• 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.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.469-482
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• 2022

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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.363-369
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• 2021

High-definition road maps are used as the basic infrastructure for autonomous vehicles, so the latest road information must be quickly reflected. However, the current drawing and structural editing process of high-definition road maps are manually performed. In addition, it takes the longest time to generate road lanes, which are the main construction targets. In this study, the point cloud of the road lane markings, in which color types(white, blue, and yellow) were predicted through the PointNet model pre-trained in previous studies, were used as input data. Based on the point cloud, this study proposed a methodology for automatically drawing and structural editing of the layer of road lane markings. To verify the usability of the 3D vector data constructed through the proposed methodology, the accuracy was analyzed according to the quality inspection criteria of high-definition road maps. In the positional accuracy test of the vector data, the RMSE (Root Mean Square Error) for horizontal and vertical errors were within 0.1m to verify suitability. In the structural editing accuracy test of the vector data, the structural editing accuracy of the road lane markings type and kind were 88.235%, respectively, and the usability was verified. Therefore, it was found that the methodology proposed in this study can efficiently construct vector data of road lanes for high-definition road maps.

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.55-70
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• 2021

In this study, in the field of remote sensing, where the scope of application is rapidly expanding to fields such as land monitoring, disaster prediction, facility safety inspection, and maintenance of cultural properties, monitoring of rural space and surrounding environment using UAV is utilized. It was carried out to verify the possibility, and the following main results were derived. First, the aerial image taken with an unmanned aerial vehicle had a much higher image size and spatial resolution than the aerial image provided by the National Geographic Information Service. It was suitable for analysis due to its high accuracy. Second, the more the number of photographed photos and the more complex the terrain features, the more the point cloud included in the aerial image taken with the UAV was extracted. As the amount of point cloud increases, accurate 3D mapping is possible, For accurate 3D mapping, it is judged that a point cloud acquisition method for difficult-to-photograph parts in the air is required. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. Fourth, the digital elevation model(DEM) produced with aerial image taken with an UAV can visually express the altitude and shape of the topography of the study site, so it can be used as data to predict the effects of topographical changes due to changes in rural space. Therefore, it is possible to utilize various results using the data included in the aerial image taken by the UAV. In this study, the superiority of images acquired by UAV was verified by comparison with existing images, and the effect of 3D mapping on rural space monitoring was visually analyzed. If various types of spatial data such as GIS analysis and topographic map production are collected and utilized using data that can be acquired by unmanned aerial vehicles, it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.5-18
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• 2023

As the development of drones and sensors accelerates, new services and values are created by fusing data acquired from various sensors mounted on drone. However, the construction of spatial information through data fusion is mainly constructed depending on the image, and the quality of data is determined according to the specification and performance of the hardware. In addition, it is difficult to utilize it in the actual field because expensive equipment is required to construct spatial information of high-quality. In this study, super-resolution was performed by applying deep learning to low-resolution images acquired through RGB and THM cameras mounted on a drone, and quantitative evaluation and feature point extraction were performed on the generated high-resolution images. As a result of the experiment, the high-resolution image generated by super-resolution was maintained the characteristics of the original image, and as the resolution was improved, more features could be extracted compared to the original image. Therefore, when generating a high-resolution image by applying a low-resolution image to an super-resolution deep learning model, it is judged to be a new method to construct spatial information of high-quality without being restricted by hardware.

• Journal of the Economic Geographical Society of Korea
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• v.8 no.1
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• pp.91-105
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• 2005

The assessment (or the evaluation) of spatial disparity is the main concern for the study of spatial disparities or spatial inequalities. In order to evaluate the spatial disparity, the regional differences have to be counted quantitatively. Several measurements have been introduced for evaluating the development potentials of each region. Most of them are the composite indices of the socio-economic variables rather than the real potentials of the region. This study attempts to investigate the spatial disparity in Korea. For the purpose, the levels of opportunity potentials of the cities have been calculated by the Potential Model redefined by Lee(1995). The opportunity potentials have been calculated for the educational, cultural, medical service, environmental sectors, income, and consumption sectors, and the spatial patterns of various opportunity potentials have been analyzed. The spatial patterns of opportunity potentials show the severe concentration on the Metropolitan Seoul area through all sectors. The next level concentration appears at the other end of the Keuyng-Bu axis. And the cities relatively high opportunity potential values are distributed along the Keuyng-Bu axis. Remain parts of the country show quietly low opportunity potential values. In particular, the southern-west and the northern-east parts show relatively very low values. This pattern appears for all sectors except for the opportunity potential of the environmental sector. It means that the spatial disparity in Korea have been promoted and enhanced by the national development policies concentrated the investment on the large cities along the Keuyng-Bu axis during the last 40 years.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.4
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• pp.224-236
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• 2002

A long-term growth simulation was performed at 496 land units in the western coastal plains (WCP) of North Korea to test the potential adaptability of each land unit for growing South Korean rice cultivars. The land units for rice cultivation (CZU), each of them represented by a geographically referenced 5 by 5 km grid tell, were identified by analyzing satellite remote sensing data. Surfaces of monthly climatic normals for daily maximum and minimum temperature, precipitation number of rain days and solar radiation were generated at a 1 by 1 km interval by spatial statistical methods using observed data at 51 synoptic weather stations in North and South Korea during 1981-2000. Grid cells felling within a same CZU and, at the same time, corresponding to the satellite data- identified rice growing pixels were extracted and aggregated to make a spatially explicit climatic normals relevant to the rice growing area of the CZU. Daily weather dataset for 30 years was randomly generated from the monthly climatic normals of each CZU. Growth and development parameters of CERES-rice model suitable for 11 major South Korean cultivars were derived from long-term field observations. Eight treatments comprised of 2 transplanting dates $\times$ 2 cropping systems $\times$ 2 irrigation methods were assigned to each cultivar. Each treatment was simulated with the randomly generated 30 years' daily weather data (from planting to physiological maturity) for 496 land units in WCP to simulate the growth and yield responses to the interannual climate variation. The same model was run with the input data from the 3 major crop experiment stations in South Korea to obtain a 30 year normal performance of each cultivar, which was used as a "reference" for comparison. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to evaluate the suitability of each land unit for growing a specific South Korean cultivar. The results may be utilized as decision aids for agrotechnology transfer to North Korea, for example, germplasm evaluation, resource allocation and crop calendar preparation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.2
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• pp.47-61
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• 2000

Agroclimatic zoning was done for paddy rice culture in North Korea based on a simulation experiment. Daily weather data for the experiment were generated by 3 steps consisting of spatial interpolation based on topoclimatological relationships, zonal summarization of grid cell values, and conversion of monthly climate data to daily weather data. Regression models for monthly climatological temperature estimation were derived from a statistical procedure using monthly averages of 51 standard weather stations in South and North Korea (1981-1994) and their spatial variables such as latitude, altitude, distance from the coast, sloping angle, and aspect-dependent field of view (openness). Selected models (0.4 to 1.6$^{\circ}C$ RMSE) were applied to the generation of monthly temperature surface over the entire North Korean territory on 1 km$\times$l km grid spacing. Monthly precipitation data were prepared by a procedure described in Yun (2000). Solar radiation data for 27 North Korean stations were reproduced by applying a relationship found in South Korea ([Solar Radiation, MJ m$^{-2}$ day$^{-1}$ ] =0.344 + 0.4756 [Extraterrestrial Solar Irradiance) + 0.0299 [Openness toward south, 0 - 255) - 1.307 [Cloud amount, 0 - 10) - 0.01 [Relative humidity, %), $r^2$=0.92, RMSE = 0.95 ). Monthly solar irradiance data of 27 points calculated from the reproduced data set were converted to 1 km$\times$1 km grid data by inverse distance weighted interpolation. The grid cell values of monthly temperature, solar radiation, and precipitation were summed up to represent corresponding county, which will serve as a land unit for the growth simulation. Finally, we randomly generated daily maximum and minimum temperature, solar irradiance and precipitation data for 30 years from the monthly climatic data for each county based on a statistical method suggested by Pickering et a1. (1994). CERES-rice, a rice growth simulation model, was tuned to accommodate agronomic characteristics of major North Korean cultivars based on observed phenological and yield data at two sites in South Korea during 1995~1998. Daily weather data were fed into the model to simulate the crop status at 183 counties in North Korea for 30 years. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to score the suitability of the county for paddy rice culture.