Journal of the Korean Society of Environmental Restoration Technology
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v.1
no.1
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pp.3-17
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1998
The purposes of this study is to investigate the possibility of planting trees at space land in the riverside. The space land is for the green space. Calculating the plantable space in the representation section and the flood flowing stability of the existing banks based on the hydrological and meteorological data of the Kap-Chon riverbasin located in Tae-jon, the following results are drawn. (1) The flood discharges in each flow section are $698.7m^3/s$ in section 1, $654.6m^3/s$ in section 2, and $1353.3m^3/s$ in section 3 during 100 years recurrence interval. Because the designed-flood discharges in those sections are $1719.9m^3/s$, $2119.7m^3/s$, and $1512.8m^3/s$ respectively, safety for flood flowing is sufficient in existing banks. (2) The possible clearance for planting trees is 1.80m in section 1, 3.90m in section 2, and 0.01m in section 3. Planting clearance is enough in section 1 and 2. However, planting should be planned after estimating a rise-height due to the bridge piers, because many piers under riverine-highway are now on the construction in section 2. The section 3 does not have sufficient clearance for planting trees, but the planting is possible after getting enough flow area with slope by cutting the terrace land on the river artificially heightened. (3) In case of planting a tree 70cm diameter in $1m^2$ in section 1, the water level increases by 0.60m. Planting a tree in a $48m^2$ area increases the water level by 0.90m. Considering that plantable clearance is 1.8m in section 1, it is sufficient to flow safely. But if the trees are planted so compactly from the upper stream, expected heavy resistance is expected due to caught materials on the trees. So, trees have to be planted widely in upper streams but compactedly in lower streams. (4) The river width without changing, Kap-Chon's flow channel can be snaked in accordance with the nature law the wide terrace land in the riverside. Decreased flow area due to planting trees will be compensated by the inclination of terrace land. And, it is theoretically proved that the flood discharge is safe even though the terrace land on the river is parked similar to the nature. Planting trees in the terrace land of the Kap-chon river to the extent that flood flowing is not adversely affected, we can get the enjoyable park to citizens not spending expensive cost. It also contributes to the recovery of ecosystem, which gives the natural beauty of river and shade to citizens and becomes good natural-educational places for children.
Journal of the Korean Institute of Traditional Landscape Architecture
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v.31
no.4
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pp.1-21
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2013
This study has researched the characteristics and elements of the chuibyong, a sort of trellis in the Joseon Dynasty through the old pictorial data. The results were as follows; First, as a result of the analysis for the 25 pictorial data in the Joseon Dynasty, the chuibyongs have usually functioned as screening the facility to protect the private life and dividing the spaces of the site, but it was internally regarded as the props which symbolized the dignity and elegance of high class. Especially, not only the faunas such as crane and deer, and the floras such as Pinus densiflora, Musa basjoo, bamboo species and Paulownia coreana, but also various garden elements including oddly shaped stone, pond and pavilion were shown in the surrounding area of the chuibyong, and they were considered as a series of combination that was needed in the ideal garden for the literati. Secondly, the chuibyong was recognized as the ideological object which was typical of the literati culture in the story derived from an ancient event of China. Such image has been reflected intactly in the garden culture, and the chuibyong has been used(considered) as the important scenery of the season to imitate and reenact the Chinese Classical Garden in the narrative painting. Thirdly, in terms of the shape and function, the chuibyong in the paintings in the Joseon Dynasty basically had the function of the shielding and spatial division. Fourthly, the height of the chuibyung was similar to the one of fence which exceeds the person's height or Youngbyek(影壁) which is installed in the front and the rear of the main gate in China, and the various shape's chuibyung was properly set up in many spaces. Lastly, the making of the chuibyong in Joseon Dynasty was related to the trend of the writer's culture which was popular nationally in Ming dynasty rather than the particular functions or the location conditions. Especially, the symbol expression of the chuibyong showed on 'Elegant Gathering in the Western Garden' which was brought from China was recreated in the mansion of the upper class in Hanyang city as the center, and the primary mode for the expression of the wealth and writer's spirit through the chuibyong was transformed into the high-quality's garden element which could be created in the royal palace or the mansion of the upper class. Also, the use of the chuibyung was changed by spreading into the residential style for common people after the mid-nineteenth century, and it means that the chuibyung was developed into Korean styles.
Journal of the Korean Association of Geographic Information Studies
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v.22
no.2
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pp.152-171
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2019
In this study, we analyzed the characteristics of the cold air generated in Hannamgeumbuk and Geumbuk-Jeongmaek and proposed their management strategies. We also suggested management strategies after analyzing detailed cold airflows for Cheongju located Hannamgeumbuk-Jeongmaek and we compared the degree of nighttime temperature reduction of the Jeongmaek by using data obtained from observatories located on Cheongju. We used KALM(Kaltluftabflussmodell), a cold air simulation model developed in Germanay and identified both cold airflows and altitude of cold air layers generated during 360minutes at night. As a result, the cold airflow generated in the Jeongmaek became strong and the cold air was appeared clearly in the western part of the Hannamgeumbuk-Jeongamek and in the northern part of the Geumbuk-Jeongmaek. The average velocity of cold airflow was recorded at 0.45m/s, and the maximum speed of cold airflow was recorded at 2.70m/s. The average height of the cold air layer was 104.27m/s and the maximum thickness was 255.0m. The average velocity of cold airflows in Cheongju was 0.51m/s and the average height of cold air layer was 48.87m high. The highest degree of nighttime temperature reduction appeared in the Cheongnamdae observatory($-3.8^{\circ}C$), where the altitude of the cold air layer is high. The results showed that cooling effect of Jeongmaek actually affected the temperature reduction during nighttime. Based on the results, we designated the main mountain area of the Jeongmaek with active cold air generation as "cold air conservation areas" and proposed the current forest and topography conservation. We also proposed to designate areas that facilitate the cold airflows as "cold air management areas" and to complement the function of Jeongmaek. This study could support the establishment of systematic management plans of the Jeongmaek. In addition, it is expected that the results can be applied as basic data for ventilation paths of Cheongju.
In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.
Kim, Hee-Young;Park, Kyung-Ae;Kwak, Byeong-Dae;Joo, Hui-Tae;Lee, Joon-Soo
Journal of the Korean earth science society
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v.43
no.5
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pp.604-617
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2022
Sea surface temperature (SST) is a key variable that can be used to understand ocean-atmosphere phenomena and predict climate change. Satellite microwave remote sensing enables the measurement of SST despite the presence of clouds and precipitation in the sensor path. Therefore, considering the high utilization of microwave SST, it is necessary to continuously verify its accuracy and analyze its error characteristics. In this study, the validation of the microwave global precision measurement (GPM)/GPM microwave imager (GMI) SST around the Northwest Pacific and Korean Peninsula was conducted using surface drifter temperature data for approximately eight years from March 2014 to December 2021. The GMI SST showed a bias of 0.09K and an average root mean square error of 0.97K compared to the actual SST, which was slightly higher than that observed in previous studies. In addition, the error characteristics of the GMI SST were related to environmental factors, such as latitude, distance from the coast, sea wind, and water vapor volume. Errors tended to increase in areas close to coastal areas within 300 km of land and in high-latitude areas. In addition, relatively high errors were found in the range of weak wind speeds (<6 m s-1) during the day and strong wind speeds (>10 m s-1) at night. Atmospheric water vapor contributed to high SST differences in very low ranges of <30 mm and in very high ranges of >60 mm. These errors are consistent with those observed in previous studies, in which GMI data were less accurate at low SST and were estimated to be due to differences in land and ocean radiation, wind-induced changes in sea surface roughness, and absorption of water vapor into the microwave atmosphere. These results suggest that the characteristics of the GMI SST differences should be clarified for more extensive use of microwave satellite SST calculations in the seas around the Korean Peninsula, including a part of the Northwest Pacific.
Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.
Damages by heavy snow does not occur very often, but when it does, it causes damage to a wide area. To mitigate snow damage, it is necessary to know, in advance, the depth of snow that causes damage in each region. However, snow depths are measured at observatory locations, and it is difficult to understand the spatial distribution of snow depth that causes damage in a region. To understand the spatial distribution of snow depth, the point measurements are interpolated. However, estimating spatial distribution of snow depth is not easy when the number of measured snow depth is small and topographical characteristics such as altitude are not similar. To overcome this limit, satellite images such as Synthetic Aperture Radar (SAR) can be analyzed using Differential Interferometric SAR (DInSAR) method. DInSAR uses two different SAR images measured at two different times, and is generally used to track minor changes in topography. In this study, the spatial distribution of snow depth was estimated by DInSAR analysis using dual polarimetric IW mode C-band SAR data of Sentinel-1B satellite operated by the European Space Agency (ESA). In addition, snow depth was estimated using geostationary satellite Chollian-2 (GK-2A) to compare with the snow depth from DInSAR method. As a result, the accuracy of snow cover estimation in terms with grids was about 0.92% for DInSAR and about 0.71% for GK-2A, indicating high applicability of DInSAR method. Although there were cases of overestimation of the snow depth, sufficient information was provided for estimating the spatial distribution of the snow depth. And this will be helpful in understanding regional damage-causing snow depth.
In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.
This study views the aged inequalities according to the inequality hypothesis of the life course perspective in OECD 10 countries. Focusing on educational level which is early social status and welfare state regime which is social structure factors of inequality, this study analyzes income inequality for the aged who have transformed into old age period from non-aged period. The analysis is based on the data SHARE of Europe and HRS of USA. The main results of this study are summarized in four points. First, the income inequality is quite high by welfare system and the educational level. Second, the income inequality is somewhat reduced in case the people move from the period of non-aged to the period of aged. However, gini coefficient is still high(0.475). Considering welfare state regimes, although the income inequality is high in conservative regime of non-aged period, this would be higher in aged period. This result supports cumulative advantages/disadvantages hypothesis. The liberal regime remains high income inequality which supports the theoretical argument of status maintenance. Social democratic regime provides evidence to offer some support for the status leveling hypothesis. In there, income inequality is lower in aged period even though income inequality of non-aged period is low. Third, the cumulative advantages/disadvantages of disposable income according to educational level are strengthened and heterogeneity is grown in case people transition from the late period of non-aged to aged period. But public pension has been more equally distributed than gross income. Fourth, seeing welfare state regimes, public pension of aged-period is more inequally distributed than that of non-aged period in liberal and conservative regime. Specially in conservative regime, inequality of gross income is very high and public pension is also inequally distribute So this might show that the social security system strengthens the cumulative advantages/disadvantages. However, in the social democratic regime, public pension is more equally distributed than gross income and it could be much more equally distributed in aged period, which can support the status leveling hypothesis.
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.
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