• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.2
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• pp.63-73
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• 2020

Drought is considered as a devastating hazard that causes serious agricultural, ecological and socio-economic impacts worldwide. Fundamentally, the drought can be defined as temporarily different levels of inadequate precipitation, soil moisture, and water supply relative to the long-term average conditions. From no unified definition of droughts, droughts have been divided into different severity level, i.e., moderate drought, severe drought, extreme drought and exceptional drought. The drought severity classification defined the ranges for each indicator for each dryness level. Because the ranges of the various indicators often don't coincide, the final drought category tends to be based on what the majority of the indicators show and on local observations. Evaporative Stress Index (ESI), a satellite-based drought index using the ratio of potential and actual evaporation, is being used as a index of the droughts occurring rapidly in a short period of time from studies showing a more sensitive and fast response to drought compared to Standardized Precipitation Index (SPI), and Palmer Drought Severity Index (PDSI). However, ESI is difficult to provide an objective drought assessment because it does not have clear drought severity classification criteria. In this study, U.S. Drought Monitor (USDM), the standard for drought determination used in the United States, was applied to ESI, and the Percentile method was used to classify drought categories by severity. Regarding the actual 2017 drought event in South Korea, we compare the spatial distribution of drought area and understand the USDM-based ESI by comparing the results of Standardized Groundwater level Index (SGI) and drought impact information. These results demonstrated that the USDM-based ESI could be an effective tool to provide objective drought conditions to inform management decisions for drought policy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.3
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• pp.195-202
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• 2007

The normalized difference in incident solar energy between a target surface and a level surface (overheating index, OHI) is useful in eliminating estimation error of site-specific maximum temperature in complex terrain. Due to the complexity in its calculation, however, an empirical proxy variable called northern exposure index (NEI) which combines slope and aspect has been used to estimate OHI based on empirical relationships between the two. An experiment with real-world landscape and temperature data was carried out to evaluate performance of the NEI - derived OHI (N-OHI) in reduction of spatial interpolation error for daily maximum temperature compared with that by the original OHI. We collected daily maximum temperature data from 7 sites in a mountainous watershed with a $149 km^2$ area and a 795m elevation range ($651{\sim}1,445m$) in Pyongchang, Kangwon province. Northern exposure index was calculated for the entire 166,050 grid cells constituting the watershed based on a 30-m digital elevation model. Daily OHI was calculated for the same watershed ana regressed to the variation of NEI. The regression equations were used to estimate N-OHI for 15th of each month. Deviations in daily maximum temperature at 7 sites from those measured at the nearby synoptic station were calculated from June 2006 to February 2007 and regressed to the N-OHI. The same procedure was repeated with the original OHI values. The ratio sum of square errors contributable by the N-OHI were 0.46 (winter), 0.24 (fall), and 0.01 (summer), while those by the original OHI were 0.52, 0.37 and 0.15, respectively.

• Korean Institute of Interior Design Journal
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• v.20 no.4
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• pp.174-182
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• 2011

This study analyzed visitors' behaviors in the viewpoint of Attraction Power and Holding Power of exhibits on the basis of exhibition layout of real science museums. Through the analysis, the study grasped efficiency of analysis index and exhibition environment elements which might have an effect on planning the exhibition space of a large-scale museum and producing detailed ranges of exhibition. The main indicators used are: 1. Attraction Power: it indicates the relative incidence of people who have stopped in front of an object/exhibit during the exhibition tour. It is calculated by dividing the number of people who stop by the total number of people who have visited the museum or gallery. 2. Holding Power: it measures the average time spent in front of an information/communication element. It is calculated by dividing the average time of stay by the time "necessary" to read an element. As a result of analyzing the exhibition areas of National Science Museum (Daejeon) and National Museum of Emerging Science and Innovation(Tokyo), the Holding Power was found to be relatively lower than the Attracting Power. This means that 3.5 out of 10 visitors stop in front of the exhibit in 6 exhibition areas, and among these, only 1/10 is used when compared to the user required time of the exhibits. In other words, like the method of deriving an analysis index, the stage of viewing can be categorized as Attracting Power and Holding Power, and because the stage from Attracting Power to the stage of Holding Power are strongly linked, it shows that it is not easy to display a meaningful result. Except, the general distribution of Attracting Power was shown to be high from the entrance area of the exhibition hall based on the standard of viewing sequence. Also, the Holding Power became sequentially lower according to the sequence of exhibition viewing and displayed a meaningful interrelationship with the distribution ratio of island exhibits. In the case of island exhibition method, it is less influenced by the movement flow of visitors when compared to the wall type method of exhibition and can be understood as an exhibition method that provides spatial chances enabling stopping and viewing.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.124-131
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• 2009

A reliable detection of regions in radiography is one of the most important task before the evaluation of defects on welded joints. The extracted features is to be classified into distinctive clusters for each segmented region. But conventional segmentation techniques give unsatisfactory results for this task due to the spatial superposition of intensity and low signal-to-ratio(SNR) in radiographic images. The usage of global or local processes not only provide the necessary noise resistance but also fail in classification of regions. In this paper, we presents an appropriate approach for segmentation of region-based indications in industrial Computed Radiography(CR) images. The geometric differences between welded and non-welded area which is generated on radiography as the representative regions(background, thickness, middle and welded region in steel tube image) have constructed the hierarchical structure. Although this structure is contaminated by noise, the scheme between regions can be selected by the help of local clustering based on distinctive geometric property of each region. Because of the geometric nature of the considered region and so that the region is selected layer by layer, and that the real class represents the boundary between regions, the vertical and horizontal clustering process in each layer must be judicious. In order to show the effectiveness of this approach, a comparative experiment of various segmentation method is performed on industrial steel tube CR images.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.883-896
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• 2023

As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.

• Korean Journal of Environmental Biology
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• v.22 no.1
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• pp.57-65
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• 2004

In order to determine the effect of fresh water inflow from the Heongsan river on the changes of water quality in the Yeongil Bay (Korea), the seasonal changes of water temperature, salinity, chemical oxygen demand (COD), dissolved inorganic nitrogen(DIN) and phosphate phosphorus ($PO_4$-P) concentrations were examined using the data set obtained five fixed points of Yeongil Bay from 1998 to 2000. The distributions and changes of COD and concentrations of total inorganic phosphorous (TIP) and nitrogen (TIN) at three points Heongsan river, were also compared with those of Yeongil Bay. Based on the correlations of DIN and $PO_4$-P, it was found that the inflow of freshwater affected on the water quality of Yeongil Bay. Such a complicacy was confirmed by the prominent differences in n few water quality measures between Site 1(the innermost area) and Site 5 (the mouth of the bay). The negative correlations in $\Delta N/\Delta P $ at sites 1, 2 and 3 of the inner-part of the bay also indicated a large effect of freshwater inflow on the water quality of the bay. The extremely low atomic ratio of an average of 6.4 in $\Delta N/\Delta P $ compared to the Redfild ratio suggested that the DIN was depleted in the overall bay system. In contrast, it was inferred that the excessive PO$_4$-P concentration was due to the inflow of freshwater from the Heongsan river.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.495-505
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• 2006

In order to classify aerosol type, Aerosol Optical Thickness (AOT) and Fine mode Fraction (FF), which is the optical thickness ratio of small particles$(<1{\mu}m)$ to total particles, data from MODIS (MODerate Imaging Spectraradiometer) aerosol products were analyzed over North-East Asia during one year period of 2005. A study area was in the ocean region of $20^{\circ}N\sim50^{\circ}N$ and $110^{\circ}E\simt50^{\circ}E$. Three main atmospheric aerosols such as dust, sea-salt, and pollution can be classified by using the relationship between AOT and FF. Dust aerosol has frequently observed over the study area with relatively high aerosol loading (AOT>0.3) of large particles (FF<0.65) and its contribution to total AOT in spring was up to 24.0%. Pollution aerosol, which is originated from anthropogenic sources as well as a natural process like biomass burning, has observed in the regime of high FF (>0.65) with wide AOT variation. Average pollution AOT was $0.31{\pm}0.05$ and its contribution to total AOT was 79.8% in summer. Characteristic of sea-salt aerosol was identified with low AOT (<0.3), almost below 0.1, and slightly higher FF than dust and lower FF than pollution. Seasonal analysis results show that maximum AOT $(0.33{\pm}0.11)$ with FF $(0.66{\pm}0.21)$ in spring and minimum AOT $(0.19{\pm}0.05)$, FF $(0.60{\pm}0.14)$ in fall were observed in the study area. Spatial characteristic was that AOT increasing trend is observed as closing to the eastern part of China due to transport of aerosols from China by the prevailing westerlies.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.4
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• pp.72-85
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• 2009

This study attempts to examine the principles of landscape composition for a 'Suhwon(書院)' and the meaning and value of its traditional landscape architecture, in order to apply the results to the design of modern landscape architecture. A 'Suhwon' is a vital space containing the form and meaning of human activity. This study analyzes the characteristics of landscape composition in the construction of the Namgea Suhwon, located in Hamyang, by examining the form and meaning of its area and composition. The Namgea Suhwon was constructed with a suitable configuration and harmony in a good location, neither field nor mountain, and which encompasses transcendence and a return after passage through a period of birth and abundance. Its appearance means 'life existence and hidden death(生居死幽)'. Its spatial system is a reflection of the idea of Samshinoje(三神五帝: The three abilities of Providence and its five subjects) connected with Ilsangje -Samshin -Ohje. It was built based on the idea of Biryebudong(非禮不動) meaning that one should follow only good decorum and avoid discourtesy, complying with "the frame of decorum" developed by the family rites of Chu Hsi. The environmental design of the Namgea Suhwon was interrupted by the material confrontation between mountains and water and a binary code system, such as front to rear, length to breadth, and movement to stillness. The design did not adhere to stiff axes, but pursued the harmonic principles of asymmetric balance in the building and the yard, which are very naturalistic. The name 'Namgea Suhwon' is closely related with the view of placement(置) and harmony(和), which are unified with the function and meaning formed by connecting Sung Confucianism with the Pungsu-Sasinsa structure in the layout of the grounds. When examining the D/H ratio of the building and yard, it can be seen that the spaces of Ganghak, Yusang and Jehyang were built appropriately, according to the natural characteristics of each space, such as a sense of openness, enclosure, tension, relief, enhancement, and hierarchical order. The spaces also reflect human scale concepts that take advantage of auditory features. The transition process after the construction of 'Namgea Suhwon' reveals the intentions of the builder to create an ecological landscape composition based on Placement and Harmony. Placement embodies' a purposeful space in which nature and the building are connected naturally, 'incomplete open space pursuing completion', and 'potential beauty in which tension and relaxation are repeated'. Harmony embodies 'order and continuity having a sense of unity with the natural environment' and the 'sharing of daily life and memory'. 'Namgea Suhwon' contains many ideas for landscape planning, land use and the design of a campus environment.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.133-149
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• 2022

Existing domestic studies on estimating rice yield were mainly implemented at the level of cities and counties in the entire nation using MODIS satellite images with low spatial resolution. Unlike previous studies, this study tried to estimate rice yield at the level of eup-myon-dong in Gimje-si, Jeollabuk-do using Sentinel-2 satellite images with medium spatial resolution, rainfall and soil data, and then to evaluate its accuracy. Five vegetation indices such as NDVI, LAI, EVI2, MCARI1 and MCARI2 derived from Sentinel-2 images of August 1, 2018 for Gimje-si, Jeollabuk-do, rainfall and paddy soil-type data were aggregated by the level of eup-myon-dong and then rice yield was estimated with gamma generalized linear model, an expanded variant of multi-variate regression analysis to solve the non-normality problem of dependent variable. In the rice yield model finally developed, EVI2, rainfall days in September, and saline soils ratio were used as significant independent variables. The coefficient of determination representing the model fit was 0.68 and the RMSE for showing the model accuracy was 62.29kg/10a. This model estimated the total rice production in Gimje-si in 2018 to be 96,914.6M/T, which was very close to 94,470.3M/T the actual amount specified in the Statistical Yearbook with an error of 0.46%. Also, the rice production per unit area of Gimje-si was amounted to 552kg/10a, which was almost consistent with 550kg/10a of the statistical data. This result is similar to that of the previous studies and it demonstrated that the rice yield can be estimated using Sentinel-2 satellite images at the level of cities and counties or smaller districts in Korea.