• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.65-77
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• 2018

It is very important to understand the factors affecting the occurrence of vacant houses in research on them. The purpose of this study is to analyze the factors affecting the rural vacancy occurrence. This study set 121 research areas and selected eight independent variables (Aged house rate, housing transaction rate, house diffusion ratio, local extinction index, net migration rate, regional aging index, the ratio of the number of employees to population and financial independence rate) and one dependent variable (vacant house rate). As a result of the study, first, both Model 1 for the entire general agricultural fishing village area and Model 2 for the county (gun) area were statistically significant, there was no problem with the independence of residual. Second, local extinction index and aged house rate had a statistically significant positive (+) relationship in both Model 1 and Model 2. Third, diffusion ratio of house had a statistically significant positive (+) relationship only in Model 1, and housing transactions rate had a statistically significant negative (-) relationship in Model 2. The implications of the study were drawn as follows: First, the increase in the house diffusion ratio without growth in households and population suggests the increase of the probability of the vacancy occurrence in the area, and the higher the aged house rate, the higher the probability of the vacancy occurrence. Second, for the revitalization of housing transactions, it is necessary to have an investment inflow in the area for mid- to long-term development. Third, local extinction index has a significant relationship with vacant house rate, it is necessary to introduce a local revitalization policy from a long-term perspective for the permanence of the area.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.123-144
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• 2019

The purpose of this study is to grasp factors the increasing population growth rate of the region through the regional and housing market characteristics. This paper has used multiple regression as the dependent variable (average of the population growth rate of 85cities during the last five years) and the independent variables analyzed the regional and housing market characteristics on the average. The results of the analysis, The regional and housing market variables that have had a significant impact on the regional population growth rate over the last five years are birth rate, employment rate, production available population growth rate, apartment rate, resale rights rate, and apartment turnover rate and the number of businesses per thousand and has decreased. In other words, The regions where the population increased by region for the last five years were the ones with the transfer of public institutions (innovation cities) and land development among the Seoul metropolitan area and non-Seoul metropolitan area excluding Seoul and metropolitan cities. The results of this study is intentional to suggest Policy point of view for the balanced regional development presented at the government level for other the metropolitan area, such as the small and medium cities that are undergoing population decline.

• Informatization Policy
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• v.26 no.1
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• pp.62-82
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• 2019

This study attempts to make an empirical analysis on how mobile devices affect users in building their social relationship and if their influences are negative or positive. The purpose of this research is to explain the results by considering all the possibilities and exploring everyday lives of using mobile devices. We used the survey data from the "Research on Mobile Environment Awareness" conducted by Gyeonggi Research Institute(GRI). The main question was about the use of mobile devices and social network services (SNS) and users' opinions on using the devices. All of the 31 municipalities in Gyeonggi Province were included as a spatial range, and the final validity sample was 1,004 residents. The extent of the relationship with people is selected as a dependent variable through the multinomial logistic model and the decision tree model. As a result of the multinomial logistic analysis on the questionnaire, the characteristics of the respondents with some changes in the scope of the human relationship were found to have a significant (+) effect on conversation with family, SNS usage, residence in the rural area but not urban area, and device usage for obtaining news. The largest variable affecting the extent of relationship was the SNS usage. As the amount of SNS usage increases, the extent of the relationship also changes a lot.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1367-1377
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• 2020

The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.991-1005
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• 2022

Satellite imaging is an effective supplementary data source for detecting and verifying nuclear activity. It is also highly beneficial in regions with limited access and information, such as nuclear installations. Time series analysis, in particular, can identify the process of preparing for the conduction of a nuclear experiment, such as relocating equipment or changing facilities. Differences in the semantic segmentation findings of time series photos were employed in this work to detect changes in meaningful items connected to nuclear activity. Building, road, and small object datasets made of KOMPSAT 3/3A photos given by AIHub were used to train deep learning models such as U-Net, PSPNet, and Attention U-Net. To pick relevant models for targets, many model parameters were adjusted. The final change detection was carried out by including object information into the first change detection, which was obtained as the difference in semantic segmentation findings. The experiment findings demonstrated that the suggested approach could effectively identify altered pixels. Although the suggested approach is dependent on the accuracy of semantic segmentation findings, it is envisaged that as the dataset for the region of interest grows in the future, so will the relevant scope of the proposed method.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.511-521
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• 2022

Cloud detection and removal from satellite images is an essential process for topographic observation and analysis. Threshold-based cloud detection techniques show stable performance because they detect using the physical characteristics of clouds, but they have the disadvantage of requiring all channels' images and long computational time. Cloud detection techniques using deep learning, which have been studied recently, show short computational time and excellent performance even using only four or less channel (RGB, NIR) images. In this paper, we confirm the performance dependence of the deep learning network according to the heterogeneous learning dataset with different resolutions. The DeepLabV3+ network was improved so that channel features of cloud detection were extracted and learned with two published heterogeneous datasets and mixed data respectively. As a result of the experiment, clouds' Jaccard index was low in a network that learned with different kind of images from test images. However, clouds' Jaccard index was high in a network learned with mixed data that added some of the same kind of test data. Clouds are not structured in a shape, so reflecting channel features in learning is more effective in cloud detection than spatial features. It is necessary to learn channel features of each satellite sensors for cloud detection. Therefore, cloud detection of heterogeneous sensors with different resolutions is very dependent on the learning dataset.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1053-1064
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• 2022

The Thiessen method, which is the current area average precipitation method, has serious structural limitations in accurately calculating the average precipitation in the watershed. In addition to the observation accuracy of the precipitation meter, errors may occur in the area average precipitation calculation depending on the arrangement of the precipitation meter and the direction of the heavy rain. When the watershed is small and the station density is sparse, in both simulation and observation history, the Thiessen method showed a peculiar tendency that the average precipitation in the watershed continues to increase and decrease rapidly for 10 minutes before and after the peak. And the average precipitation in the Thiessen basin was different from the rainfall radar at the peak time. In the case where the watershed is small but the station density is relatively high, overall, the Thiessen method did not show a trend of sawtooth-shaped over-peak, and the time-dependent fluctuations were similar. However, there was a continuous time lag of about 10 minutes between the rainfall radar observations and the ground precipitation meter observations and the average precipitation in the basin. As a result of examining the ground correction effect of the rainfall radar watershed average precipitation, the correlation between the area average precipitation after correction is rather low compared to the area average precipitation before correction, indicating that the correction effect of the current rainfall radar ground correction algorithm is not high.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.231-240
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• 2022

This study empirically analyzed the effect of complex commercial facilities on the price of nearby apartments in a Hedonic price model. The spatial range of this study was the walking area of H Department Store located in Pangyo among the second new towns suburb of Seoul, and the time range was 2020. The dependent variable was the real transaction price of the apartment, and independent variable were the characteristics of the housing, the characteristics of the complex, and the characteristics of the region. As a result of the analysis, the area of exclusive use space, the transaction floor, and the highway accessibility had a positive effect on the price of the apartment, and the elapsed year had a negative effect on the price of the apartment. However, the size of the apartment had little effect on apartment prices, and the distance from the complex commercial facilities was shown to be related to apartment prices, indicating that apartment prices declined as it moved away from the complex commercial facilities. Therefore, this is much more influential than the influence of distance from subway stations on apartment price. This confirms that the effect factors of apartment prices and the size of their influence appear differently in the new town area and the existing metropolitan area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.437-444
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• 2010

Soil moisture has been recognized as the essential parameter when understanding the complicated relationship between land surface and atmosphere in water and energy recycling system. It has been generally known that it is related with the temperature, wind, evaporation dependent on soil properties, transpiration due to vegetations and other constituents. There is, however, little research concerned about the relationship between soil moisture and these constitutes, thus it is needed to investigate it in detail. We estimated the soil moisture and then compared with field data using the hydrometerological data such as atmospheric temperature, specific humidity, and wind obtained from the Flux tower in Selmacheon, Korea. In the winter season, subterranean temperature showed highly positive correlation with soil moisture while it was negatively correlated from the spring to the fall. Estimation of seasonal soil moisture was compared with field measurements with the correlation of determination, R=0.82, 0.81, 0.82, and 0.96 for spring, summer, fall, and winter, respectively. Comprehensive relationship from this study can supply useful information about the downscaling of soil moisture with relatively large spatial resolutions, and will help to deepen the understanding of the water and energy recycling on the earth's surface.

• Journal of Korea Water Resources Association
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• v.57 no.4
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• pp.301-310
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• 2024

The spatial and temporal non-uniform distribution of precipitation makes water management difficult. Due to climate change, nonuniform distribution of precipitation is worsening, and droughts and floods are occurring frequently. Additionally, the intensity of droughts and floods is intensifying, making existing water management systems difficult. From June 2022 to June 2023, most of the water storage rates of major dams in the Yeongsan river and Seomjin river basin were below 30%. In the case of Juam dam, which is the most dependent on water use in the basin, the water storage rate fell to 20.3%, the lowest ever. Pyeongnim dam recorded the lowest water storage rate of 27.3% on May 4, 2023. Due to a lack of precipitation starting in the spring of 2022, Pyeongnim dam was placed at a drought concern level on June 19, 2022, and entered the severe drought level on August 21. Pyeongrim dam and Suyangje(dam) have different operating institutions. Nevertheless, the low water level was not reached at Pyeongnim dam through organic linkage operation in a drought situation. Pyeongnim dam was able to stably supply water to 63,000 people in three counties. In order to maximize the use of limited water resources, we must review ways to move water smoothly between basins and water sources, and prepare for water shortages caused by climate change by establishing a consumer-centered water supply system.