• Proceedings of the Korean Society of Agricultural Engineers Conference
• /
• 2005.10a
• /
• pp.156-163
• /
• 2005

This study was attempted to provide some fundamental data for safety structrural design of biological production facility. Wind load and snow load, acting on agricultural structures is working more sensitive than any other load. Therefore, wind speed and snow depth according to return periods for design load estimation were calculated by frequency analysis using the weather data(maximum instantaneous wind speed, maximum wind speed, maximum depth of snow cover and fall) of 68 regions in Korea. Equations for estimating maximum instantaneous wind speed with maximum wind speed were developed for all, inland and seaside regions. The results were about the same as the current eqution in general. Design wind speed and snow depth according to return periods were calculated and Local design wind load and snow load depending on return periods were presented together with iso-wind speed and iso-snow depth maps. The calculated design snow depth by maximum depth of snow cover were higher than design snow depth by maximum depth of snow fall. Considering wind speed and snow depth, protected cultivation is very difficult in Ullungdo, Gangwon seaside and contiguity inland regions, and strong structural design is needed in the west-south seaside against wind speed, and structure design of biological production facility in these regions need special consideration.

• Korean Journal of Remote Sensing
• /
• v.30 no.3
• /
• pp.341-350
• /
• 2014

Landsat images can monitor the snow-covered Earth surface variations with the ground resolution of 30m and the multi-spectral bands in the visible, NIR, SWIR and TIR spectral regions for the last 30 years. The Southern Volcanic Zone (SVZ) of Chile consists of many volcanoes, and all of the volcanoes are covered with snow at the top of mountain. Snow cover area in southern province of the SVZ of Chile (37 to $46^{\circ}S$) have been influenced by significant frontal retreats as well as eruptive activities. In this study, we have investigated the changes of the snow-cover area and snow-line elevation at Mt. Villarrica and Mt. Llaima, Chile from three Landsat images acquired on Feb. 1990, 2005 and 2011. The snow-cover areas are 13.42, 26.75 and $21.60km^2$ at Mt. Villarrica in 1990, 2005 and 2011, respectively, and 3.82, 25.12 and $8.89km^2$ at Mt. Llaima in 1990, 2005 and 2011, respectively. The snow-line elevations are 1871, 1738 and 1826m at Mt. Villarrica in 1990, 2005 and 2011, respectively, and 2007, 1822 and 1818m at Mt. Llaima in 1990, 2005 and 2011, respectively. The results indicate that both of the snow-cover and snow-line changes are strongly related with the volcanic activity change. The results demonstrate that the snow-cover area and snow-line elevation changes can be used as an indicator of the volcanic activity at Mt. Villarrica and Mt. Llaima, Chile.

• Atmosphere
• /
• v.22 no.1
• /
• pp.117-128
• /
• 2012

Does snow depth initialization have a quantitative impact on sub-seasonal to seasonal prediction skill? To answer this question, a snow depth initialization technique for seasonal forecast system has been implemented and the impact of the initialization on the seasonal forecast of surface air temperature during the wintertime is examined. Since the snow depth observation can not be directly used in the model simulation due to the large systematic bias and much smaller model variability, an anomaly rescaling method to the snow depth initialization is applied. Snow depth in the model is initialized by adding a rescaled snow depth observation anomaly to the model snow depth climatology. A suite of seasonal forecast is performed for each year in recent 12 years (1999-2010) with and without the snow depth initialization to evaluate the performance of the developed technique. The results show that the seasonal forecast of surface air temperature over East Asian region sensitively depends on the initial snow depth anomaly over the region. However, the sensitivity shows large differences for different timing of the initialization and forecast lead time. Especially, the snow depth anomaly initialized in the late winter (Mar. 1) is the most effective in modulating the surface air temperature anomaly after one month. The real predictability gained by the snow depth initialization is also examined from the comparison with observation. The gain of the real predictability is generally small except for the forecasting experiment in the early winter (Nov. 1), which shows some skillful forecasts. Implications of these results and future directions for further development are discussed.

• Journal of the Society of Disaster Information
• /
• v.13 no.2
• /
• pp.199-212
• /
• 2017

Rapid roadway snow removal is significantly important due to difficult occurrence estimation of heavy snowfall disasters by global warming and climate change. Local governments of S. Korea have snow removal equipments and vehicles based on past experiences without considering snowfall and roadway characteristics. The objective of this research is to develop the demand estimation procedure for snow removal equipments and vehicles based on regional snowfall and roadway characteristics. This research first classifies regional snowfall characteristics using KMO's ten-year snowfall data. Second, roadway snow removal length is computed for local governments. Real possession data is compared with demand estimation of snow removal equipments & vehicles for each local government with roadway snow removal scenarios. Finally, required demands of snow removal equipments & vehicles are predicted by concerning regional snowfall amount and required snow removal hours. Results from this research are used for developing heavy snowfall disaster management policies for optimal demands and snow removal routes of 229 local governments.

• Journal of Environmental Science International
• /
• v.31 no.10
• /
• pp.815-824
• /
• 2022

It is necessary to understand the amount of snowfall and area of snow cover of Mt. Halla to ensure the safety of mountaineers and to protect the ecosystem of Mt. Halla against climate change. However, there are not enough related studies and observation posts for monitoring snow load. Therefore, to supplement the insufficient data, this study proposes an analysis of snow load and snow cover using normalized-difference snow index. Using the images obtained from the Sentinel2 satellite, the normalized-difference snow index image of Mt. Halla could be acquired. This was examined together with the meteorological data obtained from the existing observatory to analyze the change in snow cover for the years 2020 and 2021. The normalized-difference snow index images showed a smaller snow pixel number in 2021 than that in 2020. This study concluded that 2021 may have been warmer than 2020. In the future, it will be necessary to continuously monitor the amount of snow and the snow-covered area of Mt. Halla using the normalized-difference snow index image analysis method.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_1
• /
• pp.1025-1032
• /
• 2018

Snow Cover is a form of precipitation that is defined by snow on the surface and is the single largest component of the cryosphere that plays an important role in maintaining the energy balance between the earth's surface and the atmosphere. It affects the regulation of the Earth's surface temperature. However, since snow cover is mainly distributed in area where human access is difficult, snow cover detection using satellites is actively performed, and snow cover detection in forest area is an important process as well as distinguishing between cloud and snow. In this study, we applied the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to the geostationary satellites for the snow detection of forest area in existing polar orbit satellites. On the rest of the forest area, the snow cover detection using $R_{1.61{\mu}m}$ anomaly technique and NDSI was performed. As a result of the indirect validation using the snow cover data and the Visible Infrared Imaging Radiometer (VIIRS) snow cover data, the probability of detection (POD) was 99.95 % and the False Alarm Ratio (FAR) was 16.63 %. We also performed qualitative validation using the Himawari-8 Advanced Himawari Imager (AHI) RGB image. The result showed that the areas detected by the VIIRS Snow Cover miss pixel are mixed with the area detected by the research false pixel.

• Archives of design research
• /
• v.18 no.2 s.60
• /
• pp.91-100
• /
• 2005

There is few cultural tourism festival study which investigated snow related sculptures satisfaction from festival visitors and residents. The purposes of this study were to investigate the satisfaction of snow related sculptures based on festival visitors' and residents' evaluation and give directions for festival planners The important results of this study are as following: First, visitors from out of Taebak city satisfied with National Snow Sculpture Contest, International Snow Sculpture Exhibition, and Mysterious International Snow Culture Exhibition. They did not satisfied with Making Snowmen for Genius, Our Family Snow Sculptures, and Winter Riding Experiences. Secondly, residents satisfied with International Snow Sculpture Exhibition, Mysterious International Culture Snow Exhibition, and National Snow Sculpture Contest. Their satisfaction was low about Our Families' Snow Sculptures, and Winter Riding Experiences. Thirdly, introducing experience-oriented programs and facilities are recommended to festival planners for better festival than this year.

• Korean Journal of Remote Sensing
• /
• v.23 no.2
• /
• pp.119-124
• /
• 2007

The few observed data related snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. Remote sensing technology is very effective to observe a wide area. Although many researchers have used remote sensing for snow observation, there were a few discussions on the characteristics of spatial and temporal variation. Snow cover maps were derived from NOAA AVHRR images for the winter seasons from 1997 to 2006. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation stations. Model parameters (Snow Cover Area: SCA, snow depth, Snow cover Depletion Curve: SDC) building for 5 major watersheds in South Korea. Especially SDC is important parameter of snowmelt model.

• Journal of the Society of Disaster Information
• /
• v.20 no.1
• /
• pp.138-146
• /
• 2024

Purpose: The purpose of this study is to find cases of using information and communication technology and smart mobility technology in snow removal vehicles and equipment for rapid and efficient road snow removal in the event of a snowstorm, and to find ways to utilize them. Method: Cases of domestic and overseas snow removal methods are investigated, and snow removal operation methods incorporating new technologies are presented. Result: Most of the operation of snow removal equipment in Korea uses GPS, CCTV, and road traffic information systems, and in the case of overseas, road weather information systems and road snow removal monitoring systems are used. It is expected that snow removal technology using autonomous snow removal vehicles, which are smart mobility, will be developed in the future. Conclusion: The results of this study can contribute to the policy of using snow removal equipment and snow removal vehicles of local governments and related organizations.

• Korean Journal of Remote Sensing
• /
• v.29 no.3
• /
• pp.315-324
• /
• 2013

Spatial information of snow cover and depth distribution is a key component for snowmelt runoff modeling. Wide snow cover areas can be extracted from NOAA AVHRR or Terra MODIS satellite images. In this study eight sets of annual snow cover data (1997-2006) in two mountainous watersheds (A: Chungju-Dam and B: Soyanggang-Dam) were extracted using NOAA AVHRR images. The distribution of snow depth within the Snow Cover Area (SCA) was generated using snowfall data from ground meteorological observation stations. Snow depletion characteristics for the two watersheds were analyzed snow distribution time series data. The decreased pattern of SCA can be expressed as a logarithmic function; the determination coefficients were 0.62 and 0.68 for the A and B watersheds, respectively. The SCA decreased over 70% within 10 days from the time of maximum SCA.