• KOREAN JOURNAL OF CROP SCIENCE
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• v.58 no.2
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• pp.142-148
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• 2013

Bacterial diseases in soybean are bacterial pustule by Xanthomonas axonopodis pv. glycines, wildfire by Pseudomonas syringae pv. tabaci, bacterial blight by Pseudomonas savastanoi pv. glycines and bacterial brown spot by Pseudomonas syringae pv. syringae in Korea. It is difficult to identify each disease by early symptoms in fields, because the initial symptoms of these diseases are very similar to each other. In this study, we developed multiplex PCR detection method for rapid and accurate diagnosis of bacterial diseases. The glycinecin A of X. axonopodis pv. glycines, the tabtoxin of P. syringae pv. tabaci, the coronatine of P. savastanoi pv. glycines and the syringopeptin of P. syringae pv. syringae have been reported previously. These bacteriocin or phytotoxin producing genes were targeted to design the specific diagnostic primers. The primer pairs for diagnosis of each bacterial diseases were selected without nonspecific reactions. The studies on simultaneous diagnosis method were also conducted with primarily selected 21 primers. As a result, we selected PCR primer sets for multiplex PCR. Sizes of the amplified PCR products using the multiplex PCR primer set consist of 280, 355, 563 and 815 bp, respectively. This multiplex PCR method provides a efficient, sensitive and rapid tool for the diagnosis of the bacterial diseases in soybean.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.105-113
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• 2016

Fire radiative power(FRP), which means the power radiated from wildfire, is used to estimate fire emissions. Currently, the geostationary satellites of East Asia do not provide official FRP products yet, whereas the American and European geostationary satellites are providing near-real-time FRP products for Europe, Africa and America. This paper describes the first retrieval of Himawari-8 FRP using the mid-infrared radiance method and shows the comparisons with MODIS FRP for Sumatra, Indonesia. Land surface emissivity, an essential parameter for mid-infrared radiance method, was calculated using NDVI(normalized difference vegetation index) and FVC(fraction of vegetation coverage) according to land cover types. Also, the sensor coefficient for Himawari-8(a = 3.11) was derived through optimization experiments. The mean absolute percentage difference was about 20%, which can be interpreted as a favourable performance similar to the validation statistics of the American and European satellites. The retrieval accuracies of Himawari FRP were rarely influenced by land cover types or solar zenith angle, but parts of the pixels showed somewhat low accuracies according to the fire size and viewing zenith angle. This study will contribute to estimation of wildfire emissions and can be a reference for the FRP retrieval of current and forthcoming geostationary satellites in East Asia.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.1029-1040
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• 2017

Wildfires release a large amount of greenhouse gases (GHGs) into the atmosphere. Fire radiative power (FRP) data obtained from geostationary satellites can play an important role for tracing the GHGs. This paper describes an estimation of the Himawari-8 FRP and fire emissions for Samcheock and Gangnueng wildfire in 6 May 2017. The FRP estimated using Himawari-8 well represented the temporal variability of the fire intensity, which cannot be captured by MODIS (Moderate Resolution Imaging Spectroradiometer) because of its limited temporal resolution. Fire emissions calculated from the Himwari-8 FRP showed a very similar time-series pattern compared with the AirKorea observations, but 1 to 3 hour's time-lag existed because of the distance between the station and the wildfire location. The estimated emissions were also compared with those of a previous study which analyzed fire damages using high-resolution images. They almost coincided with 12% difference for Samcheock and 2% difference for Gangneung, demonstrating a reliability of the estimation of fire emissions using our Himawari-8 FRP without high-resolution images. This study can be a reference for estimating fire emissions using the current and forthcoming geostationary satellites in East Asia and can contribute to improving accuracy of meteorological products such as AOD (aerosol optical depth).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.327-343
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• 2020

This study proposes a method to improve the geometric quality of KOMPSAT (Korea Multi-Purpose Satellite)-3/3A Level 1R imagery, particularly for efficient disaster damage analysis. The proposed method applies a novel grid-based SIFT (Scale Invariant Feature Transform) method to the Planetscope ortho-imagery, which solves the inherent limitations in acquiring appropriate optical satellite imagery over disaster areas, and the KOMPSAT-3/3A imagery to extract GCPs (Ground Control Points) required for the RPC (Rational Polynomial Coefficient) bias compensation. In order to validate its effectiveness, the proposed method was applied to the KOMPSAT-3 multispectral image of Gangnueng which includes the April 2019 wildfire, and the KOMPSAT-3A image of Daejeon, which was additionally selected in consideration of the diverse land cover types. The proposed method improved the geometric quality of KOMPSAT-3/3A images by reducing the positioning errors(RMSE: Root Mean Square Error) of the two images from 6.62 pixels to 1.25 pixels for KOMPSAT-3, and from 7.03 pixels to 1.66 pixels for KOMPSAT-3A. Through a visual comparison of the post-disaster KOMPSAT-3 ortho-image of Gangneung and the pre-disaster Planetscope ortho-image, the result showed appropriate geometric quality for wildfire damage analysis. This paper demonstrated the possibility of using Planetscope ortho-images as an alternative to obtain the GCPs for geometric calibration. Furthermore, the proposed method can be applied to various KOMPSAT-3/3A research studies where Planetscope ortho-images can be provided.

• Journal of Life Science
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• v.25 no.2
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• pp.136-150
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• 2015

Pseudomonas syringae pathovar tabaci is a plant pathogenic bacterium that causes wildfire disease in tobacco plants. In P. syringae pv. tabaci, PsyI, a LuxI-type protein, acts as an AHL synthase, while primary and secondary sequence analysis of PsyR has revealed that it is a homolog of the LuxR-type transcriptional regulator that responds to AHL molecules. In this study, using phenotypic and genetic analyses in P. syringae pv. tabaci, we show the effect of PsyR protein as a quorum-sensing (QS) transcriptional regulator. Regulatory effects of PsyR on swarming motility and production of siderophores, tabtoxin, and N-acyl homoserine lactones were examined via phenotypic assays, and confirmed by quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR). Further qRT-PCR showed that PsyR regulates expression of these virulence genes in response to environmental signals. However, an upstream region of the gene was not bound with purified MBP-PsyR protein; rather, PsyR was only able to shift the upstream region of psyI. These results suggested that PsyR may be indirectly controlled via intermediate-regulatory systems and that auto-regulation by PsyR does not occur.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1754-1759
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• 2008

To produce plastic parts that have fine pattern through conventional injection molding, a lot of difficulties follow. Therefore, rapid heating and cooling methods are good candidates for manufacturing injection-molded parts with micro/nano patterns. In this study, we adopted the E-Mold patent technology. The mold for E-Mold technology has a separate heated core with micro heaters. It is very important to optimize the lay-out of the heaters in heated core because it influences both control and distribution of mold temperature. We developed a optimization method of heating line lay-out by using commercial softwares and compared the output with the experimental results. We used Pro-Engineer Wildfire 2.0 for the mold design, ICEMCFD for mesh generation, and FLUENT for heat transfer simulation. The simulation results showed the temperature profile from $60^{\circ}C$ to $120^{\circ}C$ or $180^{\circ}C$ during heating and cooling process which were compared with the injection molding experiments. We concluded that the simulation could well explain the experimental results. It was shown that the E-Mold optimization design for heater lay-out could be available through the simulation.

• Korean Journal of Plant Resources
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• v.35 no.2
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• pp.169-182
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• 2022

This study was conducted to predict the distribution of rare·endemic plants (Sophora koreensis Nakai) in the border forests where wildfire damage occurred and to quantify the damage. For this purpose, we tried to derive more accurate results through forest area damage (NBR) according to the Burn severity of wildfires, damage by tree species type (Vegetation map), and MaxEnt model. For Burn severity analysis, satellite imagery (Landsat-8) was used to analyze Burn severity (ΔNBR2016-2015) and to derive the extent of damage. To prepare the Vegetation map, the land cover map prepared by the Ministry of Environment, the Vegetation map prepared by the Korea Forest Service, and the vegetation survey conducted by itself were conducted to prepare the clinical map before and after the forest fire. Lastly, for MaxEnt model analysis, the AUC value was derived by using the habitat coordinates of Sophora koreensis Nakai based on the related literature and self-report data. As a result of combining the Maxent model analysis data with the Burn severity data, it was confirmed that 45.9% of the 44,760 m² of habitat (predicted) area of Sophora koreensis Nakai in the wildfire damaged area or 20,552 m², was damaged.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1805-1815
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• 2022

In 2022, wildfires broke out in Uljin-gun and Samcheok-si, which set the record for the longest forest fire in Korea, but there were no casualties. To protect local residents from wildfires, they must evacuate. Predicting the demand for evacuation in the event of wildfires is essential for the efficiency of disaster management. The purpose of this study is to analyze the human mobility patterns according to the occurrence of Uljin-gun and Samcheok-si wildfires. SKT floating population data was used in this study to analyze the human mobility patterns in Uljin-gun and Samcheok-si. The main findings are as follows. First, while the movement of the resident and visiting population decreased, the movement of the worker population was found to be similar to normal. Second, the resident population of Buk-myeon, Uljin-gun moved to the surrounding area to avoid the wildfires. Third, the region is an area judged to be safe from wildfires, and this mobility patterns are related to emergency disaster text messages. This study confirmed human mobility patterns of the population in the area where the wildfires through the floating population data, which is quantitative data. This suggests that it is important to guide residents to shelters through emergency text messages to minimize damage in the event of wildfires.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.785-798
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• 2023

Recently, forest fires have become frequent due to climate change, and the size of forest fires is also increasing. Forest fires in Korea continue to cause more than 100 ha of forest fire damage every year. It was found that 90% of the large-scale wildfires that occurred in Gangwon-do over the past five years were concentrated in the east coast area. The east coast area has a climate vulnerable to forest fires such as dry air and intermediate wind, and forest conditions of coniferous forests. In this regard, studies related to various forest fire analysis, such as predicting the risk of forest fires and calculating the risk of forest fires, are being promoted. There are many studies related to risk analysis for forest areas in consideration of weather and forest-related factors, but studies that have conducted risk analysis for forest-friendly areas are still insufficient. Management of forest adjacent areas is important for the protection of human life and property. Forest-adjacent houses and facilities are greatly threatened by forest fires. Therefore, in this study, a grid-based forest fire-related disaster risk map was created using factors affected by forest-neighboring areas using national branch numbers, and differences in risk ratings were compared for forest areas and areas adjacent to forests based on Gangneung forest fire cases.