• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.2
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• pp.1-10
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• 2009

Recently the large scale of forest disaster such as landslide and forest fire gives a very bad impact on not only forest ecosystem but also farm business so that it has became the main issue of environmental problems. In this study, the landslide hazard area forecast method was developed by considering not only the topographic thematic maps based on GIS and satellite images but also amount of rainfall data, which are very important factors of landslide. Uljin-gun was selected as the study area and the GIS weight score and overlay analysis were applied to topographical map and meteorological observation map. Finally the landslide area distribution map was constructed by considering the evaluation criteria. Also, the accuracy could be acquired by comparing the landslide hazard area forecast map and real damaged area extracted from satellite image.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.125-136
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• 2024

This study presents an automated Python algorithm for analyzing rainfall characteristics to establish critical rainfall thresholds as part of a landslide early warning system. Rainfall data were sourced from the Korea Meteorological Administration's Automatic Weather System (AWS) and the Korea Forest Service's Automatic Mountain Observation System (AMOS), while landslide data from 2020 to 2023 were gathered via the Life Safety Map. The algorithm involves three main steps: 1) processing rainfall data to correct inconsistencies and fill data gaps, 2) identifying the nearest observation station to each landslide location, and 3) conducting statistical analysis of rainfall characteristics. The analysis utilized power law and nonlinear regression, yielding an average R² of 0.45 for the relationships between rainfall intensity-duration, effective rainfall-duration, antecedent rainfall-duration, and maximum hourly rainfall-duration. The critical thresholds identified were 0.9-1.4 mm/hr for rainfall intensity, 68.5-132.5 mm for effective rainfall, 81.6-151.1 mm for antecedent rainfall, and 17.5-26.5 mm for maximum hourly rainfall. Validation using AUC-ROC analysis showed a low AUC value of 0.5, highlighting the limitations of using rainfall data alone to predict landslides. Additionally, the algorithm's speed performance evaluation revealed a total processing time of 30 minutes, further emphasizing the limitations of relying solely on rainfall data for disaster prediction. However, to mitigate loss of life and property damage due to disasters, it is crucial to establish criteria using quantitative and easily interpretable methods. Thus, the algorithm developed in this study is expected to contribute to reducing damage by providing a quantitative evaluation of critical rainfall thresholds that trigger landslides.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.743-754
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• 2023

The global occurrence of myriad natural disasters and incidents, catalyzed by climate change and extreme meteorological conditions, has engendered substantial human and material losses. International organizations such as the International Charter have established an enduring collaborative framework for real-time coordination to provide high-resolution satellite imagery and geospatial information. These resources are instrumental in the management of large-scale disaster scenarios and the expeditious execution of recovery operations. At the national level, the operational deployment of advanced National Earth Observation Satellites, controlled by National Geographic Information Institute, has not only catalyzed the advancement of geospatial data but has also contributed to the provisioning of damage analysis data for significant domestic and international disaster events. This special edition of the National Disaster Management Research Institute delineates the contemporary landscape of major disaster incidents in the year 2023 and elucidates the strategic blueprint of the government's national disaster safety system reform. Additionally, it encapsulates the most recent research accomplishments in the domains of artificial satellite systems, information and communication technology, and spatial information utilization, which are paramount in the institution's disaster situation management and analysis efforts. Furthermore, the publication encompasses the most recent research findings relevant to data collection, processing, and analysis pertaining to disaster cause and damage extent. These findings are especially pertinent to the institute's on-site investigation initiatives and are informed by cutting-edge technologies, including drone-based mapping and LiDAR observation, as evidenced by a case study involving the 2023 landslide damage resulting from concentrated heavy rainfall.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1479-1488
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• 2018

On September 3rd 2017, strong artificial seismic signals from North Korea were detected in KMA (Korea Meteorological Administration) seismic network. The location of the epicenter was estimated to be Punggye-ri nuclear test site and it was the most powerful to date. The event was not studied well due to accessibility and geodetic measurements. Therefore, we used remote sensing data to analyze surface changes around Mt. Mantap area. First of all, we tried to detect surface deformation using InSAR method with Advanced Land Observation Satellite-2 (ALOS-2). Even though ALOS-2 data used L-band long wavelength, it was not working well for this particular case because of decorrelation on interferogram. The main reason would be large deformation near the Mt. Mantap area. To overcome this limitation of decorrelation, we applied offset tracking method to measure deformation. However, this method is affected by window kernel size. So we applied various window sizes from 32 to 224 in 16 steps. We could retrieve 2D surface deformation of about 3 m in maximum in the west side of Mt. Mantap. Second, we used Pleiadas-A/B high resolution satellite optical images which were acquired before and after the 6th nuclear test. We detected widespread surface damage around the top of Mt. Mantap such as landslide and suspected collapse area. This phenomenon may be caused by a very strong underground nuclear explosion test. High-resolution satellite images could be used to analyze non-accessible area.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.889-900
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• 2017

In this study, we analyzed the paper about NIR (Near-Infrared) remote sensing data and systematically summarized the research and application fields of NIR. To do this, we conducted a case study on the use of NIR in domestic journals, and SCI journals in the field of technology development for the last 5 years. After selection, a total of 281 journals were analyzed. For the statistical analysis, the classification was divided into subclasses and the dominant research trends were examined. As a result, the researchers who wrote the papers made the highest score of about 60% or more at university. In the field of application, 50% of land, 30% of environment, and 11% of disaster were distributed on SCI journals. In Korea, on the other hand, 55% of land, 24% of environment and 10% of disasters were distributed. In addition, 17% of the national land management and 8% of the geological / natural resources. Disaster observation using NIR was used for landslide, drought, weather disaster and flood. In particular, meteorological disasters are a result of study on Asian dust. However, there were no results of forest fire detection in Korea. Considering the domestic situation, it seems necessary to carry out additional and active research on this. It is expected that this statistical analysis data will be used as basic data to help expand the NIR technology development and utilization field in Korea in the future.

• The Journal of Engineering Geology
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• v.3 no.3
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• pp.279-293
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• 1993

In recent yeaes, the collapses of man made structures have been encountered from time to time due to the deformation of the ground in korea. Furthermore, the possibilities of casasters from the ground deformation suCh as landslide and active fault are atrracting our attention to the deformation monitoring. In this study, two-coordinate tilt which was monitored during six months in order to develop tediniques for prevention of disasters from the ground deformation. The two-coordinate tilt which was detected by a tilt-sensor installed in shallow depth on the slope with the sensitivity of 0.0001 arc.sec in every 10 minutes was recorded continously to PC through the interface with 200-m line coonection. The observed digital tilt data. together with the relevant meteorological data were analyzed in reference to engineering application. During the whole observation period of six months, the net tilt is 10.06 arc.sec to the west and 73.88 arc.sec to the south. Consequently the ground has a tilt of 74.56 arc.sec to the direction of $S7.75^{\circ}W$ with average tilting of 0.02 arc.sec/hour. In spite of such fast and large tilting, it is interpreted in view of engineering aspects that the site is much safe from danger, since both East-West and North-South components of tilt converge as time goes by. Two categories of deformational events are recognized ; one is toward the direction of surface slope and the other is to the direction of increased pore pressure. Tiks are acenain to have a close relation with precipitation of rain. The daily variation of two-coordinate tilt is delayed 4.3 hours in average after the variation of atmospheric temperature. A certain correlation between atmospheric pressure and deformation might be revealed.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.715-727
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• 2023

To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.