• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.687-698
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• 2022

Purpose: This study was conducted to understand the public awareness of landslide and check dams in 2015-2020 using the big data platform 'Hyean' and to confirm the utilization of this platform in disaster prevention areas. Method: The total amount, number of detection by period by media, and affirmative and negative trends of a search for 'landslide' and 'check dam' in 2015-2020 were analyzed using a keyword search of 'Hyean.' Result: There is significant lack of public awareness of check dam compared to landslide, and the trend is more noticeable in the conspicuous gap of data amount between the news and SNS media. The number and the timing of the search for 'landslide' coincided with the actual occurrence of landslide, while the detection of 'check dam' was less related to it. Relatively affirmative preception for the check dam is inferred, but it was difficult to confirm accurate statistical affirmative and negative trends in the disaster prevention field using 'Hyean.' Conclusion: Unlike the experts who expect positive public awareness of check dam, the statistic results show that the public awareness of the check dam as an effective countermeasure against landslide was extremely low. Active promotion of erosion control projects should be carried out first, and a balanced sample survey should accompany online and periodic field surveys. Since there is a limit to grasping the effective perception in the field of disaster prevention area using 'Hyean', it should be very cautious to establish local/governmental policies using it.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.369-372
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• 2008

Recently, landslides have frequently occurred on natural slopes during periods of intense rainfall. With a rapidly increasing population on or near steep terrain in Korea, landslides have become one of the most significant natural hazards. Thus, it is necessary to protect people from landslides and to minimize the damage of houses, roads and other facilities. To accomplish this goal, many landslide prediction methods have been developed in the world. In this study, a simple landslide prediction system that enables people to escape the endangered area is introduced. The system is focused to debris flows which happen frequently during periods of intense rainfall. The system is based on the wireless sensor network (WSN) that is composed of sensor nodes, gateway, and server system. Sensor nodes comprising a sensing part and a communication part are developed to detect ground movement. Sensing part is designed to measure inclination angle and acceleration accurately, and communication part is deployed with Bluetooth (IEEE 802.15.1) module to transmit the data to the gateway. To verify the feasibility of this landslide prediction system, a series of experimental studies was performed at a small-scale earth slope equipped with an artificial rainfall dropping device. It is found that sensing nodes installed at slope can detect the ground motion when the slope starts to move. It is expected that the landslide prediction system by wireless senor network can provide early warnings when landslides such as debris flow occurs.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.253-265
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• 2020

As the risk of landslide is recently increasing due to the typhoons and localized heavy rains, effective techniques for the landslide damage detection are required to support the establishment of the recovery planning. This study describes the analysis of landslide-damaged areas using ISODATA(Iterative Self-Organizing Data Analysis Technique Algorithm) with Sentinel-2 image, regarding the case of Gokseong in August 7, 2020. A total of 4.75 ha of landslide-damaged areas was detected from the Sentinel-2 image using spectral characteristics of red, NIR(Near Infrared), and SWIR(Shortwave Infrared) bands. We made sure that the satellite remote sensing is an effective method to detect the landslide-damaged areas and support the establishment of the recovery planning, followed by the field surveys that require a lot of manpower and time. Also, this study can be used as a reference for the landslide management for the CAS500-1/2(Compact Advanced Satellite) scheduled to launch in 2021 and the Korean Medium Satellite for Agriculture and Forestry scheduled to launch in 2024.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.5115-5122
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• 2013

This paper has studied about the development and application of landslide collapse prediction real-time monitoring system based on USN to detect and measure the collapse of landslide. The rainfall measuring sensor, gap water pressure sensor, indicator displacement measuring sensor, index inclination sensor, water content sensor and image analysis sensor are selected and these are applied on the test bed. Each sensor's operation and performance for reliability verification is tested by the instrument which is installed in the field. As the result, u-IT based real-time landslide monitoring system which is developed by this research for landslide collapse detection could minimize life and property damages because it makes advance evacuation with collapse risk pre-estimate through real-time monitoring on roadside cut and bedrock slopes. This system is based on the results of this study demonstrate the effect escarpment plan are spread throughout.

• Journal of The Korean Society For Urban Railway
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• v.6 no.4
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• pp.269-278
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• 2018

Railway obstacle detecion system has been introduced with high-speed railway in 2004 to prevent accidents by obstacles such as landslide, rockfall and things fallen from the gauntry over the railway. But existing system has some limitation for landslide or fallen obstacle over railway. Therefore, In this study, we suggest new advanced obstacle detection system introducing the OTDR, optical fiber fences and detection cameras. This system can detect depression degree by the force to the fences and video for the specific region as well as detection wire Off condition. We produce and functional tests for fiber fence and OTDR, which are the core parts of the development system, and results were obtained to demonstrate improved detection capabilities. Several functions also been tested to verify the advanced detection performance and got some satisfactory results. Further we will conduct environment tests and field test.

• Economic and Environmental Geology
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• v.37 no.4
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• pp.425-436
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• 2004

The purpose of this study is to analyze the spatial relationship between the landslides occurred by typhoon, Rusa in 2002 and geospatial dataset. Landslide locations were detected using satellite image and field survey. Topogra-phy, soil, forest, geology and land use data sets were constructed as a spatial database in GIS. From the database, slope, aspect, curvature, water system, type of topography, texture, material, drainage, effective thickness of soil, type, age, diameter, density of wood, lithology, lineament of geology, land use and lineament were used as the land-slide occurrence factors. Using a frequence ratio model, the spatial relationships between the landslides and the factors were extracted. The spatial relationships is helpful to explain the characteristics of the landslide, and to make landslide susceptibility map.

• Smart Media Journal
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• v.12 no.3
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• pp.77-84
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• 2023

Forest fires are representative natural disasters resulting from dramatic global climate change in these modern times. When forest formation is insufficient due to forest damage caused by fire, secondary damages such as landslides occur during the winter thawing period and heavy rains. In most countries, only a limited area is managed as CCTV-centered monitoring systems for forest management. For the landslide prediction, markers containing 3D spatial coordinates were located on the slopes of the danger areas in advance. Then 3D mapping and angle of repose were obtained by periodic drone imaging. The recognition range and angle of view of markers were defined, and a new method for predicting signs of landslides in advance was presented in this study.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.11-19
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• 2010

In recent years, Korea has witnessed an increase to natural disasters such as landslides due to localized sudden and intensive rainfalls. Thus there have been researches on surface displacements to detect and monitor displacements in the areas prone to landslides by using high-precision and density numerical elevation data from LiDAR, which is an advanced 3D measuring equipment. However, the commercial software to process large-capacity LiDAR data, is expensive and difficult to be applied to specialized tasks such as analysis of landslide. In addition, there are no measures for many users to easily access diverse spatial information related to landslides and put it to intuitive uses. Thus this study developed an application program to analyze landslides by processing time series LiDAR data and intuitively serve many users with information about the topography and landslides of given areas. It analyzed the current state of landslides in the subject region through case study and proposed that 3D-based landslide and topography information can be served intuitively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.439-447
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• 2019

In this study, experiments were conducted to establish appropriate measures for slopes with high risk of collapse and to obtain results for minimizing slope collapse damage by detecting the micro-displacement of soil in advance by installing a laser sensor and a vibration sensor in the landslide reduction model experiment. Also, the behavior characteristics of the soil layer due to rainfall and moisture ratio changes such as pore water pressure and moisture were analyzed through a landslide reduction model experiment. The artificial slope was created using granite weathering soil, and the resulting water ratio(water pressure, water) changes were measured at different rainfall conditions of 200mm/hr and 400mm/hr. Laser sensors and vibration sensors were applied to analyze the surface displacement, and the displacement time were compared with each other by video analysis. Experiments have shown that higher rainfall intensity takes shorter time to reach the limit, and increase in the pore water pressure takes shorter time as well. Although the landslide model test does not fully reflect the site conditions, measurements of the time of detection of displacement generation using vibration sensors show that the timing of collapse is faster than the method using laser sensors. If ground displacement measurements using sensors are continuously carried out in preparation for landslides, it is considered highly likely to be utilized as basic data for predicting slope collapse, reducing damage, and activating the measurement industry.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.1-8
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• 2021

In this paper, we propose the construction of an IOT that monitors foresters' physical abnormalities in real time, performs emergency measures, and provides alarms for natural disasters or heatstroke such as a nearby forest fire or landslide. Nodes provided to foresters include 6-axis sensors, temperature sensors, GPS, and LoRa, and transmit the measured data to the network server through the gateway using LoRa communication. The network server uses 6-axis sensor data to determine whether or not a forester has any signs of abnormal body, and performs emergency measures by tracking GPS location. After analyzing the temperature data, it provides an alarm when there is a possibility of heat stroke or when a forest fire or landslide occurs in the vicinity. In this paper, it was confirmed that the real-time detection of physical abnormalities of foresters and the establishment of disaster early warning IOT is possible by analyzing the data obtained by constructing a node and a gateway and constructing a network server.