• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.671-680
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• 2019

Many researches illustrated that the magnitude and frequency of hydrological event would increase in the future due to changes of hydrological cycle components according to climate change. However, few studies performed quantitative analysis and evaluation of future rainfall in North Korea, where the damage caused by extreme precipitation is expected to occur as in South Korea. Therefore, this study predicted the extreme precipitation change of North Korea in the future (2020-2060) compared to the current (1981-2017) using stationary and nonstationary frequency analysis. This study conducted nonstationary frequency analysis considering the external factors (mean precipitation of JFM (Jan.-Mar.), AMJ (Apr.-Jun.), JAS (Jul.-Sept.), OND (Oct.-Dec.)) of the HadGEM2-AO model simulated according to the Representative Concentration Pathway (RCP) climate change scenarios. In order to select external factors that have a similar tendency with extreme rainfall events in North Korea, the maximum annual rainfall data was obtained by using the ensemble empirical mode decomposition (EEMD) method. Correlation analysis was performed between the extracted residue and the external factors. Considering selected external factors, nonstationary GEV model was constructed. In RCP4.5, four of the eight stations tended to decrease in future extreme precipitation compared to the present climate while three stations increased. On the other hand, in RCP8.5, two stations decreased while five stations increased.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.113-126
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• 2021

This study was conducted to analyze the forest status and deforestation area changes of the DMZ region in North Korea based on satellite images. Using growing and non-growing season's RapidEye satellite images, land cover of the North Korean DMZ was classified into stocking land(conifer, deciduous, mixed), deforested land(unstocked mountain, cultivated mountain, bare mountain), and non-forest areas. Deforestation rates in the Yeonan-baecheon, Beopdong-Pyeonggang, Heoyang-Geumgang and Tongcheon-Goseong district were calculated as 14.24%, 16.75%, 5.98%, and 16.63% respectively. Forest fire and land use change of forest were considered as the main causes of deforestation of DMZ. Changes in deforestation area were analyzed through Google Earth images. As a results, it was shown that the area of deforestation was on a decreasing trend. This study can be used as basic data for establishing inter-Korean border region's forest cooperation strategies by providing forest spatial information on the North Korea's DMZ.

• Economic and Environmental Geology
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• v.51 no.6
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• pp.589-593
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• 2018

Democratic Peoples' Republic of Korea (DPRK) conducted the $6^{th}$ underground nuclear test at the Punggye-ri underground nuclear test site on September 27, 2017 12 hours 30 minutes of Korean local time. Comprehensive Nuclear-Test Ban Treaty Organization (CTBTO) under U.N. announced the body wave magnitude of the event was mb 6.1 while U.S. Geological Survey (USGS)'s calculation was mb 6.3. In this study, the differences of the magnitude estimates were investigated and verified. For this purpose, a source scaling between the $5^{th}$ and $6^{th}$ event, which's epicenters are 200 meters apart, was performed using seismic data sets from 30 broadband stations. The relative amplitude variations of the $6^{th}$ event compared to the $5^{th}$ event in the frequency domain was analyzed through the scaling. The increased amount of the bodywave magnitude $m_b$ for the $6^{th}$ event was calculated at 1 Hz, which was compared to those from USGS and CTBTO's calculations.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.649-663
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• 2019

The 2018 United Nations Development Programme (UNDP) report announced that deforestation in North Korea is the most extreme situation and in terms of climate change, this deforestation is a global scale issue. To respond deforestation, various study and projects are conducted based on remote sensing, but access to public data in North Korea is limited, and objectivity is difficult to be guaranteed. In this study, the forest detection based on density estimation in statistic using Landsat imagery was conducted in Gangwon province which is the only administrative district divided into South and North. The forest spatial data of South Korea was used as data for the labeling of forest and Non-forest in the Normalized Difference Vegetation Index (NDVI), and a threshold (0.6658) for forest detection was set by Gaussian Probability Density Function (PDF) estimation by category. The results show that the forest area decreased until the 2000s in both Korea, but the area increased in 2010s. It is also confirmed that the reduction of forest area on the local scale is the same as the policy direction of urbanization and industrialization at that time. The Kappa value for validation was strong agreement (0.8) and moderate agreement (0.6), respectively. The detection based on the Gaussian PDF estimation is considered a method for complementing the statistical limitations of the existing detection method using satellite imagery. This study can be used as basic data for deforestation in North Korea and Based on the detection results, it is necessary to protect and restore forest resources.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.667-675
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• 2022

Agroforestry is an ecological and economic land-use system that enables sustainable agriculture by combining forestry, agriculture, and livestock industries. North Korea chose agroforestry as a strategy for the restoration of sloping land and deforested land. Agroforestry was proposed for the inter-Korean forest cooperation subcommittee meeting and is currently highlighting carbon removal and promoting the '2050 Carbon Neutral Strategy' and 'Korea Peninsula Green Détente.' The study area, Suan-gun, Hwanghaebuk-do, is a constant deforestation monitoring area and a pilot site for management by the International Center for Research in Agroforestry. The requirements for agroforestry were analyzed through literature analysis. The agroforestry site-suitability map was visualized by applying GIS overlap analysis. Approximately 8,839 ha of sloping area was selected as suitable for agroforestry management, which is about 15% of Suan. We compared the map with Google Earth images and visually detected the land use status, such as agroforestry in Suan, to verify the results. As a future study, we will consider both natural-environment and socioeconomic factors and evaluate the relative importance of the factors to produce a high-accuracy agroforestry sitesuitability map at the national scale with the goal of producing basic data for the inter-Korea forest cooperation policy for long-term goals.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.97-109
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• 2019

Degree days have been determined using temperature data measured at nearby weather stations to a site of interest to produce information for supporting decision-making on agricultural production. Alternatively, the data products of Moderate Resolution Imaging Spectroradiometer (MODIS) can be used for estimation of degree days in a given region, e.g., Korean Peninsula. The objective of this study was to develop a simple tool for processing the MODIS product for estimating cooling degree days (CDD), which would help assessment of heat stress conditions for a crop as well as energy requirement for greenhouses. A set of scripts written in R was implemented to obtain temperature profile data for the region of interest. These scripts had functionalities for processing spatial data, which include reprojection, mosaicking, and cropping. A module to extract air temperature at the surface pressure level was also developed using R extension packages such as rgdal and RcppArmadillo. Random forest (RF) models, which estimate mean temperature and CDD with a different set of MODIS data, were trained at 34 sites in South Korea during 2009 - 2018. Then, the values of CDD were calculated over Korean peninsula during the same period using those RF models. It was found that the CDD estimates using the MODIS data explained >74% of the variation in the CDD measurements at the weather stations in North Korea as well as South Korea. These results indicate that temperature data derived from the MODIS atmospheric products would be useful for reliable estimation of CDD. Our results also suggest that the MODIS data can be used for preparation of weather input data for other temperature-based agro-ecological models such as growing degree days or chill units.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.266-266
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• 2020

본 연구에서는 기후변화로 인한 남북공유하천유역의 미래 수문특성 변화를 전망하기 위해 ArcGIS 프로그램을 통해 산정된 격자형 수문특성 매개변수를 분포형 모형인 GRM에 적용하여 임진강유역의 미래 유출수문특성 변화를 분석하였다. 분포형 모형에 사용되는 강우량 자료는 기상관측소 단위로 상세화된 13개 전지구 기후 모델 중 RCP4.5, 8.5 시나리오의 공유하천유역 인접 11개 관측소별 빈도해석 결과를 시·공간적으로 분포하여 사용하였다. 또한 미래기간별 유출특성 변화추이를 분석하기 위하여 참조기간(1981-2005), 21세기 전반기(F1, 2011-2040), 중반기(F2, 2041-2070), 후반기(F3, 2071-2100)로 구분하여 분석을 실시하였다. 분석 결과 본 연구의 대상지점인 임진강유역은 기후변화로 인해 확률강우량이 증가하여 유역의 유출수문특성에 직접적인 영향이 있을 것으로 예측되었다. RCP 4.5 시나리오에서는 21세기 후반기인 F3에 확률강우량 및 유출량의 증가추세가 줄어들 것으로 전망되나, 참조기간 대비 F1에서 20.4%, F2에서 35.7%, F3에서 34.6%의 평균 유출량 증가율을 보였으며, RCP 8.5 시나리오에서는 F1에서 19.9%, F2에서 38.3%, F3에서 67.8%로 지속적인 증가가 전망되었다. 또한 첨두홍수량 발생시각은 참조기간 대비 약 4.6~13.3% 감소가 예상되었다. 기후변화로 인한 홍수량의 변화는 재해위험을 증가시킬 수 있으며, 이러한 상황에서 남한과 북한의 협력을 통한 유역통합관리의 필요성은 점차 커질 것으로 보인다. 이를 위해서는 정확한 수문학적 분석을 선행하여야 하며, 본 연구가 남북공유하천유역의 재해위험을 평가하는 기초자료로 활용될 수 있을 것으로 판단된다.

• Korean Journal of Remote Sensing
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• v.25 no.1
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• pp.71-83
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• 2009

This paper is written to analyze possible problems encountered with the existing data for the monitoring of land use and land cover change over the Korean peninsula and, further, to provide technical alternatives for the future land monitoring over the area. The oldest type of non-spatial data related to the land use change are cadastral statistics obtained since 1911. Annual statistics of cadastral data in early years (before 1942) can be used to assess land use change over the area. However, the cadastral statistics after the Korean War are not very appropriate for land use monitoring since the land class in cadastral data does not always correspond with actual land cover status. Majority of spatial data available for land monitoring over the area are land cover maps classified from satellite imagery since early 1970's. To analyze the suitability of land cover maps that were produced by two separate institutes with about 10 years interval, we conducted simple change detection analysis using these maps. These maps were not quite ready to be compared each other, in which they did not have the same class definition, classification method, and geometric registration. To achieve continuous and effective monitoring of land use and land cover change, particularly over North Korea, we should have a standard scheme in type and season of satellite imagery, image classification procedure, and class definition, which also should correspond to international standards.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1129-1135
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• 2016

The NH-NongHyup network and servers were paralyzed in 2011, in the 2013 3.20 cyber attack happened and classified documents of Korea Hydro & Nuclear Power Co. Ltd were leaked on december in 2015. All of them were conducted by a foreign country. These attacks were planned for a long time compared to the script kids attacks and the techniques used were very complex and sophisticated. However, no successful solution has been implemented to defend an APT attacks(Advanced Persistent Threat Attacks) thus far. We will use big data analytics to analyze whether or not APT attacks has occurred. This research is based on the data collected through ISAC monitoring among 3 hierarchical Korean Defense System. First, we will introduce related research about big data analytics and machine learning. Then, we design two big data analytics models to detect an APT attacks. Lastly, we will present an effective response method to address a detected APT attacks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.317-320
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• 2016

The NH-NongHyup network and servers were paralyzed in 2011, in the 2013 3.20 cyber attack happened and Classified documents of Korea Hydro & Nuclear Power Co. Ltd were leaked on December in 2015. All of them were conducted by a foreign country. These attacks were planned for a long time compared to the script kids attacks and the techniques used were very complex and sophisticated. However, no successful solution has been implemented to defend an APT attack thus far. Therefore, we will use big data analytics to analyze whether or not APT attack has occurred in order to defend against the manipulative attackers. This research is based on the data collected through ISAC monitoring among 3 hierarchical Korean defense system. First, we will introduce related research about big data analytics and machine learning. Then, we design two big data analytics models to detect an APT attack and evaluate the models' accuracy and other results. Lastly, we will present an effective response method to address a detected APT attack.