• Korean Journal of Radiology
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• v.25 no.2
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• pp.166-178
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• 2024

Objective: This study aimed to determine the predictive performance of non-contrast CT (NCCT) signs for hemorrhagic growth after intracerebral hemorrhage (ICH) when stratified by onset-to-imaging time (OIT). Materials and Methods: 1488 supratentorial ICH within 6 h of onset were consecutively recruited from six centers between January 2018 and August 2022. NCCT signs were classified according to density (hypodensities, swirl sign, black hole sign, blend sign, fluid level, and heterogeneous density) and shape (island sign, satellite sign, and irregular shape) features. Multivariable logistic regression was used to evaluate the association between NCCT signs and three types of hemorrhagic growth: hematoma expansion (HE), intraventricular hemorrhage growth (IVHG), and revised HE (RHE). The performance of the NCCT signs was evaluated using the positive predictive value (PPV) stratified by OIT. Results: Multivariable analysis showed that hypodensities were an independent predictor of HE (adjusted odds ratio [95% confidence interval] of 7.99 [4.87-13.40]), IVHG (3.64 [2.15-6.24]), and RHE (7.90 [4.93-12.90]). Similarly, OIT (for a 1-h increase) was an independent inverse predictor of HE (0.59 [0.52-0.66]), IVHG (0.72 [0.64-0.81]), and RHE (0.61 [0.54-0.67]). Blend and island signs were independently associated with HE and RHE (10.60 [7.36-15.30] and 10.10 [7.10-14.60], respectively, for the blend sign and 2.75 [1.64-4.67] and 2.62 [1.60-4.30], respectively, for the island sign). Hypodensities demonstrated low PPVs of 0.41 (110/269) or lower for IVHG when stratified by OIT. When OIT was ≤ 2 h, the PPVs of hypodensities, blend sign, and island sign for RHE were 0.80 (215/269), 0.90 (142/157), and 0.83 (103/124), respectively. Conclusion: Hypodensities, blend sign, and island sign were the best NCCT predictors of RHE when OIT was ≤ 2 h. NCCT signs may assist in earlier recognition of the risk of hemorrhagic growth and guide early intervention to prevent neurological deterioration resulting from hemorrhagic growth.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.27-44
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• 1999

Digital maps produced in Korea are various in scale and include a lot of geographic and attribute data. In this study, it is argued that, to reduce the production cost and the difficulties for renewal, it is necessary to establish the already nationally drawn 1:5,000 scale digital maps as the base maps and simplify them as much as the TIGER files in the U.S. The comprehensive data included in the digital maps in Korea are mostly land use information, which are supposed to be established separately from the digital maps. The land use information system could be maintained and updated cheaply and frequently at the local government level. In response to common needs, the land use information could be imported to GIS and used for analyses. As technologies and societies changes, the Census questions and methodologies should be changed for better uses. Along with GIS, the Census would be developed and processed more reliably and efficiently. Also, it is recommended for Korean government to develop the Census Tract and Block Group system. Current Eup, Myon, Dong as basic units for Census information may not be useful or effective for micro level urban analyses and public service planning activities because of their large population and land areas. It is recommended that optimum population of a Census Tract be 5,000 and a Block Groups 1,500, and one Census Tract includes 1~9 Block Groups. It is recommend that Census Tract and Block Group boundary lines be decided flexibly in light of population, physical features, socio-economic attributes, and tradition. For urban analyses using GIS, socio-economic census data, city government's information such as parcel data and building permit data, survey data, and satellite image data could also be used. The existence of Census Tracts and Block Groups as well as GIS could help for the data and methods to be useful for urban analyses and public service provisions.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.100-118
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• 2015

This study established a land-cover classification method on objects using satellite images, and figured out distributional patterns of land cover according to categories through spatial statistics techniques. Object-based classification generated each land cover classification map by spectral information, texture information, and the combination of the two. Through assessment of accuracy, we selected optimum land cover classification map. Also, to figure out spatial distribution pattern of land cover according to categories, we analyzed hot spots and quantified them. Optimal weight for an object-based classification has been selected as the Scale 52, Shape 0.4, Color 0.6, Compactness 0.5, Smoothness 0.5. In case of using the combination of spectral information and texture information, the land cover classification map showed the best overall classification accuracy. Particularly in case of dry fields, protected cultivation, and bare lands, the accuracy has increased about 12 percent more than when we used only spectral information. Forest, paddy fields, transportation facilities, grasslands, dry fields, bare lands, buildings, water and protected cultivation in order of the higher area ratio of DMZ according to categories. Particularly, dry field sand transportation facilities in Yanggu occurred mainly in north areas of the civilian control line. dry fields in Cheorwon, forest and transportation facilities in Inje fulfilled actively in south areas of the civilian control line. In case of distributional patterns according to categories, hot spot of paddy fields, dry fields and protected cultivation, which is related to agriculture, was distributed intensively in plains of Yanggu and in basin areas of Cheorwon. Hot spot areas of bare lands, waters, buildings and roads have similar distribution patterns with hot spot areas related to agriculture, while hot spot areas of bare lands, water, buildings and roads have different distributional patterns with hot spot areas of forest and grasslands.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.52-68
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• 2014

In this study, we investigated the seasonal variation of SST(Sea Surface Temperature) and thermal effluents estimated by using Landsat-7 ETM+ around the Kori Nuclear Power Plant for 10 years(2000~2010). Also, we analyzed the direction and range of thermal effluents dispersion by the tidal current and tide. The results are as follows, First, we figured out the algorithm to estimate SST through the linear regression analysis of Landsat DN(Digital Number) and NOAA SST. And then, the SST was verified by compared with the in situ measurement and NOAA SST. The determination coefficient is 0.97 and root mean square error is $1.05{\sim}1.24^{\circ}C$. Second, the SST distribution of Landsat-7 estimated by linear regression equation showed $12{\sim}13^{\circ}C$ in winter, $13{\sim}19^{\circ}C$ in spring, and $24{\sim}29^{\circ}C$ and $16{\sim}24^{\circ}C$ in summer and fall. The difference of between SST and thermal effluents temperature is $6{\sim}8^{\circ}C$ except for the summer season. The difference of SST is up to $2^{\circ}C$ in August. There is hardly any dispersion of thermal effluents in August. When it comes to the spread range of thermal effluents, the rise range of more than $1^{\circ}C$ in the sea surface temperature showed up to 7.56km from east to west and 8.43km from north to south. The maximum spread area was $11.65km^2$. It is expected that the findings of this study will be used as the foundational data for marine environment monitoring on the area around the nuclear power plant.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.80-92
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• 2007

Forest fire is the dominant large-scale disturbance mechanism in the Korean temperate forest, and it strongly influences forest structure and function. Moreover burn severity incorporates both short- and long-term post-fire effects on the local and regional environment. Burn severity is defined by the degree to which an ecosystem has changed owing to the fire. Vegetation rehabilitation may specifically vary according to burn severity after fire. To understand burn severity and process of vegetation rehabilitation at the damaged area after large-fire is required a lot of man powers and budgets. However the analysis of burn severity in the forest area using satellite imagery can acquire rapidly information and more objective results remotely in the large-fire area. Space and airbone sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. For classifying fire damaged area and analyzing burn severity of Samcheok fire area occurred in 2000, Cheongyang fire in 2002, and Yangyang fire in 2005 we utilized Normalized Burn Ratio(NBR) technique. The NBR is temporally differenced between pre- and post-fire datasets to determine the extent and degree of change detected from burning. In this paper we use pre- and post-fire imagery from the Landsat TM and ETM+ imagery to compute the NBR and evaluate large-scale patterns of burn severity at 30m spatial resolution. 65% in the Samcheok fire area, 91% in the Cheongyang fire area and 65% in the Yangyang fire area were corresponded to burn severity class above 'High'. Therefore the use of a remotely sensed Differenced Normalized Burn Ratio(${\Delta}NBR$) by RS and GIS allows for the burn severity to be quantified spatially by mapping damaged domain and burn severity across large-fire area.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.115-127
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• 2018

This study aims to propose management strategies of ventilation paths for improving urban thermal environments. For this purpose, Gimhae-si in Gyeongsangnamdo was selected as a study area. We analyzed hot spots and cool spots in Gimhae by using Landsat 8 satellite image data and spatial statistical analysis, and finally derived the vulnerable areas to thermal environment. In addition, the characteristics of ventilation paths including wind direction and wind speed were analyzed by using data of the wind resource map provided by Korea Meteorological Administration. As a result, it was found that a lot of hot spots were similar to those with weak wind such as Jinyoung-eup, Jillye-myeon, Juchon-myeon and the downtown area. Based on the analysis, management strategies of ventilation paths in Gimhye were presented as follows. Jinyoung-eup and Jillye-myeon with hot spot areas and week wind areas have a strong possibility that hot spot areas will be extended and strengthened, because industrial areas are being built. Hence, climate-friendly urban and architectural plans considering ventilation paths is required in these areas. In Juchon-myeon, where industrial complexes and agricultural complexes are located, climate-friendly plans are also required because high-rise apartment complexes and an urban development zone are planned, which may induce worse thermal environment in the future. It is expected that a planning of securing and enlarging ventilation paths will be established for climate-friendly urban management. and further the results will be utilized in urban renewal and environmental planning as well as urban basic plans. In addition, we expect that the results can be applied as basic data for climate change adaptation plan and the evaluation system for climate-friendly urban development of Gimhye.

• Journal of Korea Water Resources Association
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• v.39 no.5 s.166
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• pp.453-466
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• 2006

The objective of this study was to analyze the changes in the hydrological environment in Soyanggang-dam watershed due to climate change results (in yews 2050 and 2100) which were simulated using CCCma CGCM2 based on SRES A2 and B2. The SRES A2 and B2 were used to estimate NDVI values for selected land use using the relation of NDVI-Temperature using linear regression of observed data (in years 1998$\sim$2002). Land use change based on SRES A2 and B2 was estimated every 5- and 10-year period using the CA-Markov technique based on the 1985, 1990, 1995 and 2000 land cover map classified by Landsat TM satellite images. As a result, the trend in land use change in each land class was reflected. When land use changes in years 2050 and 2100 were simulated using the CA-Markov method, the forest class area declined while the urban, bareground and grassland classes increased. When simulation was done further for future scenarios, the transition change converged and no increasing trend was reflected. The impact assessment of evapotranspiration was conducted by comparing the observed data with the computed results based on three cases supposition scenarios of meteorological data (temperature, global radiation and wind speed) using the FAO Penman-Monteith method. The results showed that the runoff was reduced by about 50% compared with the present hydrologic condition when each SRES and periods were compared. If there was no land use change, the runoff would decline further to about 3$\sim$5%.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.577-587
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• 2021

Drought is generally considered to be a natural disaster caused by accumulated water shortages over a long period of time, taking months or years and slowly occurring. However, climate change has led to rapid changes in weather and environmental factors that directly affect agriculture, and extreme weather conditions have led to an increase in the frequency of rapidly developing droughts within weeks to months. This phenomenon is defined as 'Flash Drought', which is caused by an increase in surface temperature over a relatively short period of time and abnormally low and rapidly decreasing soil moisture. The detection and analysis of flash drought is essential because it has a significant impact on agriculture and natural ecosystems, and its impacts are associated with agricultural drought impacts. In South Korea, there is no clear definition of flash drought, so the purpose of this study is to identify and analyze its characteristics. In this study, flash drought detection condition was presented based on the satellite-derived drought index Evaporative Stress Index (ESI) from 2014 to 2018. ESI is used as an early warning indicator for rapidly-occurring flash drought a short period of time due to its similar relationship with reduced soil moisture content, lack of precipitation, increased evaporative demand due to low humidity, high temperature, and strong winds. The flash droughts were analyzed using hydrometeorological characteristics by comparing Standardized Precipitation Index (SPI), soil moisture, maximum temperature, relative humidity, wind speed, and precipitation. The correlation was analyzed based on the 8 weeks prior to the occurrence of the flash drought, and in most cases, a high correlation of 0.8(-0.8) or higher(lower) was expressed for ESI and SPI, soil moisture, and maximum temperature.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.65-81
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• 2021

In this study, soil moisture and evapotranspiration were calculated throughout South Korea using the Korea Land Data Assimilation System(KLDAS) of the Korea-Land Surface Information System(K-LIS) built on the basis of the Land Information System (LIS). The hydrometeorological data sets used to drive K-LIS and build KLDAS are MERRA-2(Modern-Era Retrospective analysis for Research and Applications, version 2) GDAS(Global Data Assimilation System) and ASOS(Automated Synoptic Observing System) data. Since ASOS is a point-based observation, it was converted into grid data with a spatial resolution of 0.125° for the application of KLDAS(ASOS-S, ASOS-Spatial). After comparing the hydrometeorological data sets applied to KLDAS against the ground-based observation, the mean of R² ASOS-S, MERRA-2, and GDAS were analyzed as temperature(0.994, 0.967, 0.975), pressure(0.995, 0.940, 0.942), humidity (0.993, 0.895, 0.915), and rainfall(0.897, 0.682, 0.695), respectively. For the hydrologic output comparisons, the mean of R² was ASOS-S(0.493), MERRA-2(0.56) and GDAS (0.488) in soil moisture, and the mean of R² was analyzed as ASOS-S(0.473), MERRA-2(0.43) and GDAS(0.615) in evapotranspiration. MERRA-2 and GDAS are quality-controlled data sets using multiple satellite and ground observation data, whereas ASOS-S is grid data using observation data from 103 points. Therefore, it is concluded that the accuracy is lowered due to the error from the distance difference between the observation data. If the more ASOS observation are secured and applied in the future, the less error due to the gridding will be expected with the increased accuracy.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.