• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.13-21
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• 2007

Recently, very short-term rainfall forecast using radar is required for regional flash flood according to climate change. This research is to evaluate the feasibility of GIS based distributed model using radar rainfall which can express temporal and spatial distribution in actual dam watershed during flood runoff period. Vflo model which was developed Oklahoma university was used as physical based distributed model, and Namgang dam watershed ($2,293km^2$) was applied as study site. Distributed rainfall according to grid resolution was generated by using K-RainVieux, preprocess program of radar rainfall, from JIN radar. Also, GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of distributed model(Vflo). Results of this research can provide a base for building of real-time short-term rainfall runoff forecast system according to flash flood in near future.

• Economic and Environmental Geology
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• v.28 no.4
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• pp.395-404
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• 1995

The geologic structure of the Cheju volcanic island has been investigated by analyzing the gravity and magnetic data. Bouguer gravity map shows apparent circular low anomalies at the central volacanic edifice, and the maximum difference of the anomaly values on the island appears to be 30 mgal. The subsurface structure of the island is modeled by three-dimensional depth inversion of gravity data by assuming the model consists of a stacked grid of rectangular prisms of volcanic rocks bounded below by basement rocks. The gravity modeling reveals that the interface between upper volvanic rocks and underlying basement warps downward under Mt. Halla with the maximum depth of 5 km. Magnetic data involve aeromagnetic and surface magnetic survey data. Both magnetic anomaly maps show characteristic features which resemble the typical pattern of total magnetic anomalies caused by a magnetic body magnetized in the direction of the geomagnetic field in the middle latitude region, though details of two maps are somewhat different. The reduced-to-pole magnetic anomaly maps reveal that main magnetic sources in the island are rift zones and the Halla volcanic edifice. The apparent magnetic boundaries inferred by the method of Cordell and Grauch (1985) are relatively well matched with known geologic boundaries such as that of Pyosunri basalt and Sihungri basalt which form the latest erupted masses. Inversion of aeromagnetic data was conducted with two variables: depth and susceptibility. The inversion results show high susceptibility bodies in rift zones along the long axis of the island, and at the central volcano. Depths to the basement are 1.5~3 km under the major axis, 1~1.5 km under the lava plateau and culminates at about 5 km under Mt. Halla. The prominent anomalies showing N-S trending appear in the eastern part of both gravity and magnetic maps. It is speculated that this trend may be associated with an undefined fault developed across the rift zones.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.1
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• pp.23-32
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• 2008

According to recent frequent local flash flood due to climate change, the very short-term rainfall forecast using remotely sensed rainfall like radar is necessary to establish. This research is to evaluate the feasibility of GIS-based distributed model coupled with radar rainfall, which can express temporal and spatial distribution, for multipurpose dam operation during flood season. $Vflo^{TM}$ model was used as physically based distributed hydrologic model. The study area was Yongdam dam basin ($930\;km^2$) and the 3 storm events of local convective rainfall in August 2005, and the typhoon.Ewiniar.and.Bilis.collected from Jindo radar was adopted for runoff simulation. Distributed rainfall consistent with hydrologic model grid resolution was generated by using K-RainVieux, pre-processor program for radar rainfall. The local bias correction for original radar rainfall shows reasonable results of which the percent error from the gauge observation is less than 2% and the bias value is $0.886{\sim}0.908$. The parameters for the $Vflo^{TM}$ were estimated from basic GIS data such as DEM, land cover and soil map. As a result of the 3 events of multiple peak hydrographs, the bias of total accumulated runoff and peak flow is less than 20%, which can provide a reasonable base for building operational real-time short-term rainfall-runoff forecast system.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.577-584
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• 2021

Electrical energy is an essential component in present societies, which is an important basis for our technological society. In the design of new power infrastructure, it is important to consider the psychological aspects of how our culture considers and aspects its development as an integral component of the community environment. The construction of new high voltage overhead transmission lines has become a controversial issue for public policy of government due to social opposition. The members of community are concerned about how these power lines may have an impact on their lives, basically caused by their effects on health and safety. The landscape and visual impact is one of the most impact that can be easily perceived for local community. The computer 3D simulation of new landscape is illustrated by a real life use corresponding to the selection of the power line route with least observability for local community. This paper used ArcGIS(geographic information system tool) for planning, survey, basic route and detailed route, route for implementation of transmission line corridor. Also, the paper showed the map of natural environment, living environment, safety and altitude using database of power line corridor, and transmission siting model was developed by this study. The suggested landscape of computer simulation with lowest visibility on a power line zone can contribute to reducing oppositions of local community and accelerating the construction of new power lines.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Korean Journal of Heritage: History & Science
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• v.43 no.3
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• pp.306-333
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• 2010

Previous studies on Wolseong fortress have focused on capital system of Silla Dynasty and on the recreation of Wolseong fortress due to the excavations in and around Wolseong moat. Since the report on the Geographical Survey of Wolseong fortress was published and GPR survey in Wolseong fortress was executed as a trial test in 2004, the academic interest in the site has now expanded to the inside of the fortress. From such context, the preliminary research on the fortress including geophysical survey had been commenced. GPR survey had been conducted for a year from March, 2007. The principal purpose of the recent 3D GPR survey was to provide visualization of subsurface images of the entire Wolseong fortress area. In order to obtain 3D GPR data, dense profile lines were laid in grid-form. The total area surveyed was $112,535m^2$. Depth slice was applied to analyse each level to examine how the layers of the remains had changed and overlapped over time. In addition, slice overlay analysis methodology was used to gather reflects of each depth on a single map. Isolated surface visualization, which is one of 3D analysis methods, was also employed to gain more in-depth understanding and more accurate interpretations of the remain The GPR survey has confirmed that there are building sites whose archaeological features can be classified into 14 different groups. Three interesting areas with huge public building arrangement have been found in Zone 2 in the far west, Zone 9 in the middle, and Zone 14 in the far east. It is recognized that such areas must had been used for important public functions. This research has displayed that 3D GPR survey can be effective for a vast area of archaeological remains and that slice overlay images can provide clearer image with high contrast for objects and remains buried the site.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.1-9
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• 2006

Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.