Journal of the Korean Institute of Traditional Landscape Architecture
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v.29
no.1
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pp.157-165
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2011
This study is to be used as a fundamental material of rural amenity resources researches, such as excavating, establishing and modifying national agricultural landscape resources, so as to efficiently manage them. It is carried out with targeting traditional Darangyi-Rice terrace which has design factors of agricultural landscape resources. We have set up the standard range with practicable similar standard(Marginal Farmland and Less Favored Areas and etc), those of Japan, and the results of analyzing the characteristics of Darangyi-Rice terrace already known. As a result of the field investigation, it has been revealed that a great deal of Darangyi-Rice terrace are being used for not corresponding purposes, or damaged and disappeared. For preserving and well-managing Darangyi-Rice terrace as a rural landscape resource which has rural design factors, it should be advanced detailed and accurate studies on present conditions and changes of Darangyi-Rice terrace, with researches on significances, values, utilities and economical efficiency of Darangyi-Rice terrace by regions. In addition, we utilized various spatial imagery data in the researching process. Consequently, it is concluded that if high resolution imagery data is used, it can establish rather minute and accurate large-scale DB, and monitor elaborate changes as well. It is therefore thought that its application can be higher as actualizing DB hereafter.
Journal of the Korean Institute of Traditional Landscape Architecture
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v.29
no.3
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pp.12-21
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2011
We investigated the location and surveillance system of fortress using inter-visibility analysis between fortress and the capital of the Silla Dynasty. The digital terrain model(DTM) was generated with $10{\times}10m$ grid in Arcview 3.2. Then three fortresses lines(Myeonghwal-sanseong, Namsan-shinseong, Seohyeong-sanseong) were superimposed on the DTM. 4 results of this study were drew out from the cumulative visibility analysis. First, the most of fortress lines which showed the high visible frequency from the Sila-Capital(538 viewpoints) have a good aspect toward the capital. It means that 3 fortresses secured the visibility to the capital. Second, the cumulative visibility analysis from 3 fortresses generated evenly distributed visible frequency across the inside of fortress. It shows that the inner area of fortress is more advantageous to command during the war. On the contrary, a number of invisible(vulnerable) regions which is scattered on the outside were supplemented by adjacent fortress. Third, the north area of the Sila-captial showed the highest visible frequency generated by sum up the visibility from 3 fortresses. The northern captial is placed within 4km distance easy to support at the Myeonghwal and Seohyeong-sanseong. We proved that the Sila-capital had organized a solid surveillance system by 3 fortresses. Fourth, we could infer the practical process of fortress layout from comparing a cumulative visibility map. For the secure of visibility and defense systems, the fortress line would form a rising shape to the peak. This practical location theory can replace the vague common location theory that the fortress would constructed on two thirds of mountain height. It will be an empirical method in the ancient remains research.
Jang, Yeong Jae;Jo, Hyeon Jeong;Oh, Jae Hong;Lee, Chang No
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.39
no.2
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pp.93-101
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2021
Recently, with the urban redevelopment and the spread of the planned cities, there is increasing interest in the wind environment, which is related not only to design of buildings and landscaping but also to the comfortability of pedestrians. Numerical analysis for wind environment prediction is underway in many fields, such as dense areas of high-rise building or composition of the apartment complexes, a precisive 3D building model is essentially required in this process. Many studies conducted for wind environment analysis have typically used the method of creating a 3D model by utilizing the building layer included in the GIS (Geographic Information System) data. These data can easily and quickly observe the flow of atmosphere in a wide urban environment, but cannot be suitable for observing precisive flow of atmosphere, and in particular, the effect of a complicated structure of a single building on the flow of atmosphere cannot be calculated. Recently, drone photogrammetry has shown the advantage of being able to automatically perform building modeling based on a large number of images. In this study, we applied photogrammetry technology using a drone to evaluate the flow of atmosphere around two buildings located close to each other. Two 3D models were made into an automatic modeling technique and manual modeling technique. Auto-modeling technique is using an automatically generates a point cloud through photogrammetry and generating models through interpolation, and manual-modeling technique is a manually operated technique that individually generates 3D models based on point clouds. And then the flow of atmosphere for the two models was compared and analyzed. As a result, the wind environment of the two models showed a clear difference, and the model created by auto-modeling showed faster flow of atmosphere than the model created by manual modeling. Also in the case of the 3D mesh generated by auto-modeling showed the limitation of not proceeding an accurate analysis because the precise 3D shape was not reproduced in the closed area such as the porch of the building or the bridge between buildings.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.39
no.3
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pp.133-139
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2021
Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.
Journal of the Korean Association of Geographic Information Studies
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v.23
no.4
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pp.140-155
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2020
This study was conducted to identify the location characteristics of infected farms in the areas where livestock diseases were clustered(southern Gyeonggi-do and Chungcheong-do), analyze the probability of disease occurrence in poultry farms, find out the areas corresponding to the conditions, and use them as the basis for prevention of livestock diseases, selection of discriminatory prevention zones, and establishment of prevention strategies and as the basic data for complementary measures. The increase of one poultry farm within a radius of 3-kilometers increases the risk of HPAI infection by 10.9% compared to the previous situation. The increase of 1m in distance from major roads with two lanes or more reduces the probability of HPAI infection by 0.001% compared to the previous situation. If the distance of the poultry farm located with 15 kilometers from a major migratory bird habitat increases by 15 to 30 kilometers, the chance of infection with HPAI is reduced by 46.0%. And if the distance of the same poultry farm increase by more than 30 kilometers, the chances of HPAI infection are reduced by 88.5%. Based on the results of logistic regression, the predicted probability was generated and the actual area of the location condition with 'more than 15 poultry farms within 3km a radius of, within 1km distance from major roads, and within 30km distance from major migratory birds habitat was determined and the infection rate was measured. It is expected that the results of this study will be used as basic data for preparing the data and supplementary measures when the quarantine authorities establish discriminatory quarantine areas and prevention strategies, such as preventive measures for the target areas and farms, or control of vehicles, by identifying the areas where livestock diseases are likely to occur in the region.
The purpose of this study is to analyze and diagnose the actual state of extinction risk in rural villages by analyzing time series population characteristics and extinction risk index of rural villages(Haengjeong-ri). As a research method, a time series analysis was performed on the 'population over 65' and the 'female population aged 20 to 39' related to the local extinction index. In addition, the disappearance of Haengjeong-ri village was analyzed using the existing local extinction index. For the study, Haengjeong-ri village-level GIS spatial data was constructed, and population attribute data in 2010, 2015, and 2020 were constructed. In order to derive implications, the change of the 'high risk of extinction 'village in the 2020 local extinction index, the distribution of the population of 'high risk of extinction' villages by three years, the population analysis of 'high risk of extinction' villages continuously from 2010 to 2020, and 'high risk of extinction' An analysis of the increase and decrease of the population of the village and the change of the local extinction index of Haengjeong-ri, where the city, county, and towns are located were analyzed. As a result of the analysis of this study, it was found that the number of villages with an aging of more than 50% increased by 2 to 3 times over 10 years. As a result of the analysis of the local extinction index, in 2010, the southwestern and central regions of South Chungcheongnam-do were high-risk extinction areas, but in 2020, all cities except Cheonan and Asan were converted to high risk extinction areas. Research has shown that Chungnam is facing a serious aging and village extinction crisis, and since the disappearance of villages gradually spreads, an initial response policy is needed. This result will be the same not only in Chungcheongnam-do but also in other rural villages. Therefore, in the case of rural villages, it is necessary to analyze and diagnose the Haengjeong-ri village unit, not the Eup-Myeon unit, and a response policy through diagnosis must be prepared urgently.
To investigate the characteristics of detailed flows in a building-congested district, 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. For realistic numerical simulations, we used the meteorological variables such as wind speeds and directions and potential temperatures predicted by LDAPS as the initial and boundary conditions of the CFD model. We trilinearly interpolated the horizontal wind components of LDAPS to provide the initial and boudnary wind velocities to the CFD model. The trilinearly interpolated potential temperatures of LDAPS is converted to temperatures at each grid point of the CFD model. We linearly interpolated the horizontal wind components of LDAPS to provide the initial and boundary wind velocities to the CFD model. The linearly interpolated potential temperatures of LDAPS are converted to temperatures at each grid point of the CFD model. We validated the simulated wind speeds and directions against those measured at the PKNU-SONIC station. The LDAPS-CFD model reproduced similar wind directions and wind speeds measured at the PKNU-SONIC station. At 07 LST on 22 June 2020, the inflow was east-north-easterly. Flow distortion by buildings resulted in the east-south-easterly at the PKNU-SONIC station, which was the similar wind direction to the measured one. At 19 LST when the inflow was southeasterly, the LDAPS-CFD model simulated southeasterly (similar to the measured wind direction) at the PKNU-SONIC station.
There is growing significance in securing urban parks and enhancing their accessibility due to irrational residential developments and apartment construction. Accordingly, Daejeon Metropolitan City has carried out urban park management projects to improve the quality of parks and create new parks. Daejeon Metropolitan City generates and manages park data for the purpose of management by the administrative district. However, these datasets take different forms in each administrative district. This study integrates the park data in Daejeon, generated by administrative districts, into the same format and generates geographic information data with the area information of each park for analysis. Analysis results show that urban parks are severely imbalanced across administrative districts, requiring new policy measures. In addition, by normalizing the park analysis results and, then, creating their rankings, this study compares them with the actual park information in detail to confirm the soundness of the dataset. The analysis results provide implications to improve the management of urban parks. This study proposes integrated datasets and the continued management of them in each administrative district by including essential data that can feature the objective information of the parks along with park evaluation indicators based on previous studies.
The purpose of this study is to analyze regional variation factors of hypertension treatment rate in COVID-19 based on the analysis results based on ecological methodology. To this end, data suitable for ecological analysis were collected from the Korea Centers for Disease Control and Prevention's regional health statistics, local government COVID-19 confirmed cases, National Health Insurance Corporation, Health Insurance Review and Assessment Service's welfare statistics, and Korea Transport Institute's traffic access index. Descriptive statistics and correlation analysis were conducted using SPSS Statistics 23 for regional variation and related factors in hypertension treatment rate, and geographical weighted regression analysis was conducted using Arc GIS for regional variation factors. As a result of the study, the overall explanatory power of the calculated geo-weighted regression model was 27.6%, distributed from 23.1% to 33.4% by region. As factors affecting the treatment rate of hypertension, the higher the rate of basic living security medical benefits, diabetes treatment rate, and health institutions per 100,000 population, the higher the rate of hypertension treatment, the lower the number of COVID-19 confirmed patients, the lower the rate of physical activity, and the alcohol consumption. Percentage of alcohol consumption decreased due to COVID-19 pandemic. It was analyzed that the lower the ratio, the higher the treatment rate for hypertension. Based on these results, the analysis of regional variables in the treatment rate of hypertension in COVID-19 can be expected to be effective in managing the treatment rate of hypertension, and furthermore, it is expected to be used to establish community-centered health promotion policies.
Korean Journal of Agricultural and Forest Meteorology
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v.23
no.4
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pp.283-294
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2021
Solar radiation is an important meteorological factor in the agricultural sector. The ground exposed to sunlight is highly influenced by the surrounding terrains especially in South Korea where the topology is complex. The solar radiation on an inclined surface is estimated using a solar irradiance correction factor for the slope of the terrain along with the solar radiation on a horizontal surface. However, such an estimation method assumes that there is no barrier in surroundings, which blocks sunlight from the sky. This would result in errors in estimation of solar radiation because the effect of shading caused by the surrounding terrain has not been taken into account sufficiently. In this study, the shading effect was simulated to obtain the brightness value (BV), which was used as a correction factor. The shaded relief images, which were generated using a 30m-resolution digital elevation model (DEM), were used to derive the BVs. These images were also prepared using the position of the sun and the relief of the terrain as inputs. The gridded data where the variation of direct solar radiation was quantified as brightness were obtained. The value of cells in the gridded data ranged from 0 (the darkest value) to 255 (the brightest value). The BV analysis was performed using meteorological observation data at 22 stations installed in study area. The observed insolation was compared with the BV of each point under clear and cloudless condition. It was found that brightness values were significantly correlated with the solar radiation, which confirmed that shading due to terrain could explain the variation in direct solar radiation. Further studies are needed to accurately estimate detailed solar radiation using shaded relief images and brightness values.
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