• Journal of the Korean Geographical Society
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• v.42 no.1 s.118
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• pp.133-155
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• 2007

The sustainable urban development has emerged as a new paradigm of urban studies in recent years. A review of the literature of land use and transport policies in relation to sustainable development reveals a consensus that the main objectives of sustainable strategy should decrease the numbers and length of journeys, and change the land use pattern towards mixed use and high density. However, there is a lack of empirical research as to what types of policies might influence effectively the reduction in the energy consumption and emission of $CO_2$. in order to sustain urban development. This paper tries to construct the conceptual structure of the PSS(planning support system), which is designed to the simulation of the probable effects of policies and planning of different kinds in cities, and evaluate the sustainablilty level according to construct the structure of the PSS(planning support system), which is designed to the simulation of the probable effects of policies and planning of different kinds in cities, and evaluate the sustainablilty level according to the alternative scenarios. The PSS is composed of three components (input-modeling-output). The core of PSS is integrating land use-transport-environment modeling. The advantages of integrating land use-transport-environment modeling are well known, but there are very few such integrated modeling packages in practice. So this paper tries to apply TRANUS software, which is an integrated land use and transport model. The TRANUS system was calibrated to city of Yongin for the base year. The purpose of the application of TRANUS to Yongin is to examine the operability of TRANUS system in Korea. From the outputs and results of operating the system, TRANUS may be effectively used to evaluate the effects of alternative sustainable urban development policies, since sustainablilty indicators can be extracted from several aspects such as land use consumption, total trips, distance and cost, energy consumption, ratio of transport split.

• The Korean Journal of Pesticide Science
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• v.10 no.4
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• pp.279-288
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• 2006

Three different experiments were undertaken to investigate the runoff and erosion loss of diazinon and metolachlor from sloped-field by rainfall. The mobility of two pesticides and which phase they were transported by were examined in adsorption study, the influence of rainfall pattern and slope degree on the pesticide losses were evaluated in simulated rainfall study, and the pesticide losses from soybean field comparing with bare soil were measured in field lysimeter study. Freundlich adsorption parameter (K) ranged $1.6{\sim}2.0$ for metolachlor and $4.0{\sim}5.5$ for diazinon. The K values of pesticides by the desorption method were higher than those ones by the adsorption method. Another parameter (1/n) in Freundlich equation for the pesticides tested ranged $0.96{\sim}1.02$ by desorption method and $0.87{\sim}1.02$ by adsorption method. By the SSLRC's classification for pesticide mobility of diazinon and metolachlor were classified as moderately mobile ($75{\leq}Koc$ <500). Runoff and erosion losses of pesticides by three rainfall scenarios were $0.5{\sim}1.0%$ and $0.1{\sim}0.7%$ for metolachlor and $0.1{\sim}0.6%$ and $0.1{\sim}0.2%$ for diazinon. Distribution of pesticides in soil polite were investigated after the simulated rainfall events. Metolachlor was leached to $10{\sim}15$ cm soil layer and diazinon was leached to $5{\sim}10$ cm soil layer. Losses of each pesticide in the 30% of sloping degree treatment were $0.2{\sim}1.9$ times higher than those ones in the 10% of sloping degree treatment. Pesticide losses from a series of lysimeter plots in sloped land by rainfall ranged $1.0{\sim}3.1%$ for metolachlor and $0.23{\sim}0.50%$ for diazinon, and were $1/3{\sim}2.5$ times to the ones in the simulated rainfall study. The erosion rates of pesticides from soybean-plots were $21{\sim}75%$ lower than the ones from bare soil plots. The peak runoff concentration in soybean-plots and bare soil plots were $1{\sim}9{\mu}gL^{-1}$ and $3{\sim}16{\mu}gL^{-1}$ for diazinon, $7{\sim}31{\mu}gL^{-1}$ and $5{\sim}40{\mu}gL^{-1}$ for metolachlor, respectively.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.789-792
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• 2010

Major impacts of climate change expert that soil erosion rate may increase during the $21^{st}$ century. This study was conducted to assess the potential impacts of climate change on soil erosion by water in Korea. The soil loss was estimated for regions with the potential risk of soil erosion on a national scale. For computation, Universal Soil Loss Equation (USLE) with rainfall and runoff erosivity factors (R), cover management factors (C), support practice factors (P) and revised USLE with soil erodibility factors (K) and topographic factors (LS) were used. RUSLE, the revised version of USLE, was modified for Korean conditions and re-evaluate to estimate the national-scale of soil loss based on the digital soil maps for Korea. The change of precipitation for 2010 to 2090s were predicted under A1B scenarios made by National Institute of Meteorological Research in Korea. Future soil loss was predicted based on a change of R factor. As results, the predicted precipitations were increased by 6.7% for 2010 to 2030s, 9.5% for 2040 to 2060s and 190% for 2070 to 2090s, respectively. The total soil loss from uplands in 2005 was estimated approximately $28{\times}10^6$ ton. Total soil losses were estimated as $31{\times}10^6$ ton in 2010 to 2030s, $31{\times}10^6$ ton in 2040 to 2060s and $33{\times}10^6$ ton in 2070 to 2090s, respectively. As precipitation increased by 17% in the end of $21^{st}$ century, the total soil loss was increased by 12.9%. Overall, these results emphasize the significance of precipitation. However, it should be noted that when precipitation becomes insignificant, the results may turn out to be complex due to the large interaction among plant biomass, runoff and erosion. This may cause increase or decrease the overall erosion.

• 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.

• Journal of Climate Change Research
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• v.1 no.2
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• pp.121-131
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• 2010

This study was carried out to evaluate spatial variations in rice production areas by simulating rice growth and yield with CERES-Rice growth model under GCM $2{\times}CO_2$ climate change scenarios. A modified window version(v4.0) of CERES-Rice was used to simulate the growth and development of three varieties, representing early, medium, and late maturity classes. Simulated growth and yield data of the three cultivars under the climate for 1971 to 2000 was set as a reference. Compared with the current normal(1971 to 2000), heading period from transplanting to heading date decreased by 7~8 days for the climate in $2^{\circ}C$ increase over normal, and 16~18 days for the climate in UKMO with all maturity classes, while change of ripening period from heading to harvesting date was different with maturity classes. That is, physical maturity was shortened by 1~3 days for early maturity class and 14~18 days for late maturity class under different climate change scenarios. Rice yield was in general reduced by 4.5%, 8.2%, 9.9%, and 14.9% under the climate in $2^{\circ}C$, $3^{\circ}C$, $4^{\circ}C$, and about $5^{\circ}C$ increase, respectively. The yield reduction was due to increased high temperature-induced spikelet sterility and decreased growth period. The results show that predicted climate changes are expected to bring negative effects in rice production in Korea. So, it is required for introduction of new agricultural technologies to adapt to climate change, which are, for example, developing new cultivars, alternations of planting dates and management practices, and introducing irrigation systems, etc.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.2
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• pp.95-110
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• 2022

This study was conducted to determine the extent to which climate change is expanding areas in which barley can be successfully cultivated. In 2019 and 2020, we collected data on areas that had requested certified seeds from the Korea Seed and Variety Service to determine potential cultivation areas. In addition, we surveyed the growth and yield of different types of barley in fields. Certified seeds of hulled and dehulled barley were requested by farmers across Korea from the Korea Seed and Variety Service in both years. Areas that were provided with certified seeds were considered potential barley cultivation areas. The varieties and use rates of certified seeds varied based on the barley type and region. For example, certified seeds of dehulled barley in 2019 and 2020 were not used in some areas, whereas in others, these seeds constituted 100% of the seeds sown for barley crops. In 2019 and 2020, the average sowing days in Korea were from October 17 to November 9 for dehulled barley, October 26 to November 13 for hulled barley, October 19 to November 5 for malting barley, and October 3 to November 1 for naked oats. Thus, the sowing days of the barley types varied depending on the area and year they were used. For example, in the case of hulled barley in Jeonnam, some farmers sowed until December 12. The yield per 10 a of barley cultivation was typically higher in the main production areas than in the cultivation limit areas. In extreme cases, harvest was impossible in some cultivation limited areas, such as Gangwon-do. Based on the current 20-year January minimum average temperature (JMAT) in Korea (2002-2021), climate change scenarios suggest that barley cultivation is feasible, provided that the minimum temperature in January is no lower than -10℃, -8℃, and -4℃ for hulled barley, dehulled barley, and for malting barley and naked oats, respectively. Additionally, cultivation of barley across South Korea seems feasible based on data on certified barley seeds by area. Although both JMAT and certified seed data suggest that barley cultivation across Korea is feasible, our survey results of barley growth and yield showed that harvest was impossible in certain cultivation areas, such as Gangwon-do. Therefore, climate change scenarios related to the cultivation limits of different barley types need to be re-estimated by factoring in survey data on the growth and yield of crops within those cultivation areas.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Maritime Security
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• v.7 no.1
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• pp.31-60
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• 2023

This study proposes a new convergence weapon system that combines the covert placement and detection abilities of a self-propelled mobile mine with the rapid tracking and attack abilities of supercavitating rocket torpedoes. This innovative system has been designed to counter North Korea's new underwater weapon, 'Haeil'. The concept behind this convergence weapon system is to maximize the strengths and minimize the weaknesses of each weapon type. Self-propelled mobile mines, typically placed discreetly on the seabed or in the water, are designed to explode when a vessel or submarine passes near them. They are generally used to defend or control specific areas, like traditional sea mines, and can effectively limit enemy movement and guide them in a desired direction. The advantage that self-propelled mines have over traditional sea mines is their ability to move independently, ensuring the survivability of the platform responsible for placing the sea mines. This allows the mines to be discreetly placed even deeper into enemy lines, significantly reducing the time and cost of mine placement while ensuring the safety of the deployed platforms. However, to cause substantial damage to a target, the mine needs to detonate when the target is very close - typically within a few yards. This makes the timing of the explosion crucial. On the other hand, supercavitating rocket torpedoes are capable of traveling at groundbreaking speeds, many times faster than conventional torpedoes. This rapid movement leaves little room for the target to evade, a significant advantage. However, this comes with notable drawbacks - short range, high noise levels, and guidance issues. The high noise levels and short range is a serious disadvantage that can expose the platform that launched the torpedo. This research proposes the use of a convergence weapon system that leverages the strengths of both weapons while compensating for their weaknesses. This strategy can overcome the limitations of traditional underwater kill-chains, offering swift and precise responses. By adapting the weapon acquisition criteria from the Defense force development Service Order, the effectiveness of the proposed system was independently analyzed and proven in terms of underwater defense sustainability, survivability, and cost-efficiency. Furthermore, the utility of this system was demonstrated through simulated scenarios, revealing its potential to play a critical role in future underwater kill-chain scenarios. However, realizing this system presents significant technical challenges and requires further research.

• Korean Journal of Environmental Agriculture
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• v.26 no.4
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• pp.343-350
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• 2007

Three different experiments were carried out to investigate the runoff and erosion losses of endosulfan from sloped-field by rainfall. The mobility of endosulfan and which phase it was transported by were examined in adsorption study, the influence of rainfall pattern and slope degree on the pesticide loss were evaluated in simulated rainfall study, and the pesticide losses from soybean-grown field comparing with bare soil were measured in field lysimeter study. Adsorption parameter (K) of endosulfan ranged from 77 to 131 by adsorption method and K values by the desorption method were higher than those by the adsorption method. By the SSLRC's classification for pesticide mobility endosulfan was classified as non-mobile class ($K_{oc}>4,000$). Runoff and erosion loss of endosulfan by three rainfall scenarios ranged from 3.4 to 5.6%and from 4.4 to 15.6%of the amount treated. Endosulfan residues were mainly remained at the top 5 cm of soil depth after the simulated rainfall study. Pesticide loss in case of 30%-slope degree ranged from 0.6 to 0.9 times higher than those in case of 10%-slope degree. The difference of pesticide runoff loss was related with its concentration in runoff water and the difference of pesticide erosion loss would related closely with the quantity of soil eroded. Endosulfan losses from a series of lysimeter plots in sloped land by rainfall ranged from 5 to 35% of the amount treated. The erosion rate of endosulfan from soybean-plots was 66% of that from bare soil plots. The effect of slope conditions was not great for runoff loss, but was great for erosion loss as increasing to maximum $4{\sim}12$ times with slope degree and slope length. The peak runoff concentration of endosulfan in soybean-plots and bare soil plots ranged from 8 to 10 and from 7 to $9{\mu}gL^{-1}$ on nine plots with different slope degree and slope length. Therefore the difference of the peak runoff concentrations between bare soil plots and soybean-plots were not great.

• The KIPS Transactions:PartD
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• v.19D no.3
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• pp.237-246
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• 2012

Although the development of Global Positioning System (GPS) are more and more mature, its accuracy is just acceptable for outdoor positioning, not positioning for the indoor of building and the underpass. For the positioning application area for the indoor of building and the underpass, GPS even cannot achieve that accuracy because of the construction materials while the requirement for accurate positioning in the indoor of building and the underpass, because a space, a person is necessary, may be very small space with several square meters in the indoor of building and the underpass. The Received Signal Strength (RSS) based localization is becoming a good choice especially for the indoor of building and the underpass scenarios where the WiFi signals of IEEE 802.11, Wireless LAN, are available in almost every indoor of building and the underpass. The fundamental requirement of such localization system is to estimate location from Access Point (AP) to mobile device using RSS at a specific location. The Multi-path fading effects in this process make RSS to fluctuate unpredictably, causing uncertainty in localization. To deal with this problem, the combination for the method of Neural Networks and Push-Pull Estimation is applied so that the carried along the devices can learn and make the decision of position using mobile device where it is in the indoor of building and the underpass.