• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.497-508
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• 2023

Agricultural reservoirs are crucial structures for water resources monitoring especially in Korea where the resources are seasonally unevenly distributed. Optical and Synthetic Aperture Radar (SAR) satellites, being utilized as tools for monitoring the reservoirs, have unique limitations in that optical sensors are sensitive to weather conditions and SAR sensors are sensitive to noises and multiple scattering over dense vegetations. In this study, we tried to improve water body detection accuracy through optical-SAR data fusion, and quantitatively analyze the complementary effects. We first detected water bodies at Edong, Cheontae reservoir using the Compact Advanced Satellite 500(CAS500), Kompsat-3/3A, and Sentinel-2 derived Normalized Difference Water Index (NDWI), and SAR backscattering coefficient from Sentinel-1 by K-means clustering technique. After that, the improvements in accuracies were analyzed by applying K-means clustering to the 2-D grid space consists of NDWI and SAR. Kompsat-3/3A was found to have the best accuracy (0.98 at both reservoirs), followed by Sentinel-2(0.83 at Edong, 0.97 at Cheontae), Sentinel-1(both 0.93), and CAS500(0.69, 0.78). By applying K-means clustering to the 2-D space at Cheontae reservoir, accuracy of CAS500 was improved around 22%(resulting accuracy: 0.95) with improve in precision (85%) and degradation in recall (14%). Precision of Kompsat-3A (Sentinel-2) was improved 3%(5%), and recall was degraded 4%(7%). More precise water resources monitoring is expected to be possible with developments of high-resolution SAR satellites including CAS500-5, developments of image fusion and water body detection techniques.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.267-275
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• 2023

This study predicted rice harvest date in South Korea using 11-year (2012-2022) hindcasts based on dynamically downscaled 2m air temperature at subseasonal (1-month lead) timescale. To obtain high (5 km) resolution meteorological information over South Korea, global prediction obtained from the NOAA Climate Forecast System (CFSv2) is dynamically downscaled using the Weather Research and Forecasting (WRF) double-nested modeling system. To estimate rice harvest date, the growing degree days (GDD) is used, which accumulated the daily temperature from the seeding date (1 Jan.) to the reference temperature (1400℃ + 55 days) for harvest. In terms of the maximum (minimum) temperatures, the hindcasts tends to have a cold bias of about 1. 2℃ (0. 1℃) for the rice growth period (May to October) compared to the observation. The harvest date derived from hindcasts (DOY 289) well simulates one from observation (DOY 280), despite a margin of 9 days. The study shows the possibility of obtaining the detailed predictive information for rice harvest date over South Korea based on the dynamical downscaling method.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.661-674
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• 2023

From the seafloor of Taean, Chungcheongnamdo Province, a ship of the Joseon Dynasty was discovered for the first time in the history of underwater excavations in Korea in 2014 and was named Mado Shipwreck No. 4. A total of 27 unused whetstones loaded as tribute were discovered on the hull of Mado No. 4, which revealed that Mado Shipwreck No. 4 was a Grain transport ship that sank while carrying tribute from Naju to Hanyang between 1417 and 1425 (King Taejong to King Sejong). All of the 27 whetstones are in the shape of narrow and long sticks. The average values of length, width, thickness, and weight are 161.5 mm, 36.1 mm, 22.7 mm, and 253.2 g, respectively. The result of X-ray diffraction analysis shows that the constituent minerals are quartz, alkali feldspar, and plagioclase, which is similar to that of the high-resolution digital stereomicroscope analysis. The average porosity of Mado-2672 and 2673 is 2.69% and 1.78%, respectively, and the average surface hardness is 807.2HLD and 834.5HLD, respectively. It is interpreted that if the porosity increases beyond a certain level, it affects the decrease in surface hardness. All of these are made of feldspathic sandstones with an average SiO₂ content of 74.51% and were confirmed to be suitable as grindstones. They are all medium whetstones when classified based on the SiO₂ content. These whetstones are small in size and weight and are convenient to carry, so they are presumed to be a type of non-stationary whetstone, and are estimated to have been mainly used in the fields such as weapon polishing and craft production during the Joseon Dynasty.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.715-727
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• 2023

To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.426-441
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• 2023

This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1299-1308
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• 2023

Forest fires are becoming more frequent and larger around the world due to climate change. Remote sensing such as satellite images can be used as an alternative or assistance data because it reduces various difficulties of field survey. Forest burn severity (differenced normalized burn ratio, dNBR) is calculated through the difference in normalized burn ratio (NBR) before and after a forest fire. The images used in the NBR formula are based on Landsat's near-infrared (NIR) and short-wavelength infrared (SWIR) bands. South Korea's satellite images don't have a SWIR band. So domestic studies related to forest burn severity calculated dNBR using overseas images or indirectly using the normalized difference vegetation index (NDVI) using South Korea's satellite images. Therefore, in this study, dNBR was calculated by substituting the mid-wavelength infrared (MWIR) band of Kompsat-3A (K3A) instead of the SWIR band in the NBR formula. The results were compared with the dNBR results obtained through Landsat which is the standard for dNBR formula. As a result, it was shown that dNBR using K3A's MWIR band has a wider range of values and can be expressed in more detail than dNBR using Landsat's SWIR band. Therefore, it is considered that K3A images will be highly useful in surveying burn areas and severity affected by forest fires. In addition, this study used the K3A's MWIR band images degraded to 30 m. It is considered that much better results will be obtained if a higher-resolution MWIR band is used.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Journal of Public Diplomacy
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• v.2 no.2
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• pp.27-52
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• 2022

Objectives: The neighboring countries of South Korea and Japan in Northeast Asia have interacted in both positive and negative ways, at times as close partners and other times adversaries, throughout their long and thorny history of extensive dynamics. The controversial dispute over Dokdo is one of the most critical issues evoking harsh tensions and arguments asserting wholly opposite claims. Dokdo is a small island between two coastal states, but significant in terms of territorial, botanical, and marine resources, and thus ownership of the island has become a point of conflict accompanied by a troubled history. But why has Dokdo been a source of conflicts and how should the controversial Dokdo issue be addressed in a way that fosters positive influence and co-prosperity? Methods: This study provides comprehensive and critical insights from a wealth of previous research and strategic suggestions for the Korean government. It utilizes the three perspectives of historical documents and political context, international regulations and legal frames, and public diplomacy. Furthermore, it applies these resources to negotiation theories and strategies to propose reasonable solutions. Results: This study suggests that it is important for Korea and Japan to try to build mutual trust through more active communication and interaction in order to understand each other before attempting to create a formal resolution via negotiation. In addition to these efforts, Korea needs to be ready for the inevitable need to take decisive action in terms of negotiation, using analytic and efficient strategies. The study proposes three solutions: 1) Strong Action Strategy, 2) International Legal Strategy, and 3) Public Diplomacy Strategy. Conclusions: From the perspective of public diplomacy, the Dokdo issue needs to be converted from a symbol of conflicts between Korea and Japan into a symbol of peace and co-prosperity. In addition to promoting a positive relationship between the two states, it can also contribute to the security environment of the Northeast Asian region and global peace.

• Journal of Food Hygiene and Safety
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• v.38 no.5
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• pp.390-401
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• 2023

Major components of lac coloring include laccaic acids A, B, C, and E. The Korean Food Additive Code regulates the use of lac coloring and prohibits its use in ten types of food products including natural food products. Since no commercial standards are available for laccaic acids A, B, C, and E, a standard for lac pigment itself was used to separate laccaic acids from the lac pigment molecule. A standard for each laccaic acid was then obtained by fractionation. To obtain pure lac pigment for use in food by High performance Liquid Chromatography Photo Diode Array (PDA), a C8 column yielded the best resolution among various tested columns and mobile phases. A qualitative analytical method using High Performance Liquid Chromatography (HPLC) Tandem Mass(LC-MS/MS) was developed. The conditions for fast and precise sample preparation begin with extraction using methanol and 0.3% ammonium phosphate, followed by concentration. The degree of precision observed for the analyses of ham, tomato juice and Red pepper paste was 0.3-13.1% (Relative Standard Deviation (RSD%)), degree of accuracy was 90.3-122.2% with r²=0.999 or above, and recovery rate was 91.6-114.9%. The limit of detection was 0.01-0.15 ㎍/mL, and the limits of quantitation ranged from 0.02 to 0.47 ㎍/mL. Lac pigment was not detected in 117 food products in the 10 food categories for which the use of lac pigment is banned. Multiple laccaic acids were detected in 105 food products in 6 food categories that are allowed to use lac color. Lac pigment concentrations range from 0.08 to 16.67 ㎍/mL.