• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.1-28
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• 2019

This study analyzed the density and mortality rate of Korean fir at 9 sites where individuals of Korean firs were marked into the live and dead trees with coordinates on orthorectified aerial images by digital photogrammetric system. As a result of the analysis, Korean fir in each site showed considerable heterogeneity in density and mortality rate depending on the location within site. This make it possible to assume that death of Korean fir can occur by specific factors that vary depending on the location. Based on the analyzed densities and mortality rates of Korea fir, we investigated the correlation between topographic factors such as altitude, terrain slope, drainage network, solar radiation, aspect and the death of Korean fir. The density of Korean fir increases with altitude, and the mortality rate also increases. A negative correlation is found between the terrain slope and the mortality rate, and the mortality rate is higher in the gentle slope where the drainage network is less developed. In addition, it is recognized that depending on the aspect, the mortality rate varies greatly, and the mean solar radiation is higher in live Korean fir-dominant area than in dead Korean fir-dominant area. Overall, the mortality rate of Korean fir in Mt. Halla area is relatively higher in areas with relatively low terrain slope and low solar radiation. Considering the results of previous studies that the terrain slope has a strong negative correlation with soil moisture and the relationship between solar radiation and evaporation, these results lead us to infer that excess soil moisture is the cause of Korean fir mortality. These inferences are supported by a series of climate change phenomena such as precipitation increase, evaporation decrease, and reduced sunshine duration in the Korean peninsula including Jeju Island, increase in mortality rate along with increased precipitation according to the elevation of Mt. Halla and the vegetation change in the mountain. It is expected that the spatial patterns in the density and mortality rate of Korean fir, which are controlled by topography such as altitude, slope, aspect, solar radiation, drainage network, can be used as spatial variables in future numerical modeling studies on the death or decline of Korean fir. In addition, the method of forest distribution survey using the orthorectified aerial images can be widely used as a numerical monitoring technique in long - term vegetation change research.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.55-64
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• 2019

The flowering seasons can be advanced due to climate change that would cause an abnormally warm winter. Such warm winter would increase the frequency of crop damages resulted from sudden occurrences of low temperature before and after the vegetative growth stages, e.g., the period from germination to flowering. The degree and pattern of freezing damage would differ by the development stage of each individual fruit tree even in an orchard. A critical temperature, e.g., killing temperature, has been used to predict freeze damage by low-temperature conditions under the assumption that such damage would be associated with the development stage of a fruit flower bud. However, it would be challenging to apply the critical temperature to a region where spatial variation in temperature would be considerably high. In the present study, a phenological model was used to estimate major bud development stages, which would be useful for prediction of regional risks for the freeze damages. We also derived a linear function to calculate a probabilistic freeze risk in spring, which can quantitatively evaluate the risk level based solely on forecasted weather data. We calculated the dates of freeze damage occurrences and spatial risk distribution according to main production areas by applying the spring freeze risk function to apple, peach, and pear crops in 2018. It was predicted that the most extensive low-temperature associated freeze damage could have occurred on April 8. It was also found that the risk function was useful to identify the main production areas where the greatest damage to a given crop could occur. These results suggest that the freezing damage associated with the occurrence of low-temperature events could decrease providing early warning for growers to respond abnormal weather conditions for their farm.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.75-89
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• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.150-164
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• 2022

This study was conducted to provide basic information for the development of silvicultural guidelines and manuals. This was achieved through analysis of tree and stand characteristics according to the first and second thinning in Korean white pine plantations. Data were collected from permanent plots installed at Korean white pine plantations according to thinning intensity, and residual tree and stand variables, including diameter at breast height (DBH), volume, and mortality at age 19-43, were analyzed using data repeatedly collected in 4-5 measurements by experiments. According to one-way variance of analysis, tree DBH and volume were significantly different according to thinning intensity (p<0.05). DBH distribution was skewed to the left side over time as thinning intensity was heavier. Thus, tree DBH values were larger in heavy thinning plots with increased age. The periodic annual increment (PAI) of DBH was higher with heavier thinning intensity and fewer years after thinning. The PAI range by thinning intensity was 0.48-0.95 cm/year at age 19-24. In addition, the PAI increased in heavy thinning plots after the second thinning; The PAI range by thinning intensity was 0.29-0.67 cm/year after the second thinning at age 37-42. The PAI of tree volume differed according to thinning intensity, and the PAI value did not decrease obviously, in contrast to the pattern of the DBH PAI. Stand volume was generally higher in high-density stands, and the PAI of stand volume was high in unthinned and light thinning plots. Mortality was highest in unthinned plots, and the differences in mortality according to thinning intensity increased over time. Consequently, the growth of DBH and tree volume was lower as stand density increased, but this growth was facilitated with appropriate first and second thinning operations.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.87-97
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• 2023

In this study, we examined the effects of a large wildfire in the coastal area of Uljin-gun. The analysis of water quality and the dominant species, species composition, and community structure of marine algal was conducted quarterly in 2022 at Nagok (F-1), Hujeong (F-2), Bongpyeong (F-3), and Gongse Port (F-C) in Uljin-gun. As a result of water quality analysis, the pH, a factor of wildfire impact was 8.07~8.30 and 8.12~8.48 in surface and bottom layers, respectively, which are normal values in coastal waters of the East Sea, suggesting no direct impact from wildfires. By marine algal species composition, the coastal areas show the following order: Rhodophyta (58.1%) > Ochrophyta (25.8%) > Chlorophyta (14.5%) > Magnoliophyta (1.6%). By season, Undaria pinnatifida was the most dominant at Nagok and Hujeong in March and June, which in September and November, Gelidium elegans and Lithophyllum sp. were the most dominant in Bongpyeong and Gongse Port, respectively. In the cluster analysis, the stations were divided into two groups according to presence and absence of specific marine algal by season. The dominant species were U. pinnatifida, G. elegans and D. divaricata in group A, and Lithophyllum sp. was mainly present in group B. Thus, the species composition and group structure reflected the normal seasonal change pattern with water temperature variation and showed little significant difference from the control site, suggesting no direct effects of the wildfire on algae distribution in Uljin.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• Journal of Life Science
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• v.33 no.11
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• pp.887-896
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• 2023

The inflammatory response have been considered as one of important targets for cancer treatment because they play a key role during all steps of tumor development including initiation, promotion, malignant conversion and progression. To investigate the anti-inflammatory response during anti-tumor activity of an aqueous extracts of Ecklonia cava (AEC), alterations on the distribution of mast cells and the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), nuclear factor (NF)-κB, inflammasome compositional protein and inflammatory cytokines were examined in CT26 colon tumor-bearing BALB/cKorl syngeneic mice after administrating AEC for five weeks. After treatment of AEC, total weight of tumor and necrotic region of tumor section were significantly decreased compared to vehicle treated group. The number of infiltered mast cells was higher in AEC treated group than vehicle treated group, while the expression levels of COX-2 and iNOS were decreased in AEC treated group. Also, similar decrease pattern were detected in the expression levels of NF-κB, NLR family pyrin domain containing 3 (NLRP3), apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) and caspase-1 (Cas-1) after AEC treatment although the decrease rate was varied. Furthermore, the mRNA expressions of three inflammatory cytokines including tumor necrosis factor-α (TNF-α), interleukin-1α (IL-1α) and interleukin-6 (IL-6) were remarkably decreased in AEC treated group compared to vehicle treated group. These results suggest that inhibition of inflammatory response may be tightly associated with anti-tumor activity of AEC in CT26 colon tumor-bearing BALB/cKorl syngeneic mice.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.1
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• pp.56-66
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• 2008

Subtidal surface currents are derived from HF radar measurements in the Saemangeum coastal ocean of the Yellow sea in July 2002 and from September to November 2004. The surface current field is analyzed to examine the effect of wind, river plume and coastline change on the spatial distribution and temporal variation of the surface currents. In July 2002, average wind speed was 0.5 m/s and freshwater discharge from the Keum River was $0.88{\times}10^7\;ton/day$. Temporal mean currents ($\overline{U}$) flow to the northwest with speed of $7{\sim}10\;cm/s$ near the Keum River estuary, to the west as fast as 13 cm/s near the opening gap of the Saemangeum $4^{th}$ dyke, and to the northwest off the Gogunsan-archipelago. This flow pattern is a result of the Keum River plume dispersal and tide-residual currents from the opening gap of the Saemangeum $4^{th}$ dyke. Time series of spatially-averaged current (<$U-\overline{U}$>) direction is highly (r=0.98) correlated with wind direction. From September to November 2004, the opening gap of the Saemangeum $4^{th}$ dyke was closed, northwesterly wind blew with speed of 2.5 m/s on average and the Keum River discharge was $1.19{\times}10^7\;ton/day$. Temporal mean current field ($\overline{U}$) has weak surface flow in most of the coastal ocean and relatively strong currents flow to the southwest with speed of 10 cm/s along the shape coastline of the Gogunsan-archipelago and the Saemangeum $4^{th}$ dyke. The strong flow is generated by the prevailing northwesterly wind which pushes the Keum River plume toward the Saemangeum $4^{th}$ dyke. The residual currents from the opening gap of the Saemangeum $4^{th}$ dyke disappeared and correlation coefficient between time series of spatially-averaged current () direction and the wind direction is 0.69.