Evaluation of a Land Use Change Matrix in the IPCC’s Land Use, Land Use Change, and Forestry Area Sector Using National Spatial Information

Jeongmook Park,Jongsu Yim,Jungsoo Lee 강원대학교 산림과학연구소 2017 Journal of Forest Science Vol.33 No.4

This study compared and analyzed the construction of a land use change matrix for the Intergovernmental Panel on Climate Change’s (IPCC) land use, land use change, and forestry area (LULUCF). We used National Forest Inventory (NFI) permanent sample plots (with a sample intensity of 4 km) and permanent sample plots with 500 m sampling intensity. The land use change matrix was formed using the point sampling method, Level-2 Land Cover Maps, and forest aerial photographs (3rd and 4th series). The land use change matrix using the land cover map indicated that the annual change in area was the highest for forests and cropland; the cropland area decreased over time. We evaluated the uncertainty of the land use change matrix. Our results indicated that the forest land use, which had the most sampling, had the lowest uncertainty, while the grassland and wetlands had the highest uncertainty and the least sampling. The uncertainty was higher for the 4 km sampling intensity than for the 500 m sampling intensity, which indicates the importance of selecting the appropriate sample size when constructing a national land use change matrix.

Evaluation of Suitable REDD+ Sites Based on Multiple-Criteria Decision Analysis (MCDA): A Case Study of Myanmar

Park, Jeongmook,Sim, Woodam,Lee, Jungsoo Institute of Forest Science 2018 Journal of Forest Science Vol.34 No.6

In this study, the deforestation and forest degradation areas have been obtained in Myanmar using a land cover lamp (LCM) and a tree cover map (TCM) to get the $CO_2$ potential reduction and the strength of occurrence was evaluated by using the geostatistical technique. By applying a multiple criteria decision-making method to the regions having high strength of occurrence for the $CO_2$ potential reduction for the deforestation and forest degradation areas, the priority was selected for candidate lands for REDD+ project. The areas of deforestation and forest degradation were 609,690ha and 43,515ha each from 2010 to 2015. By township, Mong Kung had the highest among the area of deforestation with 3,069ha while Thlangtlang had the highest in the area of forest degradation with 9,213 ha. The number of $CO_2$ potential reduction hotspot areas among the deforestation areas was 15, taking up the $CO_2$ potential reduction of 192,000 ton in average, which is 6 times higher than that of all target areas. Especially, the township of Hsipaw inside the Shan region had a $CO_2$ potential reduction of about 772,000 tons, the largest reduction potential among the hotpot areas. There were many $CO_2$ potential reduction hot spot areas among the forest degradation area in the eastern part of the target region and has the $CO_2$ potential reduction of 1,164,000 tons, which was 27 times higher than that of the total area. AHP importance analysis showed that the topographic characteristic was 0.41 (0.40 for height from surface, 0.29 for the slope and 0.31 for the distance from water area) while the geographical characteristic was 0.59 (0.56 for the distance from road, 0.56 for the distance from settlement area and 0.19 for the distance from Capital). Yawunghwe, Kalaw, and Hsi Hseng were selected as the preferred locations for the REDD+ candidate region for the deforestation area while Einme, Tiddim, and Falam were selected as the preferred locations for the forest degradation area.

Detection of Trees with Pine Wilt Disease Using Object-based Classification Method

Jeongmook Park,Woodam Sim,Jungsoo Lee 강원대학교 산림과학연구소 2016 Journal of Forest Science Vol.32 No.4

In this study, regions infected by pine wilt disease were extracted by using object-based classification method (OB-infected region), and the characteristics of special distribution about OB-infected region were figured out. Scale 24, Shape 0.1, Color 0.9, Compactness 0.5, and Smoothness 0.5 was selected as the objected-based, optimal weighted value of OB-infected region classification. The total accuracy of classification was high with 99% and Kappa coefficient was also high with 0.97. The area of OB-infected region was approximately 90 ha, 16% of the total area. The OB-infected region in Age class V and VI was intensively distributed with 97% of the total. Also, The OB-infected region in Middle and Large DBH class was intensively distributed with 99% of the total. In terms of the topographic characteristics of OB-infected region, the damages occurred approximately 86% below the altitude of 200 m, and occurred 91% with a slope less than 10 degree. The damage occurred a lot in low hilly mountain and undulating slope. In addition, the accessibility to road and residential area from OB-infected region was less than 300 m in large part. Overall, it was figured out that artificial effect is stronger than natural effect with regard to the spread of pine wilt disease.

Anisotropic lattice thermal expansion of uranium-based metallic fuels: A high-temperature X-ray diffraction study

Park, Jeongmi,Cho, Su Yeon,Youn, Young-Sang,Lee, Jeongmook,Kim, Jong-Yun,Park, Seo-Hyeon,Bae, Sang-Eun,Kuk, Seoung Woo,Park, Jeong-Yong,Rhee, Choong Kyun,Lim, Sang Ho Elsevier 2019 Journal of Nuclear Materials Vol.527 No.-

<P><B>Abstract</B></P> <P>We characterized the lattice parameter and phase transformation behaviors of six uranium-based metallic fuels in the temperature range 303–1173 K using <I>in situ</I> high-temperature X-ray diffraction (HT-XRD). In all of the fuels, α-U crystal structure almost vanished at 1023 K while UO<SUB>2</SUB> crystal structure started forming at 843 K. Pawley refinement of HT-XRD data revealed anisotropic lattice thermal expansion with increases along the <I>a</I>- and <I>c</I>-axes upon annealing in all the metallic fuels. Furthermore, we confirmed that rare-earth elements (Nd, Ce, Pr, and La) contained in the U–10Zr metallic fuel hardly influenced the thermal behavior of the lattice parameters.</P>

Influence of Metal-doping on the Surface Structure and Electrochemical Reactivity of Uranium Dioxide

Jeongmook Lee,Jandee Kim,Young-Sang Youn,Seohyun Park,Jeong-mi Park,Jong-Yun Kim,Sang Ho Lim 한국방사성폐기물학회 2018 한국방사성폐기물학회 학술논문요약집 Vol.2018 No.10

Assessment of REDD+ Suitable Area for Sustainable Forest Management in Paraguay

Jeongmook Park,이용규,Byeongmin Lim,이정수 강원대학교 산림과학연구소 2020 Journal of Forest Science Vol.36 No.3

This study extracted deforestation area and degraded forestland area, which are potential REDD+ (Reducing Emissions from Deforestation and Forest Degradation) project candidate areas in Paraguay using Land Cover Map (LCM) and Tree Cover Map (TCM). The REDD+ project objectives scenarios were set three stages: ‘afforestation and economic efficiency scenario’, ‘local capacity reinforcement scenario’, and ‘Infrastructure-oriented scenario’. And then, we evaluated the project unit suitable area of the REDD+ project. All scenarios selected the evaluation factors for each scenario in addition to the area ratio factors for deforestation area and degraded forestland area and weighted values were extracted by assigning category scores. As a result of the three scenarios comparison analysis, Concepcion state score was the highest. Within Concepcion state, the Belon district had the highest score, making it appropriate as a project unit REDD+ project candidate area in Paraguay, while the San Carlos district had the lowest score. This study can be used as basic data for selecting REDD+ project candidate area in Paraguay, and it is expected to contribute sufficiently to REDD+ project if additional data or information of social, cultural and economic sectors are secured.

Detection of Individual Tree Species Using Object-Based Classification Method with Unmanned Aerial Vehicle (UAV) Imagery

Park, Jeongmook,Sim, Woodam,Lee, Jungsoo Institute of Forest Science 2019 Journal of Forest Science Vol.35 No.3

This study was performed to construct tree species classification map according to three information types (spectral information, texture information, and spectral and texture information) by altitude (30 m, 60 m, 90 m) using the unmanned aerial vehicle images and the object-based classification method, and to evaluate the concordance rate through field survey data. The object-based, optimal weighted values by altitude were 176 for 30 m images, 111 for 60 m images, and 108 for 90 m images in the case of Scale while 0.4/0.6, 0.5/0.5, in the case of the shape/color and compactness/smoothness respectively regardless of the altitude. The overall accuracy according to the type of information by altitude, the information on spectral and texture information was about 88% in the case of 30 m and the spectral information was about 98% and about 86% in the case of 60 m and 90 m respectively showing the highest rates. The concordance rate with the field survey data per tree species was the highest with about 92% in the case of Pinus densiflora at 30 m, about 100% in the case of Prunus sargentii Rehder tree at 60 m, and about 89% in the case of Robinia pseudoacacia L. at 90 m.

Evaluation of a Land Use Change Matrix in the IPCC's Land Use, Land Use Change, and Forestry Area Sector Using National Spatial Information

Park, Jeongmook,Yim, Jongsu,Lee, Jungsoo Institute of Forest Science 2017 Journal of Forest Science Vol.33 No.4

This study compared and analyzed the construction of a land use change matrix for the Intergovernmental Panel on Climate Change's (IPCC) land use, land use change, and forestry area (LULUCF). We used National Forest Inventory (NFI) permanent sample plots (with a sample intensity of 4 km) and permanent sample plots with 500 m sampling intensity. The land use change matrix was formed using the point sampling method, Level-2 Land Cover Maps, and forest aerial photographs (3rd and 4th series). The land use change matrix using the land cover map indicated that the annual change in area was the highest for forests and cropland; the cropland area decreased over time. We evaluated the uncertainty of the land use change matrix. Our results indicated that the forest land use, which had the most sampling, had the lowest uncertainty, while the grassland and wetlands had the highest uncertainty and the least sampling. The uncertainty was higher for the 4 km sampling intensity than for the 500 m sampling intensity, which indicates the importance of selecting the appropriate sample size when constructing a national land use change matrix.

Surface Characterization of ε-particle Doped Uranium Dioxide

Jeongmook Lee,Jeongmook Lee,Tae-Hyeong Kim,Junghwan Park,Jong-Yun Kim,Sang Ho Lim 한국방사성폐기물학회 2021 한국방사성폐기물학회 학술논문요약집 Vol.2021 No.11

Prediction of Land Use/Land Cover Change in Forest Area Using a Probability Density Function

Park, Jinwoo,Park, Jeongmook,Lee, Jungsoo Institute of Forest Science 2017 Journal of Forest Science Vol.33 No.4

This study aimed to predict changes in forest area using a probability density function, in order to promote effective forest management in the area north of the civilian control line (known as the Minbuk area) in Korea. Time series analysis (2010 and 2016) of forest area using land cover maps and accessibility expressed by distance covariates (distance from buildings, roads, and civilian control line) was applied to a probability density function. In order to estimate the probability density function, mean and variance were calculated using three methods: area weight (AW), area rate weight (ARW), and sample area change rate weight (SRW). Forest area increases in regions with lower accessibility (i.e., greater distance) from buildings and roads, but no relationship with accessibility from the civilian control line was found. Estimation of forest area change using different distance covariates shows that SRW using distance from buildings provides the most accurate estimation, with around 0.98-fold difference from actual forest area change, and performs well in a Chi-Square test. Furthermore, estimation of forest area until 2028 using SRW and distance from buildings most closely replicates patterns of actual forest area changes, suggesting that estimation of future change could be possible using this method. The method allows investigation of the current status of land cover in the Minbuk area, as well as predictions of future changes in forest area that could be utilized in forest management planning and policymaking in the northern area.