• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.3
• /
• pp.713-718
• /
• 2014

This paper proposed a real-time monitoring system that can realize effective operation of snowplows each of the local autonomous entities secures to cope with disasters in Korea like a wintertime heavy snowfall and also can promptly cope with the spot facing a heavy snowfall disaster by doing real-time monitoring on the information of the snow-removal site and the mobility of the vehicles. Also, the study has designed a relay terminal analysis tool so that the proposed system can analyze all kinds of controlling information and diagnose the relay terminal effectively. The proposed system can realize effective and emergent coping with the situations of a heavy snowfall disaster through real-time routing trace as well as effective work progress within a short time by doing real-time monitoring on the information about the status of snow-removal work and vehicle controlling for snow-removal work as well as the location information of snow-removal vehicles in the situations of a heavy snowfall.

• Atmosphere
• /
• v.29 no.3
• /
• pp.269-282
• /
• 2019

While it is important to obtain the accurate information on snowfall data due to the increase in damage caused by the heavy snowfall in the winter season, it is not easy to observe the snowfall quantitatively. Recently, snow measurements using a weighing precipitation gauge have been carried out, but there is a problem that high snowfall intensity results in low accuracy. Also, the observed snowfall data are sensitive depending on wind speed, temperature, and humidity. In this study, a new process of quality control for snow water equivalent (SWE) data of the weighing precipitation gauge were proposed to cover the low accuracy of snow data and maximize the data utilization. Snowfall data (SWE) observed by Pluvio, Parsivel, snow-depth meter using laser or ultrasonic, and rainfall gauge in Cloud Physics Observation Site (CPOS) were compared and analyzed. Applying the QC algorithm including the use of number of hydrometeor particles as reference, the increased SWE per the unit time was determined and the data noise was removed and marked by flag. The SWE data converted by the number concentration of hydrometeor particles are tested as a method to restore the QC-removed data, and show good agreement with those of the weighing precipitation gauge, though requiring more case studies. The three events data for heavy snowfall disaster in Pyeongchang area was analyzed. The SWE data with improved quality was showed a good correlation with the eye-measured data ($R^2$ > 0.73).

• Journal of Korean Society for Geospatial Information Science
• /
• v.20 no.4
• /
• pp.135-143
• /
• 2012

Remote sensing which observes repeatedly the whole Earth and GIS-based decision-making technology have been utilized widely in disaster management such as early warning monitoring, damage investigation, emergent rescue and response, rapid recovery etc. In addition, various countermeasures of national level to collect timely satellite imagery in emergency have been considered through the operation of a satellite with onboard multiple sensors as well as the practical joint use of satellite imagery by collaboration with space agencies of the world. In order to respond heavy snowfall disaster occurred on the east coast of the Korean Peninsula in February 2011, snow-covered regions were analyzed and detected in this study through NDSI(Normalized Difference Snow Index) considering reflectance of wavelength for MODIS sensor and change detection algorithm using satellite imagery collected from International Charter. We present the application case of National Disaster Management Institute(NDMI) which supported timely decision-making through GIS spatial analysis with various spatial data and snow cover map.

• Journal of the Korean earth science society
• /
• v.40 no.3
• /
• pp.240-258
• /
• 2019

Typhoons, torrential rainfall, and heavy snowfall cause catastrophic losses each year in the Republic of Korea. Therefore, if we can know the possibility of this phenomenon in advance through regular observations, it will be greatly beneficial to Korean society. Korea is surrounded by sea on its three sides, and the sea surface temperature (SST) directly or indirectly affects the development of typhoons, heavy rainfall, and heavy snowfall. Therefore, the characteristics of SST variability related to the high impact weather are investigated in this paper. The heavy rainfall in Korea was distributed around Seoul, Gyeonggi, and west and southern coast. The heavy snowfall occurred mainly in the eastern coastal (hereafter Youngdong Heavy Snow) and the southwestern region (hereafter Honam-type heavy snow). The SST variability was slightly different depending on the type and major occurrence regions of the high impact weather. When the torrential rain occurred, the SST variability was significantly increased in the regions extending to Jindo-Jeju island-Ieodo-Shanghai in China. When the heavy snow occurred, the SST variability has reduced in the southern sea of Jeju island, regardless of the type of heavy snowfall, whereas the SST variability has increased in the East Sea near $130^{\circ}E$ and $39^{\circ}N$. Areas with high SST variability are anticipated to be used as a basis for studying the atmospheric-oceanic interaction mechanism as well as for determining the background atmospheric aerosol observation area.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.63 no.2
• /
• pp.61-74
• /
• 2021

Agriculture is most closely related to weather, and the government pursues stable food production by weather research. However, abnormal weather conditions have occurred frequently around the world in recent years, and stable food production has been threatened. Among them, heavy snow in winter tends to increase in frequency and size, which causes serious damage to greenhouses. Therefore, it is imperative to build a system reflecting various demands to reduce the damage to agricultural facilities caused by heavy snow. A business model can realize this as a way of commercialization, however, no suitable model has been presented to date. Therefore, this study aims to design a representative business model that can establish a safety system by distributing a greenhouse disaster prevention warning system for heavy snow to farms.

• Journal of the Society of Disaster Information
• /
• v.13 no.2
• /
• pp.163-172
• /
• 2017

Because of abnormal weather, a heavy snow on the Northern latitudes occurs frequently. This has resulted in significant damage and recovery costs. In korea, it has been declared a special disaster area due to heavy snowfall in Gangneung and Pohang 2004, 2005 and 2011, so there was a revision of action instruction for the road snow removal. Although, in our current system, snow removing methodology, regional equipment holdings, and snow responsible interval, respectively, has been classified by the National Highway, near cities and provinces support system not yet prepared. Only, if snow removing is not possible within the region itself, which contained the contents of "support and assistance to military or nearby offices requests". In this thesis, we studied the disaster scenario development according to heavy snow and the response and support system to the features of each regional. For the scenario deduction, we preferentially collected day snowfall and disaster yearbook data to regionals, classified similar pattern and plotted GIS snow map. We also classified heavy snow disaster by region and type and we deduced five-step scenario. The five-step scenario is nationwide(1st-stage), the National Capital region(2nd-stage), the Chungcheong Provinces(3rd-stage), the Kangwon province(4th-stage) and the Ch?l a provinces(5th-stage). Therefore we build near provinces support system according to five-step scenario.

• Korean Journal of Remote Sensing
• /
• v.36 no.2_1
• /
• pp.217-229
• /
• 2020

Recently, weather changes in Korea have intensified due to global warming, and the five major natural disasters that occur mostly include heavy rains, typhoons, storms, heavy snow, and earthquakes. Busan is vulnerable to snow disaster, given that the amount of natural disaster damage in Busan accounts for more than 50% of the total amount in the entire metropolitan cities in Korea, and that the Busan area includes many hilly mountains. In this study, we attempted to identify vulnerable areas for snowfall disasters in Busan areas using the geographic information system (GIS) with the data for both geographical and anthropogenic characteristics. We produced the maps of vulnerable areas for evaluating factors that include altitude, slope, land cover, road networks, and demographics, and overlapped those maps to rank the vulnerability to snowfall disasters as the 5th levels finally. To weight each evaluating factor, we used an entropy method. The riskiest areas are characterized by being located in mountainous areas with roads, including Sansung-ro in Geumjeong-gu, Mandeok tunnel in Buk-gu, Hwangnyeongsan-ro in Suyeong-gu, and others, where road restrictions were actually enforced due to snowfall events in the past. This method is simple and easy to be updated, and thus we think this methodology can be adapted to identify vulnerable areas for other environmental disasters.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.4
• /
• pp.305-316
• /
• 2015

The GPS signal delays in troposphere, which are along the signal path between a transmitting satellite and GPS permanent station, can be used to retrieve the precipitable water vapor. The GPS remote sensing technique of atmospheric water vapor is capable of monitoring typhoon and detecting long term water vapor for tracking of earth’s climate change. In this study, we analyzed GPS precipitable water vapor variations during the heavy snowstorm event occurred in the Yeongdong area, 2014. The results show that the snowfall event were occurring after the GPS precipitable water vapor were increased, the maximum fresh snow depth was recorded after the maximum GPS precipitable water vapor was generated, in Kangneug and Wuljin, respectively. Also, we analyzed that the closely correlation among the GPS precipitable water vapor, the K-index and total index which was acquired by the upper air observation system during this snowstorm event was revealed.

• Journal of the Korean Society of Safety
• /
• v.38 no.6
• /
• pp.50-59
• /
• 2023

As the diversity of disasters continues to increase, the concept of "complex disasters" has gained prominence in various policies and studies related to disaster management. However, there has been a certain limitation in the availability of the systematic statistics or data in advancing policies and research initiatives related to complex disasters. This study aims to analyze the macro-level characteristics of the complex disasters that have occurred domestically utilizing a 30-year span of a news data. Initially, we categorize the complex disasters into the three types: "Natural disaster-Natural disaster", "Natural disaster-Social disaster", and "Social disaster-Social disaster". As a result, the "natural diaster-social disaster" type is the most prevalent. It is noted that "natual disaster-natural disaster" type has increased significantly in recent 10 years (2011-2020). In terms of specific disaster types, "Storm and Flood", "Collapse", "Traffic Accident", "National Infrastructure Paralysis", and "Fire⋅Explosion" occur the most in conjunction with other disasters in a complex manner. It has been observed that the types of disasters co-ocuuring with others have become more diverse over time. Parcicularly, in recent 10 years (2011-2020), in addition to the aforementioned five types, "Heat Wave", "Heavy Snowfall⋅Cold Wave", "Earthquake", "Chemical Accident", "Infectious Disease", "Forest Fire", "Air Pollution", "Drought", and "Landslide" have been notable for their frequent co-occurrence with other disasters. These findings through the statistical analysis of the complex disasters using long-term news data are expected to serve as crucial data for future policy development and research on complex disaster management.

• Journal of Korea Water Resources Association
• /
• v.52 no.12
• /
• pp.1001-1009
• /
• 2019

Due to recent increasing heavy snow in Korea, the damage caused by heavy snow is also increasing. In Korea, there are many efforts including establishing disaster prevention measures to reduce the damage throughout the country, but it is difficult to establish the design criteria due to the characteristics of heavy snow. In this study, snowfall frequency analysis was performed to estimate design snow depths using observed snow depth data at Jinju, Changwon and Hapcheon stations. The conventional frequency analysis is sometime limted to apply to the snow depth data containing zero values which produce unrealistc estimates of distributon parameters. To overcome this problem, this study employed mixed distributions based on Lognormal, Generalized Pareto (GP), Generalized Extreme Value (GEV), Gamma, Gumbel and Weibull distribution. The results show that the mixed distributions produced smaller design snow depths than single distributions, which indicated that the mixed distributions are applicable and practical to estimate design snow depths.