• Investigative Magnetic Resonance Imaging
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• v.23 no.3
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• pp.251-258
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• 2019

Purpose: To assess the feasibility of the use of spin-echo echo-planar imaging (SE-EPI) magnetic resonance elastography (MRE) in livers of children and young adults. Materials and Methods: Patients (${\leq}20$ years old) who underwent 3T SE-EPI MRE were included retrospectively. Subjects were divided into three groups according to the purpose of the liver MRI: suspicion of fatty liver or focal fat deposition in the liver (FAT group), liver fibrosis after receiving a Kasai operation from biliary atresia (BA group), and hepatic iron deposition after receiving chemotherapy or transfusions (IRON group). Technical failure of MRE was defined when a stiffness map showed no pixel value with a confidence index higher than 95%, and the patients were divided as success and failure groups accordingly. Clinical findings including age, gender, weight, height, and body mass index and magnetic resonance imaging results including proton density fat fraction (PDFF), $T2^*$, and MRE values were assessed. Factors affecting failure of MRE were evaluated and the image quality in wave propagation image and stiffness map was evaluated using the appropriate scores. Results: Among total 240 patients (median 15 years, 211 patients in the FAT, 21 patients in the BA, and 8 patients in the IRON groups), technical failure was noted in six patients in the IRON group (6/8 patients, 75%), while there were no failures noted in the FAT and BA groups. These six patients had $T2^*$ values ranging from 0.9 to 3.8 ms. The image quality scores were not significantly different between the FAT and BA groups (P > 0.999), while the scores were significantly lower in the IRON group (P < 0.001). Conclusion: The 3T SE-EPI MRE in children and young adults had a high technical success rate. The technical failure was occurred in children with decreased $T2^*$ value (${\leq}3.8ms$) from iron deposition.

• Geophysics and Geophysical Exploration
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• v.22 no.1
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• pp.37-43
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• 2019

We present gravity anomaly maps based on KIGAM's gravity data measured from 2000 to 2018. Until 2016, we acquired gravity data on about 6,400 points for the purpose of regional mapping covering the whole country with data density of at least one point per $4km{\times}4km$ for reducing the time of the data acquisition. In addition, we have performed local gravity surveys for the purpose of mining development in and around the NMC Moland Mine at Jecheon in 2013 and in the Taebaeksan mineralized zone from 2015 to 2018 with data interval of several hundred meters to 2 km. Meanwhile, we carried out precise gravity explorations with data interval of about 250 m on and around epicenter areas of Gyeongju and Pohang earthquakes of relatively large magnitude which occurred in 2016 and in 2017, respectively. Thus we acquired in total about 9,600 points data as the result. We also used additional data acquired by Pusan National University for some local areas. Finally, gravity data more than 16,000 points except for the repetition and temporal control points were available to calculate free-air, Bouguer, and isostatic gravity anomalies. Therefore, the presented anomaly maps are most advanced in spatial distribution and the number of used data so far in Korea.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.5
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• pp.1-12
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• 2019

It is important to measure the height of trees as an essential element for assessing the forest health in urban areas. Therefore, an automated method that can measure the height of individual tree as a three-dimensional forest information is needed in an extensive and dense forest. Since airborne LiDAR dataset is easy to analyze the tree height(z-coordinate) of forests, studies on individual tree height measurement could be performed as an assessment forest health. Especially in urban forests, that adversely affected by habitat fragmentation and isolation. So this study was analyzed to measure the height of individual trees for assessing the urban forests health, Furthermore to identify environmental factors that affect forest growth. The survey was conducted in the Mt. Bongseo located in Seobuk-gu. Cheonan-si(Middle Chungcheong Province). We segment the individual trees on coniferous by automatic method using the airborne LiDAR dataset of the two periods (year of 2016 and 2017) and to find out individual tree growth. Segmentation of individual trees was performed by using the watershed algorithm and the local maximum, and the tree growth was determined by the difference of the tree height according to the two periods. After we clarify the relationship between the environmental factors affecting the tree growth. The tree growth of Mt. Bongseo was about 20cm for a year, and it was analyzed to be lower than 23.9cm/year of the growth of the dominant species, Pinus rigida. This may have an adverse effect on the growth of isolated urban forests. It also determined different trees growth according to age, diameter and density class in the stock map, effective soil depth and drainage grade in the soil map. There was a statistically significant positive correlation between the distance to the road and the solar radiation as an environmental factor affecting the tree growth. Since there is less correlation, it is necessary to determine other influencing factors affecting tree growth in urban forests besides anthropogenic influences. This study is the first data for the analysis of segmentation and the growth of the individual tree, and it can be used as a scientific data of the urban forest health assessment and management.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.692-703
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• 2021

Recently, with the development of computer graphics technology, research on technology for expressing real objects as more realistic virtual graphics is being actively conducted. Point cloud is a technology that uses numerous points, including 2D spatial coordinates and color information, to represent 3D objects, and they require huge data storage and high-performance computing devices to provide various services. Video-based Point Cloud Compression (V-PCC) technology is currently being studied by the international standard organization MPEG, which is a projection based method that projects point cloud into 2D plane, and then compresses them using 2D video codecs. V-PCC technology compresses point cloud objects using 2D images such as Occupancy map, Geometry image, Attribute image, and other auxiliary information that includes the relationship between 2D plane and 3D space. When increasing the density of point cloud or expanding an object, 3D calculation is generally used, but there are limitations in that the calculation method is complicated, requires a lot of time, and it is difficult to determine the correct location of a new point. This paper proposes a method to generate additional points at more accurate locations with less computation by applying 2D interpolation to the image on which the point cloud is projected, in the V-PCC technology.

• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.330-338
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• 2023

To investigate the impact of forestry projects on the carbon stocks of forests, we estimated the carbon stock change of above-ground and soil before and after forestry projects using forest type maps, forestry project information, and soil information. First, we selected six map sheet with large areas and declining age class based on forest type map information. Then, we collected data such as forest type maps, growth coefficients, soil organic matter content, and soil bulk density of the estimated areas to calculate forest carbon storage. As a result, forest carbon stocks decreased by about 34.1~70.0% after forestry projects at all sites. In addition, compared to reference studies, domestic forest soils store less carbon than the above-ground, so it is judged that domestic forest soils have great potential to store more carbon and strategies to increase carbon storage are needed. It was estimated that the amount of carbon stored before forestry projects is about 1.5 times more than after forestry projects. The study estimated that it takes about 27 years for forests to recover to their pre-thinning carbon stocks following forestry projects. Since it takes a long time for forests to recover to their original carbon stocks once their carbon stocks are reduced by physical damage, it is necessary to plan to preserve them as much as possible, especially for highly conservative forests, so that they can maintain their carbon storage function.

• Korean Journal of Ecology and Environment
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• v.55 no.3
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• pp.201-211
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• 2022

The macroinvertebrate community in the Singal reservoir, Yedang and Juam lake was investigated three times from April 2021 to October 2021. Each lake was investigated by dividing it into inflow, middle-flow, and outflow. Additionally, sampling was conducted again by dividing it into the edge and center parts at each inflow, middle-flow, and outflow. Eight families of benthic macroinvertebrates were collected except for chironomids in the sampling sites. Dominant macroinvertebrates were investigated as chironomids, and Tubificidae was sub-dominant organisms. The density of macroinvertebrate community was higher in the edge area than in the center bottom of the lakes. The density of chironomids was low when the water level was high but was high when the water level was low. In the edge area of the middle-flow in Singal reservoir, the density of chironomids was 1,208 ind. m^-2 in April when the water level was high, but it increased to 1,401 ind. m^-2 in July when the water level was low. Similarly, the density of chironomids at the outflow of Yedang lake was high (1,990 ind. m^-2) in July when the water level was low. The density of chironomids also decreased along with the increasing water level at all edge areas of Juam lake. These results indicated that it will be necessary to consider the water level when studying macroinvertebrate communities in the lake.

• Journal of Korean Society of Forest Science
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• v.98 no.4
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• pp.409-416
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• 2009

Forest biomass estimation is essential for greenhouse gas inventories and terrestrial carbon accounting. Remote sensing allows for estimating forest biomass over a large area. This study was conducted to estimate forest biomass and to produce a forest biomass map for Muju county using forest biomass conversion table developed by field plot data from the 5th National Forest Inventory and Landsat TM-5. Correlation analysis was carried out to select suitable independent variables for developing regression models. It was resulted that the height class, crown closure density, and age class were highly correlated with forest biomass. Six regression models were used with the combination of these three stand variables and verified by validation statistics such as root mean square error (RMSE) and mean bias. It was found that a regression model with crown closure density and height class (Model V) was better than others for estimating forest biomass. A biomass conversion table by model V was produced and then used for estimating forest biomass in the study site. The total forest biomass of the Muju county was estimated about 8.8 million ton, or 128.3 ton/ha by the conversion table.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.9-20
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• 2010

In order to visualize participating media in 3D space, they usually calculate the incoming radiance by subdividing the ray path into small subintervals, and accumulating their respective light energy due to direct illumination, scattering, absorption, and emission. Among these light phenomena, scattering behaves in very complicated manner in 3D space, often requiring a great deal of simulation efforts. To effectively simulate the light scattering effect, several approximation techniques have been proposed. Volume photon mapping takes a simple approach where the light scattering phenomenon is represented in volume photon map through a stochastic simulation, and the stored information is explored in the rendering stage. While effective, this method has a problem that the number of necessary photons increases very fast when a higher variance reduction is needed. In an attempt to resolve such problem, we propose a different approach for rendering particle-based volume data where kernel smoothing, one of several density estimation methods, is explored to represent and reconstruct the light in-scattering effect. The effectiveness of the presented technique is demonstrated with several examples of volume data.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.124-137
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• 2012

Climate analysis is important in urban planning for human comfort. Synoptic weather conditions can only resolve the 30% of local variance of wind conditions whereas 70% of the variance arise from local terrain, buildings, and other small scale thermal conditions. Climate Analysis Seoul (CAS) was developed to resolve such micro-scale climate. The Local-scale air temperature Deviation (LD) analysis map from CAS showed the co-existence of built-up and suburban areas in the study region (CR, Cold-air analysis Region) despite its small extent. Temperature, humidity, wind speed, and wind direction were monitored in CR. Hourly observed cooling rate agreed well with LD. Cold air production, transportation, and stagnation was visualized by the observed Vertical Temperature Gradient (VTG) along the small stream in CR. VTG observed at the upper-most stream can be divided into two components: radiative cooling and cold air inflow from outside. Radiative cooling exists regardless of the wind speed whereas cold air inflow occurs only with calm wind. From the regression analyses based on the wind speed, the inflow portion was determined as 84% of radiative cooling. Climate analysis in the future will be able to characterize the changes in cold air by urban development plan to support the human comfort.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.12-25
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• 2009

The aim of this study is to analyze the periodical and spatial characteristics of urban crime and to find out the factors that affect the crime occurrence. For these, crime data of Masan City was examined and crime occurrence pattern is ploted on a map using crime density and criminal hotspot analysis. The spatial relationship of crime occurrence and factors affecting crime were also investigated using ESDA (Exploratory Spatial Data Analysis) and SAR (Spatial Auto-Regression) model. As a result, it was found that crimes had strong tendency of happening during a certain period of time and with spatial contiguity. Spatial contiguity of crimes was made clear through the spatial autocorrelation analysis on 5 major crimes. Especially, robbery revealed the highest spatial autocorrelation. However as a autocorrelation model, Spatial Error Model(SEM) had statistically the highest goodness of fit. Moreover, the model proved that old age population ratio, property tax, wholesale-retail shop number, and retail & wholesale number were statistically significant that affect crime occurrence of 5 most major crimes and theft crime. However population density affected negatively on assault crime. Lastly, the findings of this study are expected to provide meaningful ideas to make our cities safer with U-City strategies and services.