. Humidity and microbial concentration were positively correlated, but when the humidity was too high, the dispersion of airborne microorganisms was inhibited. These comprehensive data on the microbial metagenome in bioaerosols and PM may be used to understand the roles and functions of microorganisms in the atmosphere, and to develop strategies and abatement techniques to address the environmental and public health problems caused by these microorganisms.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.533-541
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• 2022

An analysis of marine accidents that occurred in the last five years, revealed that 77.0 % of all grounding accidents and 66.1% of all marine casualties involved small vessels, which was a very high level relatively. The Mokpo Regional Maritime Safety Tribunal (Mokpo-KMST) inquired on 72 cases of marine accidents in 2021, of which 10 cases were grounding accidents. Furthermore, eight cases of grounding accidents occurred in small fishing vessels. This study analyzed eight cases of grounding accidents on small fishing vessels that inquired in the jurisdictional area of Mokpo-KMST in 2021. I found out that this grounding occurred in clear weather with good visibility (2-4 miles) and good sea conditions with a wave height of less than 1 meter. Furthermore, I found that the main causes of grounding were drowsy navigation due to fatigue, neglect of vigilance, neglect of checking ship's position, overconfidence in GPS plotter, and lack of understanding of chart symbols and tidal differences. To reduce grounding accidents of small fishing vessels, I suggested the following measures. First, crew members who have completed the able seafarer training course on bridge watchkeeping should assist to the master. Second, alarm systems to prevent drowsiness should be installed in the bridge. Third, the regulation should be prepared for the performance standards and updating GPS plotter. Finally, the skipper of small vessels should be trained periodically to be familiar with chart symbols and basic terrestrial navigation.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1101-1107
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• 2022

The leaf temperature is principally regulated by the opening and closing of stomata that is sensitive to various kinds of plant physiological stress. Thus, the analysis of thermal imagery, one of remote sensing technique, will be useful to detect crop physiological condition on smart farm system and phenomics platform. However, there are few case studies using a thermal imaging camera on the agricultural application. In this study, three cases are presented: the effect of lime fertilizer on the rice, the different physiological properties of soybean under shading condition, and the screening of soybean breeds for salinity tolerance characteristic. The leaf temperature measured by thermal imaging camera on the three cases was used effectively to the physiological change and characteristics. However, the thermal imagery analysis requires considering the accuracy of measured temperature and the weather conditions that affects to the leaf temperature.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1231-1244
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• 2022

The frequency of exposure of field crops to stress situations is increasing due to abnormal weather conditions. In South Korea, large-scale diseases in representative paddy rice cultivation area were happened. There are limits to field investigation on the crop damage due to large-scale. Satellite-based remote sensing techniques are useful for monitoring crops in cities and counties, but the sensitivity of vegetation index measured from satellite under abnormal growth of crop should be evaluated. The goal is to evaluate satellite-based normalized difference vegetation index (NDVI) retrieved from different spatial scales using drone imagery. In this study, Sentinel-2 and Landsat-8 satellites were used and they have spatial resolution of 10 and 30 m. Drone-based NDVI, which was resampled to the scale of satellite data, had correlation of 0.867-0.940 with Sentinel-2 NDVI and of 0.813-0.934 with Landsat-8 NDVI. When the effects of bias were minimized, Sentinel-2 NDVI had a normalized root mean square error of 0.2 to 2.8% less than that of the drone NDVI compared to Landsat-8 NDVI. In addition, Sentinel-2 NDVI had the constant error values regardless of diseases damage. On the other hand, Landsat-8 NDVI had different error values depending on degree of diseases. Considering the large error at the boundary of agricultural field, high spatial resolution data is more effective in monitoring crops.