• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.64-77
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• 2015

An effective method for produce munitions effectiveness data is to calculate weapon effectiveness indices in the US military's Joint Munitions Effectiveness Manuals (JMEM) and take advantage of the damage evaluation model (GFSM) and weapon Effectiveness Evaluation Model (Matrix Evaluator). However, a study about the Range Safety that can be applied in the live firing exercises is very insufficient in the case of ROK military. The Range Safety program is an element of the US Army Safety Program, and is the program responsible for developing policies and guidance to ensure the safe operation of live-fire ranges. The methodology of Weapon Danger Zone (WDZ) program is based on a combination of weapon modeling/simulation data and actual impact data. Also, each WDZ incorporates a probability distribution function which provides the information necessary to perform a quantitative risk assessment to evaluate the relative risk of an identified profile. A study of method to establish for K-Range Safety data is to develop manuals (pamphlet) will be a standard to ensure the effective and safe fire training at the ROK military education and training and environmental conditions. For example, WDZs are generated with the WDZ tool as part of the RMTK (Range Managers Tool Kit) package. The WDZ tool is a Geographic Information System-based application that is available to operational planners and range safety manager of Army and Marine Corps in both desktop and web-based versions. K-Range Safety Program based on US data is reflected in the Korean terrain by operating environments and training doctrine etc, and the range safety data are made. Thus, verification process on modified variables data is required. K-Range Safety rather than being produced by a single program, is an package safety activities and measures through weapon danger zone tool, SRP (The Sustainable Range Program), manuals, doctrine, terrain, climate, military defence M&S, weapon system development/operational test evaluation and analysis to continuously improving range safety zone. Distribution of this K-range safety pamphlet is available to Army users in electronic media only and is intended for the standing army and army reserve. Also publication and distribution to authorized users for marine corps commands are indicated in the table of allowances for publications. Therefore, this study proposes an efficient K-Range Safety Manual producing to calculate the danger zones that can be applied to the ROK military's live fire training by introducing of US Army weapons danger zone program and Range Safety Manual

• Journal of Korea Water Resources Association
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• v.45 no.7
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• pp.643-656
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• 2012

There has been an increase for the landslide areas and restoration expenses due, in large part, to the increased locally heavy rains caused by recent climate change as well as the reckless development. This study carried out a slope stability analysis by the application of distributed wetness index, using the GIS-based infinite slope stability model, which took the root cohesion effect into consideration, for part of Mt. Umyeon in Seoul, where landslide occurred in July 2011, in order to compensate the defects of existing analysis method, and subsequently compared its result with the case on the exploitation of lumped wetness index. In addition, this study estimated the distributed wetness index by methodology, applying three methods of specific catchment area calculation: single flow direction (SFD), multiple flow direction (MFD), and infinity flow direction (IFD), for catchment area, one of the variables of distributed wetness indices, and finally implemented a series of comparative analysis for slope stability by methodology. The simulation results showed that most unstable areas within the study site were dominantly located in cutting-area surroundings along with the residential area and the mountaintop and unstable areas of IFD and lumped wetness index method were similar while SFD and MFD provided smaller unstable areas than the two former methods.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.651-664
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• 2014

Recently, the demands of accurate forest carbon stock estimation and mapping are increasing in Korea. This study investigates the feasibility of two methods, k-Nearest Neighbor (kNN) and Regression Tree Analysis (RTA), for carbon stock estimation of pilot areas, Gongju and Sejong cities. The 3rd and 5th ~ 6th NFI data were collected together with Landsat TM acquired in 1992, 2010 and Aster in 2009. Additionally, various vegetation indices and tasseled cap transformation were created for better estimation. Comparison between two methods was conducted by evaluating carbon statistics and visualizing carbon distributions on the map. The comparisons indicated clear strengths and weaknesses of two methods: kNN method has produced more consistent estimates regardless of types of satellite images, but its carbon maps were somewhat smooth to represent the dense carbon areas, particularly for Aster 2009 case. Meanwhile, RTA method has produced better performance on mean bias results and representation of dense carbon areas, but they were more subject to types of satellite images, representing high variability in spatial patterns of carbon maps. Finally, in order to identify the increases in carbon stock of study area, we created the difference maps by subtracting the 1992 carbon map from the 2009 and 2010 carbon maps. Consequently, it was found that the total carbon stock in Gongju and Sejong cities was drastically increased during that period.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.417-418
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• 2018

미국 국립가뭄경감센터 (National Drought Mitigation Center, NDMC)는 다양한 가뭄지수를 통합하여 미국 전역의 가뭄진행상황을 모니터링하고 가뭄대응정책 수립을 위한 주요 의사결정정보로 활용하고 있다. 대표적으로 1999년에 개발되어 현재까지 운영 중인 미국가뭄모니터 (United States Drought Monitor, USDM)는 미국 전역에 대하여 가뭄단계를 표시한 지도 (U.S. Drought Monitor map)를 매주 생성하여 제공하고 있다 (http://droughtmonitor.unl.edu/). 가뭄지표(drought index)는 가뭄의 현황과 시공간적인 전개 과정을 분석하고 정량적 가뭄심도 평가 및 가뭄대응계획 수립을 위한 도구로써 다양하게 개발되어 활용되고 있다. 가뭄의 정도를 정량화하기 위하여 개발된 다수의 가뭄지수는 대상과 평가방법에 따라 가뭄을 표현하는 특성이 서로 다르다. 하나의 가뭄지수로는 가뭄특성을 온전히 표현하기 어렵기 때문에, 최근에는 단일 가뭄지수에 의존하기 보다는 다수의 가뭄지수를 이용하되, 여러 가뭄지수 간의 특징을 고려하여 각 가뭄지수가 갖는 장단점을 상호 보완하여 사용하기를 권고하고 있다. USDM은 파머가뭄심도지수 (Palmer Drought Severity Index, PDSI), Soil Moisture Model (NOAA Climate Prediction Center, CPC), 미 지리조사국의 하천유량 주간보고 (USGS Weekly Streamflow), 표준강수지수 (Standardized Precipitation Index, SPI) 등의 주요 가뭄판단지표를 선정하고, 가뭄판단의 기준으로써 각 가뭄지수의 가뭄심도 (drought severity) 및 백분위수 (percentiles)로 등급을 구분하였다. 가뭄등급은 '정상 상태 (none)'를 포함하여 '비정상적인 건조 (abnormally dry, D0)'에서 최악의 가뭄상태를 의미하는 '이례적인 가뭄상태 (exceptional, D4)'에 이르는 6 단계로 구분하고, 정상상태를 제외한 5 단계의 통합가뭄단계로 표시한다. 우리나라에서는 기상청, 수자원공사, 농어촌공사에서 기상/수문/농업관련 가뭄지수의 위험지도를 실시간으로 제공하고 있으며, 각 지표별로 상이한 기준으로 가뭄을 판단하고 있다. 각각의 가뭄지표에 대한 가뭄판단기준은 해당 국가의 장기적으로 축적된 자료를 활용하여 가뭄단계 및 가뭄판단기준의 재설정에 대한 연구가 필요하다. 본 연구에서는 SPI, SC-PDSI, 표준강수증발산지수 (Standardized Precipitation Evapotranspiration Index, SPEI), Evaporative Demand Drought Index (EDDI), 유효가뭄지수 (Effectvie Drought Index, EDI)의 다양한 가뭄지수를 활용하여 USDM의 가뭄심도 및 가뭄판단기준을 적용하고자한다.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1803-1818
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• 2021

As the frequency of drought increases due to climate change, it is very important to have a monitoring system that can accurately determine the situation of widespread drought. However, while ground-based meteorological data has limitations in identifying all the complex droughts in Korea, satellite remote sensing data can be effectively used to identify the spatial characteristics of drought in a wide range of regions and to detect drought. This study attempted to analyze the possibility of using remote sensing data for drought identification in South Korea. In order to monitor various aspects of drought, remote sensing and ground observation data of precipitation and potential evapotranspiration, which are major variables affecting drought, were collected. The evaluation of the applicability of remote sensing data was conducted focusing on the comparison with the observation data. First, to evaluate the applicability and accuracy of remote sensing data, the correlations with observation data were analyzed, and drought indices of various aspects were calculated using precipitation and potential evapotranspiration for meteorological drought monitoring. Then, to evaluate the drought monitoring ability of remote sensing data, the drought reproducibility of the past was confirmed using the drought index. Finally, a high-resolution drought map using remote sensing data was prepared to evaluate the possibility of using remote sensing data for actual drought in South Korea. Through the application of remote sensing data, it was judged that it would be possible to identify and understand various drought conditions occurring in all regions of South Korea, including unmeasured watersheds in the future.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1117-1126
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• 2018

Water supply system aims to meet the user's demand by securing water resources in a stable way. However, water supply failure sometimes happens because inflow decreases during drought period. Droughts induced by the lack of precipitation do not always lead to water supply failures. Thus, it is necessary to consider features of actual water shortage event when we evaluate a water supply risk. In this study, we developed a new drought index for drought management, i.e., Joint Drought Management Index (JDMI), using two water supply system performance indices such as reliability and vulnerability. Future data that were estimated from GCMs according to RCP 4.5 and 8.5 scenarios were used to estimate future water supply risk. After dividing the future period into three parts, the risk of water supply failure in the Nakdong River basin was analyzed using the JDMI. As a result, the risk was higher with the RCP 4.5 than the RCP 8.5. In case of RCP 4.5, W18 (Namgangdam) was identified as the most vulnerable area, whereas in case of RCP 8.5, W23 (Hyeongsangang) and W33 (Nakdonggangnamhae) were identified as the most vulnerable area.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.493-502
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• 2021

Recently, because of changes in temperature and rising water temperatures due to increased pollution sources, many algae have been produced in the water system. Therefore, there has been a lot of research using satellite images for the generation and monitoring of green algae. However, in prior studies, it is difficult to consider the optical properties of the local water system by using only a single index, and by using medium and low-resolution satellite images to conduct large-scale algae detection, there is a problem of accuracy in narrow, broad rivers. Therefore, in this work, we utilize high-resolution images of Sentinel-2 satellites to perform green algae detection on a single index (NDVI, SEI, FGAI) and development index (NDVI & SEI, FGAI & SEI) that mixes single indices. In this study, POD, FAR, and PC values were utilized to evaluate the accuracy of green algae detection algorithms, and the FGAI & SEI index showed the highest accuracy with 98.29% overall accuracy PC.

• Korean Journal of Environmental Biology
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• v.39 no.2
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• pp.245-257
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• 2021

Ulleungdo, a volcanic island, has different climate, soil, and topography characteristics from inland of the Korean Peninsula. Its agriculture also exhibits distinctive features. This study focused on floristic compositions and characteristics of crop lands in Ulleungdo. Flora surveys were conducted for 37 areas three times, one in May of 2016, one in July of 2020, and one in August of 2020. Results showed that vascular plants of crop lands in Ulleungdo included 186 taxa of 53 families, 132 genera, 160 species, 14 varieties, five subspecies, and five hybrids. Asteraceae had the most diverse species (33 taxa), followed by Poaceae (25 taxa), Fabaceae (12 taxa), Polygonaceae (11 taxa), and Liliaceae (nine taxa). The biological type of crop lands in Ulleungdo island was determined to be Th-R₅-D₄-e type. Rare plants were found for nine taxa: Athyrium acutipinnulum Kodama ex Nakai, Sedum takasimense Nakai, Rubus takesimensis Nakai, Dystaenia takesimana (Nakai) Kitag., Ligustrum foliosum Nakai, Aster pseudoglehni Y.Lim, Cirsium nipponicum (Maxim.) Makino, Lilium hansonii Leichtlin ex D.D.T.Moore, and Polygonatum robustum (Korsh.) Nakai. In addition, 45 taxa contained naturalized plants of 13 families, 33 genera, 44 species, and one variety. Urbanization and naturalization indices were 13.9%, and 24.2%, respectively.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1193-1201
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• 2020

This study aims to develop a regression model that estimates a low-flow index that can be applied to ungauged basins. A total of 30 midsized basins in South Korea use long-term runoff data provided by the National Integrated Water Management System (NIWMS) to calculate average low-flow, average minimum streamflow, and low-flow index duration and frequency. This information is used in the correlation analysis with 18 basin factors and 3 climate change factors to identify the basin area, average basin altitude, average basin slope, water system density, runoff curve number, annual evapotranspiration, and annual precipitation in the low-flow index regression model. This study evaluates the model's accuracy by using the root-mean-square error (RMSE) and the mean absolute error (MAE) for 10 ungauged, verified basins and compares them with the previous model's low-flow calculations to determine the effectiveness of the newly developed model. Comparative analysis indicates that the new regression model produces average low-flow, attributed to the consideration of varied basin and hydrologic factors during the new model's development.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1273-1283
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• 2022

Recently, forest fires have frequently occurred due to climate change, leading to human and property damage every year. The forest fire monitoring technique using remote sensing can obtain quick and large-scale information of fire-damaged areas. In this study, the Gangneung and Donghae forest fires that occurred in March 2022 were analyzed using the spectral band of Sentinel-2, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) to classify the affected areas of forest fires. The U-net based convolutional neural networks (CNNs) model was simulated for the fire-damaged areas. The accuracy of forest fire classification in Donghae and Gangneung classification was high at 97.3% (f₁=0.486, IoU=0.946). The same model used in Donghae and Gangneung was applied to Uljin and Samcheok areas to get rid of the possibility of overfitting often happen in machine learning. As a result, the portion of overlap with the forest fire damage area reported by the National Institute of Forest Science (NIFoS) was 74.4%, confirming a high level of accuracy even considering the uncertainty of the model. This study suggests that it is possible to quantitatively evaluate the classification of forest fire-damaged area using a spectral band and indices similar to that of the Compact Advanced Satellite 500 (CAS500-4) in the Sentinel-2.