• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.145-157
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• 2018

Mountainous areas are 64% in Korea and are allowed to be used by the permission standards of the "Mountainous Districts Management Act". In the act, slope and elevation criteria are defined to regulate the use of vulnerable land parcels to disaster. However, the standards cannot represent topographical variation in a land parcel such as terrain relief. Therefore, the applicability of slope type standard as a permission standard was tested using Catena in this study. Based on the theoretical grounds, two slope types were analyzed as 'risky slope' with disaster risk. The slope types of landslides in Namwon City were analyzed that 'risky slope' types were distributed about 57%. This study analyzed the forestland parcels that could be used when applying the current permission standards and the parcels that were already used in Namwon City. The ratio of the 'risky slope' in the parcels was more than 50%. Therefore, it is necessary to prevent the mountain development in 'risky slope' by establishing permission standard related to slope types. In addition, this study suggested the ratio of 'risky slope' in the parcel for the permission standard for forestland use conversion.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1209-1220
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• 2020

In the case of forest areas, the installation of ground control points (GCPs) and the selection of terrain features, which are one of the unmanned aerial photogrammetry work process, are limited compared to urban areas, and safety problems arise due to non-visible flight due to high forest. To compensate for this problem, the drone equipped with a real time kinematic (RTK) sensor that corrects the position of the drone in real time, and a 3D flight method that fly based on terrain information are being developed. This study suggests to present a method for investigating damage using drones in forest areas. Position accuracy evaluation was performed for three methods: 1) drone mapping through GCP measurement (normal mapping), 2) drone mapping based on topographic data (3D flight mapping), 3) drone mapping using RTK drone (RTK mapping), and all showed an accuracy within 2 cm in the horizontal and within 13 cm in the vertical position. After evaluating the position accuracy, the volume of the landslide area was calculated and the volume values were compared, and all showed similar values. Through this study, the possibility of utilizing 3D flight mapping and RTK mapping in forest areas was confirmed. In the future, it is expected that more effective damage investigations can be conducted if the three methods are appropriately used according to the conditions of area of the disaster.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.43-50
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• 2021

In Korea, the frequency of soil disasters has soared recently due to increased torrential rains caused by abnormal weather conditions. In particular, soil generated from mountainous areas is flowing into small rivers along valleys, depositing rivers and adding to flood damage. In order to prevent damage from such soil disasters, it is important to predict sediments and to quantitatively identify bed load. In this work, we conducted an experiment to indirectly measure acoustic sensor-based bed load collision sounds using pipe hydrophones, and compared them with raw data by applying denoising methods to improve the reliability of the measured data. As a result, we derive results in a more clear analysis of bed load estimation by correcting noise when the denoising method is applied to raw data.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.9-15
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• 2021

The frequency of flash floods in mountainous areas is increasing due to the abnormal weather that occurs increasingly in the recent, and it causes human and material damages is increasing. Various plans for disaster mitigation have been established, but artificial plans such as raising embankment and dredging operation are inappropriate for valleys and rivers in national parks that prioritize nature protection. In this study, flood risk assessment was conducted for Gyeryongsan National Park in Korea using the WMS (Watershed Modeling System)which is rainfall runoff model for valleys and rivers in the catchment. As the result, it was simulated that it is flooding in three sub-catchments (Jusukgol, Sutonggol, Dinghaksa) of a total in Gyeryongsan National Park when rainfall over the 50 years return period occurs, and it was confirmed that the risk of trails and facilities what visitors are using was high. The risk of trails in national parks was quantitatively presented through the results of this study, and we intend to present the safe management guidelines of national parks in the future.

• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.440-446
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• 2020

The application field of smart terminals is increasing and its application is also spreading in the defense field. The use of smart terminal based map application is very important in battle fields. The problem is that the communication infrastructure is easy to collapse and the use of GPS is usually disturbed. In this paper, we studied the maps stored in the QR tag at the battle field. The problem is to abstract the map information so that it can be stored in the small QR tag. We have abstracted path information on a vector basis and require only a small amount of data compared to imaged path information. We analyzed the amount of data generated by the abstraction and mathematically analyzed the boundary where the amount does not exceed the capacity limit of the QR tag. Our research can be applied not only to battlefields, but also to disaster / disaster scenes, or in environments with difficult Internet communications, such as mountainous areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.10 no.2
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• pp.57-62
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• 1992

As population is increased, land use types are changed mountainous areas from flatland in Korea. Because natural disaster as landslides occur of life, property, and environmental damage, prediction of landslides have become increasingly important. We focus on the issue for assessment of landslides, not slope stability analysis for a simple slope site. In this study, we could know the correlations of mean, standard deviation for brightness value of imagery by aerial photo scanning. The range of brightness values and standard deviation of landslide area is 35~65 and tend to increment of value, in the every years. When evaluating large regions with past occurrence of landslides, it is possible to search for correlation of site conditions such as degree of slope, soil characteristics, vegetative cover, and rainfall conditions in aerial photo interpretation data.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.214-214
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• 2015

Rainfall induced landslides is one of the most devastating natural disasters acting on mountainous areas. In Korea, landslide damage areas increase significantly from 1990s to 2000s due to the increase of both rainfall intensity and rainy days in addition with haphazard land development. This study was carried out based on the application of TRIGRS unsaturated (Transient Rainfall Infiltration and Grid-based Regional Slope stability analysis), a Fortran coded, physically based, and numerical model that can predict landslides for areas where are prone to shallow precipitation. Using TRIGRS combining with the geographic information system (GIS) framework, the landslide incident happened on 27th, July 2011 in Mt. Umyeon in Seoul was modeled. The predicted results which were raster maps showed values of the factors of safety on every pixel at different time steps show a strong agreement with to the observed actual landslide scars in both time and locations. Although some limitations of the program are still needed to be further improved, some soil data as well as landslide information are lack; TRIGRS is proved to be a powerful tool for shallow landslide susceptibility zonation especially in great areas where the input geotechnical and hydraulic data for simulation is not fully available.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.1
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• pp.17-25
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• 2013

In this paper we interpreted the changes in wind field over complex mountainous terrains. The results of our study can be applied for predicting the direction of fire spread and for establishing strategies for fire prevention. The study area is bounded by $12{\times}12$ km domains of the Samcheok's long-term ecological research (LTER) site located in the east coast, in which a large-fire had occurred from 7 to 13 April 2000. Because of the area's complex topography, we compared the result of the Weather Research and Forecasting (WRF) mesoscale model with those observed by four automated weather stations. The WRF simulation overestimated the wind speed by 5 to 8 m/s (~200%) in comparison with those from four automated weather stations. The wind directions observed by the AWSs were from various directions whereas those from WRF model were mostly west wind at all stations. Overall, the simulations by the WRF mesoscale models were not appropriate for the estimation of microscale wind fields over complex mountainous areas. To overcome such inadequacy of reproducing the wind fields, we employed the ENVI-met model over Samcheok's LTER site. In order to test the model's sensitivity with the terrain effects, experimental simulations were conducted with various initial conditions. The simulation results of the ENVI-met model showed a reasonable agreement in wind speeds (about 70% accuracy) with those of the four AWSs. Also, that the variations in wind directions agreed reasonably well with changes in terrain effect. We concluded that the ENVI-met model is more appropriate in representing the microscale wind field over complex mountain terrains, which is required to predict fire spread and to establish strategies for forest fire prevention.

• Journal of the Korean association of regional geographers
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• v.13 no.4
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• pp.396-408
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• 2007

Natural disasters occurred in Inje and Pyeongchang in 2006 show that unusual changes of weather, which Korean Peninsula has not experienced before, are becoming quite common phenomenon nowadays. In future we have to proceed in the direction of preventing such disasters so as to minimize the damage, by analyzing character and cause of various disasters whenever necessary, performing modeling in simulated real world, and applying the results in disaster prevention policy next year. Applying GIS in this process, the best information for decision-making can be offered. This study has also progressed proceeding from such point of view. The results of this study show that local concentrated heavy rain, caused by the primary topographical factor in the Sulak mountain region, was the main cause of flood disaster occurred in Inje-Gun area in July of 2006. Local concentrated heavy rain is greatly affected by topography. Namely, if there is a mountainous region behind, the area opposite to the direction of rain clouds motion will have high possibility of local concentrated heavy rain.