• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1435-1446
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• 2021

Wind and flood damage caused by typhoons causes a lot of damage to the Korean Peninsula every year. In order to minimize damage, a preliminary analysis of damage estimation and evacuation routes is required for rapid decision-making. This study attempted to develop an analysis module that can provide necessary information according to the disaster stage. For use in the preparation stage, A function to check past typhoon routes and past damage information similar to typhoon routes heading north, a function to extract isolated dangerous areas, and a function to extract reservoir collapse areas were developed. For use in the early stages of response and recovery, a function to extract the expected flooding range considering the current flooding depth, a function to analyze expected damage information on population, buildings, farmland, and a function to provide evacuation information were included. In addition, an automated web map creation method was proposed to express the analysis results. The analysis function was developed and modularized based on Python open source, and the web display function was implemented based on JavaScript. The tools developed in this study are expected to be efficiently used for rapid decision-making in the early stages of monitoring against storm and flood damage.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.525-532
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• 2021

In the ocean, it is difficult to separate the effects of one cause due to the multiple causes, but the self-organizing map can be analyzed by adding other factors to the cluster result. Therefore, in this study, the results of the clustering of sea level data were applied to sea surface temperature. Sea level data was clustered into a total of 6 nodes. The difference between sea surface temperature and sea level height has a one-month delay, which applied sea surface temperature data a month ago to the clustered results. As a result of comparing the mean of sea surface temperature of 140 to 150°E, where the sea surface temperature was variously distributed, in the case of nodes 1, 3, and 5, it was possible to find a meandering sea surface temperature distribution that is clearly distinguished from the sea level data. While nodes 2, 4 and 6, the sea surface temperature distribution was smooth. In this study, sea surface temperature data were applied to the clustered results of sea level data, but later it is necessary to apply wind or geostrophic velocity data to compare.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.785-798
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• 2023

Recently, forest fires have become frequent due to climate change, and the size of forest fires is also increasing. Forest fires in Korea continue to cause more than 100 ha of forest fire damage every year. It was found that 90% of the large-scale wildfires that occurred in Gangwon-do over the past five years were concentrated in the east coast area. The east coast area has a climate vulnerable to forest fires such as dry air and intermediate wind, and forest conditions of coniferous forests. In this regard, studies related to various forest fire analysis, such as predicting the risk of forest fires and calculating the risk of forest fires, are being promoted. There are many studies related to risk analysis for forest areas in consideration of weather and forest-related factors, but studies that have conducted risk analysis for forest-friendly areas are still insufficient. Management of forest adjacent areas is important for the protection of human life and property. Forest-adjacent houses and facilities are greatly threatened by forest fires. Therefore, in this study, a grid-based forest fire-related disaster risk map was created using factors affected by forest-neighboring areas using national branch numbers, and differences in risk ratings were compared for forest areas and areas adjacent to forests based on Gangneung forest fire cases.

• Spatial Information Research
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• v.17 no.2
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• pp.243-249
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• 2009

Damages from typhoon events have contributed more than 60 percent of total economic and social loss and the size of loss have been increased up to 800 million dollars per year in Korea, It is therefore necessary to make an effort to mitigate the loss of natural disasters. To facilitate the evaluation of damages in advance and to support the decision making to recover the damages, scientific methods have been adopted. With the effort, GIS data can provide various tools. Three components of hazard mapping are estimation of hazard, inventory for vulnerable features, and fragility of each feature. Vulnerability of natural disaster can be obtained by relation between loss and meteorological data such as precipitation and wind speed. Features can be categorized from other GIS data of public facilities and private properties, and then social and economic loss can be estimated. At this point, GIS data conversions for each model are required. In this study, we build a method to estimate typhoon risk based on GIS data such as DEM, land cover and land use map, facilities.

• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.481-487
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• 2005

In this study, a GIS model to simulate the behavior of surface forest fires was developed on the basis of forest fire growth prediction algorithm. This model consists of three modules for data-handling, simulation and report writing. The data-handling module was designed to interpret such forest fire environment factors as terrain, fuel and weather and provide sets of data required in analyzing fire behavior. The simulation module simulates the fire and determines spread velocity, fire intensity and burnt area over time associated with terrain slope, wind, effective humidity and such fuel condition factors as fuel depth, fuel loading and moisture content for fire extinction. The module is equipped with the functions to infer the fuel condition factors from the information extracted from digital vegetation map sand the fuel moisture from the weather conditions including effective humidity, maximum temperature, precipitation and hourly irradiation. The report writer has the function to provide results of a series of analyses for fire prediction. A performance test of the model with the 2002 Chungyang forest fire showed the predictive accuracy of 61% in spread rate.

• Bulletin of the Korean Space Science Society
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• 2010.04a
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• pp.30.2-30.2
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• 2010

It is a mistaken impression that the midlatitude ionosphere was a very stable region with well-known morphology and physical mechanism. However, the large disturbances of midlatitude ionospheric contents in response to global thermospheric changes during geomagnetic storms are reported in recent studies using global GPS TEC map and space-born thermospheric UV images, and its importance get higher with the increasing application areas of space navigation systems and radio communication which are mostly used in the midlatitudes. Positive and negative storm phases are used to describe increase and decrease of ionospheric electron density. Negative storms result generally from the enhanced loss rate of electron density according to the neutral composition changes which are initiated by Joule heating in high-latitudes during geomagnetic storms. In contrast, positive ionospheric storms have not been well understood because of rare measurements to explain the mechanisms. The large enhancements of ground-based GPS TEC in Korea were observed on 8 and 10 November 2004. The positive ionospheric storm was continued except for dawn on 8 November, and its maximum value is ~65 TECU of ~3 times compared with the monthly mean TEC values. The other positive phase on 10 November begin to occur in day sector and lasted for more than 6 hours. The O/N2 ratios from GUVI/TIMED satellite show ~1.2 in northern hemisphere and ~0.3 in southern hemisphere of the northeast Asian sector on 8 and 10 November. We suggest the asymmetric features of O/N2 ratios in the Northeast Asian sector may play an important role in the measured GPS TEC enhancements in Korea because global thermospheric wind circulation can globally change the chemical composition during geomagnetic storms.

• Journal of Astronomy and Space Sciences
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• v.40 no.4
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• pp.199-215
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• 2023

The Korea Pathfinder Lunar Orbiter (KPLO), the first South Korea lunar exploration probe, successfully arrived at the Moon on December, 2022 (UTC), following a 4.5-month ballistic lunar transfer (BLT) trajectory. Since the launch (4 August, 2022), the KPLO magnetometer (KMAG) has carried out various observations during the trans-lunar cruise phase and a 100 km altitude lunar polar orbit. KMAG consists of three fluxgate magnetometers capable of measuring magnetic fields within a ± 1,000 nT range with a resolution of 0.2 nT. The sampling rate is 10 Hz. During the originally planned lifetime of one year, KMAG has been operating successfully while performing observations of lunar crustal magnetic fields, magnetic fields induced in the lunar interior, and various solar wind events. The calibration and offset processes were performed during the TLC phase. In addition, reliabilities of the KMAG lunar magnetic field observations have been verified by comparing them with the surface vector mapping (SVM) data. If the KPLO's mission orbit during the extended mission phase is close enough to the lunar surface, KMAG will contribute to updating the lunar surface magnetic field map and will provide insights into the lunar interior structure and lunar space environment.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Journal of the Korean earth science society
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• v.34 no.6
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• pp.536-549
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• 2013

This study investigates the damages of and analyzes the social and economic impacts of volcanic ash eruptions in the world in order to estimate the potential volcanic ash impacts in South Korea when Mt. Baekdusan volcano erupts in the future. First, we build a comparison chart called "the impact of volcanic ash" on each economic and social sector by using major volcanic eruptions and we compare the damage with respect to volcanic ash thickness/weights. Secondly, we analyze the social and economic impact from volcanic ash. The economic damage is not likely to occur in South Korea, unless Mt. Baekdusan erupts in winter. However, the potential damage should not be overlooked because the volcanic ash may have a global impact around the world. If Mt. Baekdusan volcano erupts when the wind blows from north or northeast, the volcanic ash may then significantly affect South Korea of which economy is highly dependent on exports. Particularly when the volcanic ash moves to the densely populated metropolitan areas or agricultural areas, the damage can be significant. In preparation for the potential volcanic disasters, the volcanic ash forecast table suitable for South Korea should be prepared. In addition, building a Korean volcanic ash hazard map in advance will have a strategic significance.

• Journal of the Korean Geographical Society
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• v.32 no.1
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• pp.31-46
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• 1997

The purposes of this paper are to classify the spatial distribution types of precipitation by making daily isohyetal maps based on the winter daily precipitation and to analyse both the distributional characteristics of precipitation during the winter in South Korea and the synoptic characteristics related to them. Also, the correspondence between the spatial distribution types of precipitation and the synoptic characteristics occuring among them is examined with regards to pressure patterns and then precipitation distribution types. In addition, the characteristics of the pressure fields and temperature fields in 850hPa, 700hPa, and 500hPa level were analysed to find out the difference between the Ullung-do type and the Ullung-do${\cdot}$Honam type, which have similar characteristics on the surface weather map. As a result, the Ullung-do area showed a high frequency of occurrence regardless of precipitation classes, the East Coast area revealed a higher frequency of occurrence in over the 5mm section, while the Honam area had high frequency of occurrence in the 1~5mm section. There are twelve distribution types of precipitation during the winter. These distribution types show clear changes according to the season. The difference in precipitation distribution between the Ullung-do type and the Ullung-do${\cdot}$Honam type has a close relationship with the aspect of the upper cold air advection rather than the direction and the speed of the wind.