• Particle and aerosol research
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• v.17 no.1
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• pp.9-20
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• 2021

As a large city advanced, the urban environment is becoming an issue. The contribution of vehicle emissions in air pollutants was very high according to the clean air policy support system (CAPSS). In order to improve the air quality in large cities, it is necessary to establish improvement measures by sources, analyzing the air quality of roadside. We divided Bucheon city into 4 regions to investigate the roadside pollutants of each district using the mobile laboratory (ML) and air quality monitoring station (AQMS). ML was used to measure pollutants emitted from vehicles and AQMS data was used as a comparison group of ML data. As a measurement result of pollutants in the roadside, the concentration of air pollutants in industrial & engineering complex area was the highest and concentration of air pollutants in residential & forest complex area was lower. By street, Bucheon-ro, Sinheung-ro, Sosa-ro, and Gyeongin-ro were identified as high concentrations. Therefore, further researches on preparing management measures for roads in the hot-spot area are needed.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.370-377
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• 2000

The red ginseng is very popular as a health food. It has been manufactured with raw ginseng by the conventional method. But, the yield of the heaven grade ginseng (the best quality red ginseng) among the whole products is around 5-7％, Therefore, the yield should be improved in order to increase economic returns. In this study, a new model of drying system was developed to improve the yield of heaven grade ginseng from 7% to 15% or more. For this system, temperature and relative humidity were controlled by the feedback control system, and a solenoid valve for steam supply and other variables were controlled by the PC. The special features of this system developed are an image processing system for monitoring the red ginseng during the drying process in the drying chamber, and a cylindrical porous tray for holding ginseng that is rotating with the speed of 0-10rpm in the drying chamber and makes uniform drying of red ginseng possible.

• Korean Journal of Environment and Ecology
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• v.31 no.6
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• pp.508-519
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• 2017

There have been many studies on monitoring of biodiversity changes and preservation of Gwangneung Forest Biosphere Reserve (GFBR) in South Korea in recognition of the rare ecosystem that has been preserved for a long period. However, there are few studies on diversity and community characteristics of benthic macroinvertebrates as an indicator of stream health of GFBR. The purpose of this study was to assess the water quality of Bongseonsa Stream that penetrated through Gwangneung Forest and the nearby torrents by analyzing the benthic macroinvertebrates community during April to September 2016. The investigation collected a total of 114 species of benthic macroinvertebrates belonging to 56 families, 17 orders, 8 classes, and 5 phyla from the Bongseonsa Stream and Kwangneung Stream. Ephemeroptera and Trichoptera were the largest groups in species diversity with 30 species (32.3%) and 16 species (17.2%), respectively, and Tubificidae sp., Baetis fuscatus, Antocha KUa, and Cheumatopsyche brevilineata, which usually habit in contaminated streams, appeared frequently. Among the feeding function groups, the gatherers and hunters appeared relatively frequently, and the shredders and scrapers appeared frequently in the torrents. Among the habitat oriented groups, the clingers and burrower appeared more frequently and represented the microhabitats in the shallow areas. The result of the analysis of benthic macroinvertebrates community showed that the dominant index was $0.48{\pm}0.10$ in average while it was lowest with 0.33 in GS 8 of the Gwangneung Forest torrent and highest in BS 1 of Bongseonsa Stream. The diversity and richness indices were inversely proportional to the dominant index and were 2.53 and 4.22, respectively, in GS 8 where the dominant index was low. The result of the analysis of community stability showed that area I, which had high resistance and restoration, was high in Bongseonsa Stream while the area III, which had low resistance and restoration, was high in Gwangneung Forest, indicating that the water system in Gwangneung Forest had a wider distribution of specifies sensitive to agitation. The biological water quality assessment showed ESB of $50.88{\pm}17.69$, KSI of $1.11{\pm}0.57$, and BMI of $78.55{\pm}11.05$. GS 8 of Gwangneung Forest torrent was judged to be the highest priority protective water area with the best water environment and I class water quality with ESB of 63, KSI of 0.55, and BMI of 89.9. On the contrary, BS 1 of Bongseonsa Stream was judged to be the high priority improvement area that had the lowest water quality rating of III with ESB of 25, KSI of 2.13, and BMI of 62.7. Although the diversity of water beetle was higher in the water system of nearby Bongseonsa Stream than the water system inside the Gwangneung Forest, the annual community structure appeared to have distinct differences.

• Korean Journal of Ecology and Environment
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• v.45 no.4
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• pp.392-402
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• 2012

In this study, to analyze the stream health using fish assemblage and make effective management, we conducted fish monitoring in the Hoeya River basin and neighboring streams. A total of 33 species classified into 12 families were collected from 29 sites in 2007. Dominant species was Zacco platypus (Relative abundance, RA: 24.8%), and subdominant species was Rhynchocypris oxycephalus (RA: 16.2%). Eight Korean endemic species and 4 exotic species were identified. Moreover, two species (Opsariichthys uncirostris amurensis and Hemiculter eigenmanni) were translocated from other basin. To evaluate stream health of the study sites, Index of Biological Integrity (IBI) was applied, based on fish assemblages. Overall, IBI values were "C (Fair)" or "D (Poor)" condition, according to the grade except two sites which recorded "B (Good)". The correlation between land use pattern of surrounding watershed and IBI was analyzed to verify impact of development on stream health using fish assemblage. As a result, when percentage of the developmental groups increased, IBI values were decreased (Pearson correlation, r=-0.425, p=0.022). In contrast, increment of percent forest and grass land was positively correlated with IBI (r=0.556, p=0.002). The agricultural group and IBI did not significantly correlate with each other (r=-0.231, p=0.333). In this study, we identified a relationship between land use of surrounding watershed and stream health using fish data (i.e. IBI). These results could be provided useful fundamental information to establish management and restoration plan in the Hoeya River basin and other rivers distributed in Korea.

• Journal of IKEEE
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• v.23 no.4
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• pp.1273-1279
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• 2019

Though sleep polysomnography (PSG) is considered as a golden rule for medical diagnosis of sleep disorder, it is essential to find alternative diagnosis methods due to its cost and time constraints. Recently, as the popularity of wearable health devices, there are many research trials to replace conventional actigraphy to consumer grade devices. However, these devices are very limited in their use due to the accessibility of the data and algorithms. In this paper, we showed the predictive model for sleep stages classified by American Academy of Sleep Medicine (AASM) standard and we proposed the estimation of sleep cycle by comparing sensor data and power spectrums of δ wave and θ wave. The sleep stage prediction for 31 subjects showed an accuracy of 85.26%. Also, we showed the possibility that proposed algorithm can find the sleep cycle of REM sleep and NREM sleep.

• Korean Journal of Agricultural Science
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• v.47 no.1
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• pp.59-66
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• 2020

Particulate matter (PM) is regarded as a major threat to public health and safety in urban areas. Despite a variety of efforts to systemically monitor the distribution of PM, the limited amount of sampling sites may not provide sufficient coverage over the areas where the monitoring stations are not located in close proximity. This study examined the capacity of using remotely sensed data to estimate the PM10 and PM2.5 concentrations in Seoul, South Korea. Multiple linear regression models were developed using the multispectral band data from the Moderate-resolution imaging spectro-radiometer equipped on Terra (MODIS) and Operational Land Imager equipped on Landsat 8 (Landsat 8) and meteorological parameters. Compared to MODIS-derived models (r² = 0.25 for PM10, r² = 0.30 for PM2.5), the Landsat 8-derived models showed improved model reliabilities (r² = 0.17 to 0.57 for PM10, r² = 0.47 to 0.71 for PM2.5). Landsat 8 model-derived PM concentration and ground-truth PM measurements were cross-validated to each other to examine the capability of the models for estimating the PM concentration. The modeled PM concentrations showed a stronger correlation to PM10 (r = 0.41 to 0.75) than to PM2.5 (r = 0.14 to 0.82). Overall, the results indicate that Landsat 8-derived models were more suitable in estimating the PM concentrations. Despite the day-to-day fluctuation in the model reliability, several models showed strong correspondences of the modeled PM concentrations to the PM measurements.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.751-761
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• 2019

Mt. Baekdu, Mt. Aso, Mt. Sakurajima, Mt. Kikai and etc are distributed around the Korean Peninsula. Recently signs of eruption of Mt. Baekdu are increasing, raising concerns over possible damage to volcanic ash from seasonal winds during the winter eruption. Therefore, detailed procedures for investigation and countermeasures for volcanic ash spread and damage are required. But the standards for the warning and alarm signal of volcanic ash presented by Korea Ministry of Government Legislation are vague, with "when damage is expected" and "when serious damage is expected". In this study, to analyze the damage threshold and to apply the cases of overseas damage to the country, a survey was conducted on the establishment of domestic spatial information by public institutions with public confidence. As a result of the investigation of damage from volcanic ash overseas, the details of the damage cases were different depending on the type of life or income sources of each country. Therefore, instead of applying the volcanic ash damage cases abroad in Korea, spatial information analysis was performed to reflect domestic social and natural characteristics. In addition, we selected the areas to be considered in the event of volcanic ash damage in Korea. Finally, domestic volcanic ash damages should be classified as health, residential, road, railroad, aviation, power, water, agriculture, livestock, forest, and soil. When establishing the volcanic ash alarm optimized for Korea in the future, overseas volcanic ash damage cases and domestic spatial information construction in this study will be helpful in policy establishment.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.319-341
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• 2024

The utilization of multispectral imaging systems (MIS) in remote sensing has become crucial for large-scale agricultural operations, particularly for diagnosing plant health, monitoring crop growth, and estimating plant phenotypic traits through vegetation indices (VIs). However, environmental factors can significantly affect the accuracy of multispectral reflectance data, leading to potential errors in VIs and crop status assessments. This paper reviewed the complex interactions between environmental conditions and multispectral sensors emphasizing the importance of accounting for these factors to enhance the reliability of reflectance data in agricultural applications.An overview of the fundamentals of multispectral sensors and the operational principles behind vegetation index (VI) computation was reviewed. The review highlights the impact of environmental conditions, particularly solar zenith angle (SZA), on reflectance data quality. Higher SZA values increase cloud optical thickness and droplet concentration by 40-70%, affecting reflectance in the red (-0.01 to 0.02) and near-infrared (NIR) bands (-0.03 to 0.06), crucial for VI accuracy. An SZA of 45° is optimal for data collection, while atmospheric conditions, such as water vapor and aerosols, greatly influence reflectance data, affecting forest biomass estimates and agricultural assessments. During the COVID-19 lockdown,reduced atmospheric interference improved the accuracy of satellite image reflectance consistency. The NIR/Red edge ratio and water index emerged as the most stable indices, providing consistent measurements across different lighting conditions. Additionally, a simulated environment demonstrated that MIS surface reflectance can vary 10-20% with changes in aerosol optical thickness, 15-30% with water vapor levels, and up to 25% in NIR reflectance due to high wind speeds. Seasonal factors like temperature and humidity can cause up to a 15% change, highlighting the complexity of environmental impacts on remote sensing data. This review indicated the importance of precisely managing environmental factors to maintain the integrity of VIs calculations. Explaining the relationship between environmental variables and multispectral sensors offers valuable insights for optimizing the accuracy and reliability of remote sensing data in various agricultural applications.