• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.17 no.4
• /
• pp.339-348
• /
• 1999

The information & Communication industry including internet is rapidly developing and expanding, which integrates our living space and provides diversity. Internet provides users with an variety of real-time information through networking. Also the functions and services of Geographic Information Systems are on a changing trend providing services for various organizations and users dispersed in different networks. It is necessary to understand that GIS is available not only on a desktop and server, but in any place where the network is connected using the web. Recently, Internet GIS for the search and subscription of spatial informations through the internet is receiving an active research field. So. this study aims to apply the Gas Disaster Management to the internet and develop the internet GIS techniques which make an effective utilization of GIS functions using MapObjects IMS, SDE, and Oracle.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2010.04a
• /
• pp.363-365
• /
• 2010

In this study, based on numerical map GIS-T Dataset build and by using ArcGIS Network Analysis emergency vehicle's reach time were analyzed. AutoCad using 1: 50,000 based on roads and hospitals of numerical map were creating a Polyline and Point and Network Dataset made using ArcCatalog. ArcGIS Analysis setting the interval for the period reached 3 minutes, 5 minutes, 15 minutes was set and then U-Turn was set to not allow because U-turn takes a long time to calculate and does not happen often on the real road. Intersection of the passage of time, considering that the emergency vehicles were set to 3 seconds. To expand by taking advantage of this facility on Vulnerable area will be used as base material. If we focus on analyzing the emergency activity to convert little data, To prepare for disaster and disaster will be able to use the materials.

• Journal of Korea Water Resources Association
• /
• v.35 no.4 s.129
• /
• pp.453-461
• /
• 2002

The run-up process of the 1983 Central East Sea Tsunami along the Eastern Coast is numerically investigated in this study. A finite difference numerical model based on the nonlinear shallow-water equations is employed. The maximum run-up height at Imwon is predicted and compared to field observation. A good agreement is observed. A maximum inundation map is made based on the maximum run-up heights to accentuate hazards of tsunami flooding.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.3
• /
• pp.126-135
• /
• 2011

In this study, the algorithm for priority area of forest fire surveillance was developed to enhance the effectiveness of fire detection. The high priority surveillance area for forest fire detection was defined as the area with not only low value of viewshed analysis of the lookouts and detection cameras but also high fire occurrence probability. To build the priority map, fuzzy function and map algebra were used. The analysis results of Bonghwa-gun, Gyeongbuk Province, showed that the surveillance priority of central and southern area is higher than north area. This algorithm could be used in the allocation of fire prevention resources and selection of suitable point for new fire detection system.

• Journal of Korea Spatial Information System Society
• /
• v.3 no.1 s.5
• /
• pp.27-36
• /
• 2001

The 4S represents four systems that are commonly related to spatial information: GIS, GNSS, SIIS, ITS. The 4S technology that integrates the four systems gets more and more interests recently. In this paper, we adopt component paradigm to 4S system, apply it to the disaster control field, and design a system based on component architecture. There are many application areas to which the 4S technology can be applied. but the disaster control system is one of the most typical fields. We apply 4S technology to the disaster control fields, including fire, flood, and typhoon. Because of the characteristics of disaster control system that handles large-volume map data, component-based 4S system will take considerable effects on the improvement of disaster control works. The core functions that are common to all disaster control fields are included in 4S kernel component because of the consideration of time performance. Remaining non-common functions are implemented as separate components named as work-specific components. In our suggested system, a vehicle named as 4S-Van collects real-time information on the spot of disaster and sends image and location information to control center via wireless transmission. The control center analyzes the information together with its own spatial database or map, which was not possible in the conventional disaster control works. The control center can get desired information by sending a request of re-transmission to 4S-Van. Such method of real-time transmission supported by on-the-spot information makes the current situation judgment, decision making, and order issuance more exact, effective, and timely. The suggested system and method are expected to bring remarkable improvement on disaster control works.

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

• 한국방재학회:학술대회논문집
• /
• 2008.02a
• /
• pp.775-778
• /
• 2008

In general, forecast tsunami heights announced for tsunami warning are computed by using a linear tsunami model with coarse grids which leads the underestimation of inundation area. Thus, an accurate tsunami inundation map corresponding to the forecast tsunami height is indispensible for an emergency evacuation plan. A practical way to construct a relatively accurate tsunami inundation map was proposed in this study for the quantitative forecast of inundation area. This procedure can be introduced as in the followings: The fault dislocations of potential tsunami sources generating a specific tsunami height near an interested area are found by using a linear tsunami model. Based on these fault dislocations, maximum inundation envelops of the interested area are computed and illustrated by using nonlinear inundation numerical model. In this study, the tsunami inundation map for Imwon area was constructed according to 11 potential tsunami sources, and the validity of this process was examined.

• Journal of the Society of Disaster Information
• /
• v.19 no.2
• /
• pp.334-343
• /
• 2023

Purpose: In this study, the cavity data found through ground cavity exploration was combined with underground facilities to derive a correlation, and the ground subsidence prediction map was verified based on the AI algorithm. Method: The study was conducted in three stages. The stage of data investigation and big data collection related to risk assessment. Data pre-processing steps for AI analysis. And it is the step of verifying the ground subsidence risk prediction map using the AI algorithm. Result: By analyzing the ground subsidence risk prediction map prepared, it was possible to confirm the distribution of risk grades in three stages of emergency, priority, and general for Busanjin-gu and Saha-gu. In addition, by arranging the predicted ground subsidence risk ratings for each section of the road route, it was confirmed that 3 out of 61 sections in Busanjin-gu and 7 out of 68 sections in Sahagu included roads with emergency ratings. Conclusion: Based on the verified ground subsidence risk prediction map, it is possible to provide citizens with a safe road environment by setting the exploration section according to the risk level and conducting investigation.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.321-324
• /
• 2007

It is commonly believed that a gigantic earthquake (Tokai Earthquake) could occur in Shizuoka Prefecture in the near future. The Shizuoka Prefecture Government made the prediction report of Tokai Earthquake disaster damage. But this report does not pay attention to the ground conditions. The authors make a prediction map using GIS of Tokai Earthquake disaster damage in Asada-cho and Hirosawa Ni-chome in the central Hamamatsu City and revealed the location of dangerous houses and dangerous points in road networks in each town. These information could be useful when people try to find escape routes in an earthquake.

• Korean Journal of Remote Sensing
• /
• v.17 no.2
• /
• pp.121-129
• /
• 2001

A DEM(digital elevation model) is generated from a SPOT panchromatic stereo-pair using automated algorithms over a 8 km$\times$10 km region around Mokpo city. The aims are to continue the accuracy assessment over diverse conditions and to examine the applicability of a SPOT DEM for coastal disaster monitoring. The accuracy is assessed with respect to three reference data sets: 10 global positioning system records, 19 leveling data, and 1:50,000 topography map. The planimetric error is 10.6m r.m.s. and the elevation erroer ranges from 12.4m to 14.4m r.m.s.. The DEM accuracy of the flat Mokpo region is consistent with that over a mountainous area, which supports the robustness of the algorithms. It was found that coordinate transformation errors are significant at a few meters when using the data from leveling and topographic maps. The error budget is greater than the requirements for coastal disaster monitoring. Exploiting that a sub-scene is used, the affine transformation improves the accuracy by 50% during the camera modeling.