• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.3
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• pp.42-50
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• 2012

City squares are public open spaces which are closely related to the peoples daily lives. Most squares are located in the center of the city, and they are usually used for community gatherings and they are suitable for open markets, music concerts, political rallies, and other events. City squares also play an important role as a grand public place operating in multi functions that require involvement of more people. The purpose of this study is to examine satisfaction on the spatial components, characteristics, and the user satisfaction in City Squares. The slady also analyzed the relationship between the satisfaction about spatial components, characteristics and it also shows that the user satisfaction is followed. This study sites are made in 3 grand public places in the center of Seoul including the Seoul plaza, Cheonggye Plaza, and Gwanghwarnun Square. Data were analyzed using several statistical methods such as descriptive statistics, factor analysis, ANOVA, correlation and regression. Results of the study are as follows: First, factor analysis carried out to extract the various factors of satisfaction on the sites; spatial components, usability, amenity/security, and spatial characteristics. User satisfaction concerning usability factor was higher than the satisfaction of the other factors. This result represented that the slady sites play an important role to the public open spaces in the city. Second, users showed high user satisfaction to study sites, and user satisfaction rate toward the Gwanghwarnun Square is the highest because of its facility planuing. Finally, user satisfactim was strongly correlated on the usability factor of spatial planning. Also, the significant correlations between the user satisfaction and the other factors such as spatial components, security, and spatial characteristics of spatial planning are presented. Results of this study can help guide the planning and management of the city square as a public open space based on the understanding of user perception and satisfaction.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1117-1132
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• 2019

Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1475-1490
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• 2021

Detecting oil spill area using statistical characteristics of SAR images has limitations in that classification algorithm is complicated and is greatly affected by outliers. To overcome these limitations, studies using neural networks to classify oil spills are recently investigated. However, the studies to evaluate whether the performance of model shows a consistent detection performance for various oil spill cases were insufficient. Therefore, in this study, two CNNs (Convolutional Neural Networks) with basic structures(Simple CNN and U-net) were used to discover whether there is a difference in detection performance according to the structure of CNN and distribution characteristics of oil spill. As a result, through the method proposed in this study, the Simple CNN with contracting path only detected oil spill with an F1 score of 86.24% and U-net, which has both contracting and expansive path showed an F1 score of 91.44%. Both models successfully detected oil spills, but detection performance of the U-net was higher than Simple CNN. Additionally, in order to compare the accuracy of models according to various oil spill cases, the cases were classified into four different categories according to the spatial distribution characteristics of the oil spill (presence of land near the oil spill area) and the clarity of border between oil and seawater. The Simple CNN had F1 score values of 85.71%, 87.43%, 86.50%, and 85.86% for each category, showing the maximum difference of 1.71%. In the case of U-net, the values for each category were 89.77%, 92.27%, 92.59%, and 92.66%, with the maximum difference of 2.90%. Such results indicate that neither model showed significant differences in detection performance by the characteristics of oil spill distribution. However, the difference in detection tendency was caused by the difference in the model structure and the oil spill distribution characteristics. In all four oil spill categories, the Simple CNN showed a tendency to overestimate the oil spill area and the U-net showed a tendency to underestimate it. These tendencies were emphasized when the border between oil and seawater was unclear.

• Journal of Wetlands Research
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• v.20 no.4
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• pp.398-409
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• 2018

Organic farming practices including loach based ecosystem-farming have been demonstrated to be effective in conjunction with rice farming to increase yield and quality. This new form of farming combines agriculture and fishery and is quickly developing into a new industry. The current study investigated the effect of rice-fish mixed farming system on the vegetation-diversity function. Vegetation within the four study sites was surveyed and analyzed based on plant taxonomy. The vegetation survey demonstrated that 127 taxa of 38 families, 100 genera, 107 species, and 20 varieties occurred within the study sites. A total of 15 plant species taxa occurred in the rice-fish mixed paddy fields with a fish habitat and did not occur in the conventional paddy field lacking fish habitat. This difference is thought to arise from differences in moisture requirements for vegetation. Life form analysis demonstrated differences in hemicryptophytes, therophytes, and hydrophytes according to fish habitat. The naturalized plants identified were also determined to be species widely distributed throughout Korea. Frequency analysis demonstrated that the rice-fish mixed paddy fields with a fish habitat had a high ratio of both obligate and facultative wetland plants relative to the conventional paddy field. Based on the study results, it is likely that vegetation-diversity will increase with environment diversity. However, no statistical significance was observed according to paddy types. Future research should aim to identify additional environmental factors, including the existence of fish habitat, habitat area, depth of fish habitat, hydrological parameters, water quality, and paddy soil environment, to enhance vegetation-diversity and biocultural diversity.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.695-703
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• 2018

This study was conducted to suggest a sustainable farming practice forresource recycling in vegetable gardens of North Korea. In North Korea, farmers are allowed to own private vegetable gardens less than $100m^2$. However, usage of fertilizers in private vegetable gardens is very limited due to economic sanctions by UN security council. If North and South Korea initiated the cooperative action in the near future, agricultural sector would be the highest priority cooperation area. Considering the current North Korean situation in agriculture, we would like to suggest a method for producing organic fertilizer manure. For raw materials for producing manure, we selected corn byproduct, which is the most abundant material, and rabbits' feces, which are easily obtained from individual private farms in North Korea. As we cannot get corn byproducts and rabbits' feces from North Korea, we prepared samples of corn byproducts and rabbits; feces from many places in South Korea. After statistical analysis of variance, there was no significant difference in the T-N contents of corn byproducts from Gyeonggi, Gangwon, Chungnam, Chungbuk, Jeollabuk and Gyeongsangnam-dos, which indicates that the fertilizing quality of corn byproducts does not vary significantly in the spatial scale of South. Korea. In this sense, if we use corn samples from Gyeonggi province, they would not be very different from those of North Korean regions. Physicochemical properties of rabbits' feces were different between those eating feed grains and those eating plants only. Hence, we used rabbits' feces of the rabbits from Yeonchun area, which were fed by plants only. Using three different mixing ratios of corn byproducts and rabbits' feces, composting was conducted for 60 days. The mixing ratio of 1:1 produced the manure with % T-N of 1.98% and OM/N ratio of 31.7 after 30 days of composting, which is comparable to the quality of commercial manure.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.265-274
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• 2021

Outlier detection research in ocean data has traditionally been performed using statistical and distance-based machine learning algorithms. Recently, AI-based methods have received a lot of attention and so-called supervised learning methods that require classification information for data are mainly used. This supervised learning method requires a lot of time and costs because classification information (label) must be manually designated for all data required for learning. In this study, an autoencoder based on unsupervised learning was applied as an outlier detection to overcome this problem. For the experiment, two experiments were designed: one is univariate learning, in which only SST data was used among the observation data of Deokjeok Island and the other is multivariate learning, in which SST, air temperature, wind direction, wind speed, air pressure, and humidity were used. Period of data is 25 years from 1996 to 2020, and a pre-processing considering the characteristics of ocean data was applied to the data. An outlier detection of actual SST data was tried with a learned univariate and multivariate autoencoder. We tried to detect outliers in real SST data using trained univariate and multivariate autoencoders. To compare model performance, various outlier detection methods were applied to synthetic data with artificially inserted errors. As a result of quantitatively evaluating the performance of these methods, the multivariate/univariate accuracy was about 96%/91%, respectively, indicating that the multivariate autoencoder had better outlier detection performance. Outlier detection using an unsupervised learning-based autoencoder is expected to be used in various ways in that it can reduce subjective classification errors and cost and time required for data labeling.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.527-536
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• 2022

The purpose of this study is to predict changing traffic environments and related economic effects by reflecting the changed KTDB and socio-economic indicators pertaining to Mulgeum station, a general railway stop, when it is confirmed as a KTX stop. To analyze the data of this study, socioeconomic indicators and the general status of transportation facility operations were investigated with reference to related statistical data, centered on the country overall and on Yangsan city in particular. In addition, we investigated and referenced the railroad facility construction plan and train operation plan, which are national high-level plans related to land development and transportation network construction. Currently, there are only ITX trains (4 times/day) and Mugunghwa trains (29 times/day) that stop at Mulgeum station in Yangsan, meaning that passengers cannot use KTX trains in the Yangsan area. In particular, the need for a KTX stop at Mulgeum station has been continuously raised because train users in the Yangsan area have inconvenient transportation in that they must travel 40 minutes to Ulsan station or 30 minutes to Gupo station to use the KTX. As a result of analyzing railroad transportation demand that will change in the future as the KTX stop at Mulgeum station is confirmed, the number of passengers boarding and arriving at Mulgeum station is predicted to be 1,674 passengers/day by 2025. In addition, the numbers of train passengers that are converted from Ulsan and Gupo stations due to the stop at Mulgeum station are predicted to be 594 passengers/day boarding and 562 passengers/day arriving by 2025. In the future, if Yangsan citizens use the KTX Mulgeum station, the access time to Mulgeum station can be shortened to 22 minutes from 65 minutes, and it is predicted that the inconvenience of transferring between railroads will be resolved, with the waiting time for transfers reduced by up to a maximum of 40 minutes. Therefore, the economic effect of creating a KTX stop at Mulgeum station was analyzed to be B/C=1.823 when general railroad operating costs are not taken into account and B/C=2.127 when general railroad operating costs are considered. In conclusion, when using KTX trains to visit the Seoul Metropolitan Area, it takes 2 hours and 43 minutes to use Mulgeum station without using Ulsan station or Gupo station, which is considered to be very effective for reducing travel times and improving the economic feasibility of this development; it is also expected that Yangsan city will be able to improve accessibility and mobility to the Seoul Metropolitan Area by breaking free from the disgrace of being a remote location given its link to KTX in the future.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.603-611
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• 2022

In urban areas, the impermeable area continues to increase due to urbanization, which interferes with the surface penetrating and infiltrating of rainwater, causing most rainwater runoff to the surface, deepening the distortion of water circulation. Distortion of water circulation affects not only flood disasters caused by rainfall and runoff, but also various aspects such as dry stream phenomenon, deterioration of water quality, and destruction of ecosystem balance, and the Ministry of Environment strongly recommends the use of Low Impact development (LID) techniques. In order to apply the LID technique, it is necessary to set a rainwater management target to handle the increase in outflow after the development of the target site, and the current standard sets the rainwater management target using the 10-year daily rainfall. In this study, the difference from the current standards was analyzed through statistical analysis and classification of independent rainfall ideas using inter-event time definition (IETD) in setting the target amount of rainwater management to improve water circulation. Using 30-year rainfall data from 1991 to 2020, methods such as autocorrelation coefficient (AC) analysis, variation coefficient (VC) analysis, and annual average number of rainfall event (NRE) analysis were applied, and IETD was selected according to the target rainfall period. The more samples the population had, the more IETD tended to increase. In addition, by analyzing the duration and time distribution of independent rainfall according to the IETD, a plan was proposed to calculate the standard design rainfall according to the rainwater management target amount. Therefore, it is expected that it will be possible to set an improved rainwater management target amount if sufficient samples of independent rainfall ideas are used through the selection of IETD as in this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.595-601
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• 2008

The purpose of this study is to investigate the trends and patterns of various kind of water uses in a household by metering in Korea. Water use components are classified by toilet, washbowl, bathing, laundry, kitchen, miscellaneous. Flow meters are installed in 140 household selected by sampling in all around Korea. The data are gathered by web-based data collection system from the year 2002 to 2006, considering pre-investigated data such as occupation, revenue, family members, housing types, age, floor area, water saving devices, education, miscellaneous. Reliable data are selected by upper fence method for each observed water use component and statistical characteristics are estimated for each residential type to determine liter per capita per day. Estimated domestic per capita day show an indoor water use with the range from 150 lpcd to 169 lpcd for each housing type as the order of high rise apartment, multi-house, and single house. As the order of consuming amount among water use components, it is investigated that toilet (38.5 lpcd) is the first, and the second is laundry water (30.8 lpcd), the third is kitchen (28.4 lpcd), the fourth is bathtub (24.7 lpcd), the next is washbowl (15.4 lpcd). The results are compared with water uses in U.K. and U.S. As life style has been changed into western style, pattern of water use in Korea is tend to be similar with the U.S. water use pattern. Compared with the surveying results by Bradley, on 1985. Thirty liter of total use increased with the advancement of economic level, and a little change of water use pattern can be found. Especially, toilet water take almost half part of total water use and laundry water shows lowest as 11% in surveying at the year of 1985. But, this study shows that 39 liter, 28% of toilet water, has been decreased by the spread of saving devices and campaign. It is supposed that the spread large sized laundry machine make by-hand laundry has been decreased and water use increased. Unit water amount of each end-use in household can be applied to design factor for water and wastewater facilities, and it play a role as information in establishing water demand forecasting and conservation policy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.603-614
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• 2008

End-uses of household water have been changed by a life style, housing type, weather, water rate and water supply facilities etc. and those variables can be considered as an internal and exogenous factors to estimate long-term demand forecasts. Analysis of influential factors on water consumption in households would give an explanation to cause on the change of trend and would help predicting the water demand of end-use in household. The purpose of this study is to analyze the demand trends and patterns of household water uses by metering and questionnaire such as occupation, revenue, numbers of family member, housing types, age, floor area and installation of water saving device, etc. The peak water uses were shown at Saturday among weekdays and July in a year based on the analysis results of water use pattern. A steep increase of total water volume can be found in the analysis of water demand trend according to temperature from $-14^{\circ}C$ to $0^{\circ}C$, while there are no significant variations in the phase of more than $0^{\circ}C$, with an almost stable demand. Washbowl water shows the highest and toilet water shows the lowest relation with temperature in correlation analysis results. In the results of ANOVA to find the significant difference in each unit water use by exogenous factors such as housing type, occupation, number of generation, residential area and income et al., difference was shown in bathtub water by housing type and shown in kitchen, toilet and miscellaneous water by numbers of resident. Especially, definite differences in components except washbowl and bathtub water, could be found by numbers of resident. Based on the result, average residents in a house should be carefully considered and the results can be applied as reference information, in decision making process for predicting water demand and establishing water conservation policy. It is expected that these can be used as design factors in planning stage for water and wastewater facilities.