• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.591-597
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• 2014

A wide variety of image application methods, such as aerial image, terrestrial image, terrestrial laser, and stereo image point are currently under investigation to develop three-dimensional 3D geospatial information. In this study, matching points, which are needed to build a 3D model, were examined under diverse weather conditions by analyzing the stereo images recorded by closed circuit television (CCTV) cameras installed in the U-City. The tests on illuminance and precipitation conditions showed that the changes in the number of matching points were very sensitively correlated with the changes in the illuminance levels. Based on the performances of the CCTV cameras used in the test, this study was able to identify the optimal values of the shutter speed and iris. As a result, compared to an automatic control mode, improved matching points may be obtained for images filmed using the data obtained through this test in relation to different weather and illuminance conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.133-146
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• 2021

Providing weather information on roads today means that the road weather conditions near weather observation points are presented to road managers and road users. These weather observation points are managed by the Korea Meteorological Administration. However, it is difficult to provide accurate weather information due to physical limitations such as the presence of precipitation collection points, distance to weather information provision roads, and the presence of mountains. Therefore, this study intends to perform a comparative analysis by time zone and administrative dong provided by the Meteorological Administration using the wiper information among the information contained in the PVD(Probe Vehicle Data) collected from the highway C-ITS project. As a result of the analysis it was possible to detect rainfall even in the event of local rainfall and rainfall over a long period of time and the higher the cumulative precipitation per hour, the higher the probability of coincidence. This study is meaningful because it used PVD to solve the limitations of the existing road weather information provision method and suggested utilization plan for PVD.

• The KIPS Transactions:PartC
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• v.15C no.2
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• pp.93-102
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• 2008

The network weather map and bandwidth time-series graph are popularly used to understand the current and past traffic condition of NSP, ISP, and enterprise networks. These systems collect traffic performance data from a SNMP agent running on the network devices such as routers and switches, store the gathered information into a DB, and display the network performance status in the form of a time-series graph or a network weather map using Web user interface. Most of current enterprise networks are constructed in the form of a hierarchical tree-like structure with multi-Gbps Ethernet links, which is quietly different from the national or world-wide backbone network structure. This paper focuses on the network weather map for current enterprise network. We start with the considering points in developing a network weather map system suitable for enterprise network. Based on these considerings, this paper proposes the best way of using SNMP in constructing a network weather map system. To prove our idea, we designed and developed a network weather map system for our campus network, which is also described in detail.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.225-232
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• 2023

Owing to advancements in intelligent transportation systems (ITS) and artificial-intelligence technologies, various machine-learning models can be employed to simulate and predict the number of traffic accidents under different weather conditions. Furthermore, we can analyze the relationship between weather and traffic accidents, allowing us to assess whether the current weather conditions are suitable for travel, which can significantly reduce the risk of traffic accidents. In this study, we analyzed 30000 traffic flow data points collected by traffic cameras at nearby intersections in Washington, D.C., USA from October 2012 to May 2017, using Pearson's heat map. We then predicted, analyzed, and compared the performance of the correlation between continuous features by applying several machine-learning algorithms commonly used in ITS, including random forest, decision tree, gradient-boosting regression, and support vector regression. The experimental results indicated that the gradient-boosting regression machine-learning model had the best performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.132-132
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• 2021

Access to accurate spatial precipitation in many hydrological studies is necessary. Existence of many mountains with diverse topography in South Korea causes different spatial distribution of precipitation. Rain gauge stations show accurate precipitation information in points, but due to the limited use of rain gauge stations and the difficulty of accessing them, there is not enough accurate information in the whole area. Weather radars can provide an integrated precipitation information spatially. Despite this, weather radar data have some errors that can not provide accurate data, especially in heavy rainfall. In this study, some location-based variable like aspect, elevation, plan curvature, profile curvature, slope and distance from the sea which has most effect on rainfall was considered. Then Automatic Weather Station data was used for spatial training of variables in each event. According to this, K-fold cross-validation method was combined with Adaptive Neuro-Fuzzy Inference System. Based on this, 80% of Automatic Weather Station data was used for training and validation of model and 20% was used for testing and evaluation of model. Finally, spatial distribution of precipitation for 1×1 km resolution in Gwangdeoksan radar station was estimates. The results showed a significant decrease in RMSE and an increase in correlation with the observed amount of precipitation.

• Journal of Environmental Science International
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• v.31 no.4
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• pp.329-339
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• 2022

Better understanding the mechanism of black ice occurrence on the road in winter is necessary to reduce the socio-economic damage it causes. In this study, intensive observations of road weather elements and surface information under the influence of synoptic high-pressure patterns (22^nd December, 2020 and 29^th January, and 25^th February, 2021) were carried out using a mobile observation vehicle. We found that temperature and road surface temperature change is significantly influenced by observation time, altitude and structure of the road, surrounding terrain, and traffic volume, especially in tunnels and bridges. In addition, even if the spatial distribution of temperature and road surface temperature for the entire observation route is similar, there is a difference between air and road surface temperatures due to the influence of current weather conditions. The observed road temperature, air temperature and air pressure in Nongong Bridge were significantly different to other fixed road weather observation points.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.531-541
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• 2018

Road freezing caused by snowfall during wintertime causes traffic congestion and many accidents. To prevent such problems, we developed, in this study, a system to predict road freezing based on weather forecast data and the freezing generation modules. The weather forecast data were obtained from a high-resolution model with 1 km resolution for Jeju Island from 00:00 KST on December 1, 2017, to 23:00 KST on February 28, 2018. The results of the weather forecast data show that index of agreement (IOA) temperature was higher than 0.85 at all points, and that for wind speed was higher than 0.7 except in Seogwipo city. In order to evaluate the results of the freezing predictions, we used model evaluation metrics obtained from a confusion matrix. These metrics revealed that, the Imacho module showed good performance in precision and accuracy and that the Karlsson module showed good performance in specificity and FP rate. In particular, Cohen's kappa value was shown to be excellent for both modules, demonstrating that the algorithm is reliable. The superiority of both the modules shows that the new system can prevent traffic problems related to road freezing in the Jeju area during wintertime.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.4
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• pp.44-55
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• 2013

Intelligent transportation systems allow us to have valuable opportunities for collecting reliable wide-area coverage traffic and weather data. Significant efforts have been made in many countries to apply these data. This study identifies the critical points for classifying rain intensity by analyzing the relationship between rainfall and the amount of speed reduction. Then, traffic prediction performance by rain intensity level is evaluated using relative errors. The results show that critical points are 0.4mm/5min and 0.8mm/5min for classifying rain intensity (slight, moderate, and heavy rain). The best prediction performance is observable when previous five-block speed data is used as inputs under normal weather conditions. On the other hand, previous two or three-block speed data is used as inputs under rainy weather conditions. The outcomes of this study support the development of more reliable traffic information for providing advanced traffic information service.

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.575-587
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• 2020

Meteorological phenomena are observed by the Korea Meteorological Administration in a variety of ways (e.g., surface, upper-air, marine, ocean, and aviation). However, there are limits to the meteorological observation of the planetary boundary layer (PBL) that greatly affects human life. In particular, observations using a sonde or aircraft require significant observational costs in economic terms. Therefore, the goal of this study was to measure and analyze the meteorological factors of the vertical distribution of the see-land breeze among local meteorological phenomena using meteorological drones. To investigate the spatial distribution of the see-land breeze, a same integrated meteorological sensor was mounted on each drone at three different points (seaside, bottom of mountain, and mountainside), including the Boseong tall tower (BTT) at the Boseong Standard Weather Observatory (BSWO) in the Boseong region. Vertical profile observations for air temperature, relative humidity, wind direction, wind speed, and air pressure were conducted up to 400 m every 30 minutes from 1100 LST to 1800 LST on August 4, 2018. The spatial characteristics of meteorological phenomena for temperature, relative humidity, and atmospheric pressure were not shown at the four points. Strong winds (~8 m s-1) were observed from the midpoint (~100 m) at strong solar radiation hour, and in the afternoon the wind direction changed from the upper layer at the inland area to the west wind. It is expected that the analysis results of the lower atmospheric layer observed using the meteorological drone may help to improve the weather forecast more accurately.

• Atmosphere
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• v.15 no.1
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• pp.27-34
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• 2005

High quality meteorological information is the typical product of service business industry which can offer the investment initiative by reducing the uncertainty and by activating other related industries. It requires a high level of meteorological technology and of ability to transform such technology as merchandising products. According to the analysis of the WMO data, the level of Korean meteorological technology is comparable to that of the nation with $17,500, GDP per head. However, the income of the meteorological business agent earns in Korea is 8 billion 4 hundred million won which is less than a tenth of that made by the US or Japan. The potential for such business field in Korea will be strong enough, if one can overcome such weak points. In addition, the efforts made by the government to advance the meteorological technology have been actualized gradually. Korean government will have a chance that is comparable to offering jobs for 20,000 unemployed by creating incomes of 40 billion won by meteorological technology as a sustained economic growth engine. It is proposed that government stimulate demand and supply by focusing on sales quantity than the price. The key points for creating the new demand are marketing and outsourcing of weather and climate information by maintaining the cooperative relationship between private and public sector.