• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.10-20
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• 2019

Irregular rainfall caused by climate change, in combination with non-point pollution, can cause water systems worldwide to suffer from frequent eutrophication and algal blooms. This type of water pollution is more common in agricultural prone to water system inflow of non-point pollution. Therefore, in this study, the correlation between Unmanned Aerial Vehicle(UAV) multi-spectral images and total phosphorus, total nitrogen, and chlorophyll-a with indirect association of algal blooms, was analyzed to identify the usability of UAV image to identify water quality characteristics in agricultural streams. The analysis the vegetation index Normalized Differences Index (NDVI), the Normalized Differences Red Edge(NDRE), and the Chlorophyll Index Red Edge(CIRE) for the detection of multi-spectral images and algal blooms collected from the target regions Yang cheon and Hamyang Wicheon. The analysis of the correlation between image values and water quality analysis values for the water sampling points, total phosphorus at a significance level of 0.05 was correlated with the CIRE(0.66), and chlorophyll-a showed correlation with Blue(-0.67), Green(-0.66), NDVI(0.75), NDRE (0.67), CIRE(0.74). Total nitrogen was correlated with the Red(-0.64), Red edge (-0.64) and Near-Infrared Ray(NIR)(-0.72) wavelength at the significance level of 0.05. The results of this study confirmed a significant correlations between multi-spectral images collected through UAV and the factors responsible for water pollution, In the case of the vegetation index used for the detection of algal bloom, the possibility of identification of not only chlorophyll-a but also total phosphorus was confirmed. This data will be used as a meaningful data for counterplan such as selecting non-point pollution apprehensive area in agricultural area.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.277-283
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• 2018

The crop growth model has been widely used for climate change impact assessment. Crop growth model require genetic coefficients for simulating growth and yield. In order to determine the genetic coefficients, regional growth monitoring data or yield trial data of crops has been used to calibrate crop growth model. The aim of this study is to verify that yield trial data of corn is appropriate to calibrate genetic coefficients of CERES-MAIZE. Field experiment sites were Suwon, Jinju, Daegu and Changwon. The distance from the weather station to the experimental field were from 1.3km to 27km. Genetic coefficients calibrated by yield trial data showed good performance in silking day. The genetic coefficients associated with silking are determined only by temperature. In CERES-MAIZE model, precipitation or irrigation does not have a significant effect on phenology related genetic coefficients. Although the effective distance of the temperature could vary depending on the terrain, reliable genetic coefficients were obtained in this study even when a weather observation site was within a maximum of 27 km. Therefore, it is possible to estimate the genetic coefficients by yield trial data in study area. However, the yield-related genetic coefficients did not show good results. These results were caused by simulating the water stress without accurate information on irrigation or rainfall. The yield trial reports have not had accurate information on irrigation timing and volume. In order to obtain significant precipitation data, the distance between experimental field and weather station should be closer to that of the temperature measurement. However, the experimental fields in this study was not close enough to the weather station. Therefore, When determining the genetic coefficients of regional corn yield trial data, it may be appropriate to calibrate only genetic coefficients related to phenology.

• Korean Journal of Heritage: History & Science
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• v.46 no.3
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• pp.114-133
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• 2013

This study aims to identify the natural damage of the Samcheonsaji Temple Site in Bukhansan National Park and to suggest the plans to minimize damage for the remains. The types of natural damage are classified into direct vegetation damage, indirect topographical damage, and artificial damage. The most popular causes of damage to temple sites include the roots of trees as direct vegetation damage and the soil erosion by rain or stream as topographical damage. Direct vegetation damage includes burial remains damaged by the root of trees and vines, but it is often observed that some trees have contributed to protection against collapse. Indirect topographical changes have damaged the ruins by soil erosion caused by floods or typhoons. Vegetation changes due to topographical reasons have also caused damage. Artificial reasons of damage include forestry operations and compaction by hikers. Based on the analysis of the findings, the following could be suggested as plans to resolve these problems: 1. Natural damage occurs slowly due to negligence. Therefore, it could be reduced by forestry improvement, including forest density control through thinning, planting to prevent landslides, maintaining grasslands nearby. 2. Deciduous broadleaf trees can be planted to reduce soil erosion by rainfall. It is necessary to maintain the density of forests at around $0.02{\sim}0.18trees/m^2$. 3. It would be good to grow Quercus spp and Carpinus spp or weaken the community of Robinia pseudoacacia and Pueraria lobata which disturb the ecosystem. Samcheonsaji Temple Site is located in Mt. Bukhan National Park that is a publicly owned property. Therefore, it is constantly maintained for natural preservation and vegetation management could be considered for the preservation of historical remains.

• Korean Journal of Ecology and Environment
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• v.51 no.4
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• pp.331-344
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• 2018

Lotic organisms in streams are affected by natural and anthropogenic disturbances such as increase of heavy rainfall event caused by climate change and flow regime change caused by weir constructions. Based on domestic and foreign literature, 157 Korean benthic macroinvertebrate taxa were selected species as potential lotic candidates. Three shoreline sites (total 54 samples) were surveyed consecutively before ('08~'09), during ('10~'12) and after ('13~'16) the construction of the weirs (Gangcheon, Yeoju and Ipo weir) in the Namhan-River for tracing changes of lotic communities. As a result, water flow of the Ipo-wier and water quality variables such as T-N, T-P, BOD5, etc. of the weir section revealed no significant changes. Physical habitat conditions such as the flow velocity and streambed substrate evidently changed. Particulary, flow velocity measured at sampling points along with each microhabitat drastically decreased and particle size of streambed substrate steadily decreased after weir constructions. Lotic organisms also decreased after construction, especially Hydropsychidae (insecta: Trichoptera) acutely decreased from $3,526ind.\;m^{-2}$ to $2ind.\;m^{-2}$ As a result of CCA, lotic species such as Hydropsyche valvata, Hydropsyche kozhantschikovi, Cheumatopsyche brevilineata, Cheumatopsyche KUa, Macrostemum radiatum, etc. correlated with the flow velocity, streambed substrate. Therefore, the decrease of the flow velocity and substrate size after weir construction seemed to be closely related to the decrease of the individual abundances of the lotic organisms independently of water quality. In order to evaluate the influence of the ecosystem on the flow regime change more accurately, it is necessary to study the indicator species based on the resistance or preference of the flow.

• Korean Journal of Ecology and Environment
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• v.52 no.2
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• pp.71-80
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• 2019

Effects of environmental factors on phytoplankton succession and community structure were studied in Lake Chuncheon located in Bukhan River, South Korea. The data were sampled at three sites such as CC1 (lower side), CC2 (middle side), and CC3 (upper side of Lake Chuncheon) from 2014 to 2017. The annual average precipitation in Lake Chuncheon was 992 mm during the study period (2014~2017), and the annual precipitation was lower than 800 mm in 2014 and 2015. The annual average water temperature, total phosphorus (TP), and total nitrogen (TN) ranged from 17.0 to $21.1^{\circ}C$, 0.012 to $0.019mg\;L^{-1}$, and 1.272 to $1.922mg\;L^{-1}$, respectively. The TN concentration was relatively high in 2015 compared with the other study years, as a drought continued from 2014 to 2015. When comparing the correlation between precipitation and environmental factors, water temperature (p<0.01) and TP(p<0.05) showed positive correlations with rainfall. The average numbers of phytoplankton cells by branch were 2,094, 2,182, and $3,108cells\;mL^{-1}$ in CC1, CC2, and CC3, respectively. CC3 is considered advantageous for phytoplankton growth, even in small pollution sources due to low water depth. As a result of analyzing the relationship between precipitation and phytoplankton, the correlation between the two was shown to be high for 2016 (p<0.01) and 2017 (p<0.05), which is when precipitation was high. However, the correlation was not clear to 2014 and 2015. The relationship between water temperature and phytoplankton indicated a negative correlation with diatoms (p<0.01), yet positive correlations with green algae (p<0.01) and cyanobacteria (p<0.01). Diatoms increased in spring and autumn, which are characterized by low water temperature, and green algae and cyanobacteria increased in summer, when the water temperature is high. Our findings provide a scientific basis for characteristics of phytoplankton and water quality and management at the Lake Chuncheon.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.21-36
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• 2019

Dead fuel moisture content is a key variable in fire danger rating as it affects fire ignition and behavior. This study evaluates simple regression models estimating the moisture content of standardized 10-h fuel stick (10-h FMC) at three sites with different characteristics(urban and outside/inside the forest). Equilibrium moisture content (EMC) was used as an independent variable, and in-situ measured 10-h FMC was used as a dependent variable and validation data. 10-h FMC spatial distribution maps were created for dates with the most frequent fire occurrence during 2013-2018. Also, 10-h FMC values of the dates were analyzed to investigate under which 10-h FMC condition forest fire is likely to occur. As the results, fitted equations could explain considerable part of the variance in 10-h FMC (62~78%). Compared to the validation data, the models performed well with R2 ranged from 0.53 to 0.68, root mean squared error (RMSE) ranged from 2.52% to 3.43%, and bias ranged from -0.41% to 1.10%. When the 10-h FMC model fitted for one site was applied to the other sites, $R^2$ was maintained as the same while RMSE and bias increased up to 5.13% and 3.68%, respectively. The major deficiency of the 10-h FMC model was that it poorly caught the difference in the drying process after rainfall between 10-h FMC and EMC. From the analysis of 10-h FMC during the dates fire occurred, more than 70% of the fires occurred under a 10-h FMC condition of less than 10.5%. Overall, the present study suggested a simple model estimating 10-h FMC with acceptable performance. Applying the 10-h FMC model to the automatic mountain weather observation system was successfully tested to produce a national-scale 10-h FMC spatial distribution map. This data will be fundamental information for forest fire research, and will support the policy maker.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.140-146
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• 2019

In order to manage non-point sources, the paradigm of the system should be changed so that the management of non-point sources will be systematized from the beginning of the use and development of the land. It is necessary to change the method of national subsidy support and poeration plan for the non-point source management area. In order to increase the effectiveness of the non-point source reduction project, it is necessary to provide a minimum support ratio and to provide additional support according to the performance of the local government. A new system should be established to evaluate the performance of non-point source reduction projects and to monitor the operational effectiveness. It is necessary to establish the related rules that can lead the local government to take responsible administration so that the local governments faithfully carry out the non-point source reduction project and achieve the planned achievement and become the sustainable maintenance. Alternative solutions are needed, such as problems with the use of $100{\mu}m$ filter in automatic sampling and analysis, timely acquisition of water sampling and analysis during rainfall, and effective management of non-point sources network operation management. As an alternative, it is necessary to consider improving the performance of sampling and analysis equipment, and operate the base station. In addition, countermeasures are needed if the amount of pollutant reduction according to the non-point source reduction facility promoted by the national subsidy is required to be used as the development load of the TMDLs. As an alternative, it is possible to consider supporting incentive type of part of the maintenance cost of the non-point source reduction facility depending on the amount of pollutants reduction.

• Journal of the Korean Society for Environmental Technology
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• v.19 no.6
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• pp.503-513
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• 2018

In order to continuous watershed management and improve water quality at Yeong-san river system, we analyzed and evaluated data on the monitoring of small stream in city and county boundaries within the watershed. In-period monitoring is estimated to be more frequent in the second quarter than the first quarter, so it should be considered when evaluating the target water quality by setting the target water quality. A small stream in the Yeong-san river system has higher concentration in the downstream area than the upstream area. As a result of calculating the load of the measuring point, Y.b B3(Pungyeongjeongcheon) and Y.b E1(Sampocheon) were high. The result of correlation analysis by monitoring point in order to evaluate the correlation between BOD and T-P items, BOD was highly correlated with COD and TOC, and was affected by emission of pollutants related to organic matter. T-P was highly correlated with SS and COD, and was affected by rainfall. This study will provide basic data and direction for designing efficient and scientific method for water quality management by analyzing accumulated water quality data by conducting long-term monitoring.

• Journal of the Korean Geosynthetics Society
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• v.20 no.2
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• pp.23-33
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• 2021

In Korea, many reservoirs have been built for the purpose of solving the food shortage problem and supplying agricultural water. However, the current 75.6% of the reservoirs are in serious aged as more than 50 years have passed since the year of construction. In the case of such an aging reservoir, the stability due to scour and erosion inside the reservoir is very reduced, and if concentrated rainfall due to recent abnormal weather occurs, the aging reservoir may collapse, leading to a lot of damage to property and human life. Accordingly, each agency that manages aging reservoirs uses Ordinary Portland Cement (OPC) as an injection material and applies the grouting method. However, in the case of OPC, it may deteriorate over time and water leakage may occur again. And there are environmental problems such as consumption of natural resources and generation of greenhouse gases. So, there is a need to develop new materials and methods that can replace the OPC. In this study, an laboratory test and analysis were performed on the grout material developed to induce a curing reaction similar to that of OPC by recycling power plant byproduct. In addition, test in the field such as electric resistivity survey, Standard Penetration Test (SPT), and field permeability test were performed to analyzed to reinforcement effect and determine the possibility of using instead of OPC. As a results of the test, in the case of recycled power plant byproduct, the compressive strength was 2.9 to 3.2 times and the deformation modulus was 2.3 to 3.3 times higher, indicating that it is excellent in strength and can be used instead of OPC. And it was analyzed that the N value of the reservoir was increased by 1~2, and the coefficient of permeability (k) decreased to the level of 8.9~42.5%. showing sufficient reinforcing effect in terms of order.