• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.553-560
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• 2020

This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.241-249
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• 2014

The continuous observations for atmospheric aerosol were carried out during 3 years (2009-2011) by using a multi-wavelength Raman lidar at the Gwangju Institute of Science and Technology (GIST), Korea ($35.11^{\circ}N$, $126.54^{\circ}E$). The particle depolarization ratios were retrieved from the observations in order to distinguish the Asian dust layer. The vertical information of Asian dust layers were used as input parameter for the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model for analysis of its backward trajectories. The source regions and transport pathways of the Asian dust layer were identified. The most frequent source region of Asian dust in Korea was Gobi desert during observation period in this study. The statistical analysis on the particle depolarization ratio of Asian dust was conducted according to their transport route in order to retrieve the variation of optical properties of Asian dust during long-range transport. The transport routes were classified into the Asian dust which was transported to observation site directly from the source regions, and the Asian dust which was passed over pollution regions of China. The particle depolarization ratios of Asian dust which were transported via industrial regions of China was ranged 0.07-0.1, whereas, the particle depolarization ratio of Asian dust which was transported directly from the source regions to observation site were comparably higher and ranged 0.11-0.15. It is considered that the pure Asian dust particle from source regions were mixed with pollution particles, which is likely to spherical particle, during transportation so that the values of particle depolarization of Asian dust mixed with pollution was decreased.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1117-1132
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• 2019

Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.

• Korean Journal of Ecology and Environment
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• v.41 no.2
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• pp.188-197
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• 2008

This research was a preliminary case study to determine the levels of total mercury in the tissues of sentinel species (Zacco platypus) and ecological health in relation to habitat characteristics and chemical conditions. We collected fishes in Gap Stream during June$\sim$October 2007 and analyzed the total mercury from five types of tissues such as liver, kidney, gill, vertebrae and muscle of Zaceo platypus using Direct Mercury Analyzer (DMA-80, US EPA Method 7473). Mean concentrations of total [Hg], based on all tissues, was 67.2 and $20.7\;{\mu}g\;kg^{-1}$, in the upstream and downstream site, respectively, indicating 3 times greater level in the upstream. In other words, the levels were higher in the pristine upstream than the downstream influenced by the wastewater disposal plant. Chemical water quality, based on BOD, COD and nutrients (TN, TP) showed that severe degradation occurred in the downstreams than the upstreams. Index of Biological Integrity (IBI) using fish multi-metric model averaged 32, indicating a "good$\sim$fair" condition and varied from 42 (excellent$\sim$good) at S2 to 22 (fair$\sim$poor) at S5 depending on the sites sampled. Qualitative Habitat Evaluation Index (QHEI) in the all sites averaged 142, which was judged as "good" habitat health, but showed a high variation (181 in Site 2 vs. 67 in Site 5). Overall data suggest that health conditions, based on IBI and QHEI, was better in the upstream sites but the mercury bioaccumulation levels in the fish tissues were opposite. We believe that measurements of various parameters are required for a diagnosis of integrative ecosystem health.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.548-559
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• 2011

3-D Multi-geophysical surveys were carried out around the Hwasan caldera at the Euisung Sub-basin. To overcome the limitations of resolutions in previous studies, dense gravity data and magnetotelluric (MT) data were obtained and analyzed. In this study, the independent inversion models from gravity and MT data were integrated using correlation and classification approaches for 3-D imaging of the geologic structures. A Structure Index (SI) method was proposed and applied to the integration and classification analyses. This method consists of Type Angle (TA) and Type Intensity (TI) values, which are estimated by the spatial correlation and abnormality of the physical properties. The SI method allowed the classification analysis to be effectively performed. Major findings are as follows: 1) pyroclastic rocks around the central area of the Hwasan caldera with lower density and resistivity than those of neighboring regions extended to a depth of around 1 km, 2) intrusive igneous rocks with high resistivity and density were imaged around the ring fault boundary, and 3) a basement structure with low resistivity and high density, at a depth of 3-5 km, was inferred by the SI analysis.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.6
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• pp.45-52
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• 2019

As international criteria and standards are required in the fields of design and construction, landscape performance must also be considered not only for the value of the landscape but also for providing quality assurance and sustainability. Given the lack of research on landscape performance, the present research was purposed to analyze the importance of potential assessment categories and items using an analytical network process. A list of assessment items, which is composed of 20 items and 6 categories, was derived through a literature review and a preliminary survey of 11 landscape professionals. An ANP model was established and a survey was conducted among 30 landscape practitioners to determine the weight of priorities considering the criteria. The results of ANP showed that the categories of site selection, preservation and health, and convenience had high priorities while materials had the lowest importance score. For the assessment items, a monitoring plan was the highest importance, followed by cultural/ historic preservation, management cost reduction, and natural ground areas. Despite the difficulties in quantifying landscape achievements, most respondents agreed that there needs to be an evaluation system for landscape performance in order to assure the quality and sustainability of landscape development. More research and discussion are needed to develop an assessment system for landscape performance that is applicable to Korean context.

• Archives of design research
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• v.11 no.1
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• pp.291-302
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• 1998

This paper covers the development process of multimedia evaluation system, especially focused on customer satisfactory factors while customers navigating net-based Interactive multimedia system. Customers usually experience new level of interaction cased by newly developed web-based technology In ordinary multimedia system. However, if it gives customers satisfactory experience is a matter of question. To find out the relationship between customer satisfaction and interactivity factors exposed by multimedia system, a model has been developed which describes the structure of web-based multimedia system and its relation to customer satisfactory factors. Five different experiments, including 'semantic differential', 'focus group interview', and 'expert review', has been conducted and four customer satisfactory factors were identified. Those are 'customery value', 'structural perfectness', 'visual perfectness', and 'contemporaneity'. With these factors and newly delveoped evaluation system, 7 different web-site has been evaluated and analyzed at the end of this report.

• Journal of Korean Society of Forest Science
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• v.98 no.1
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• pp.125-131
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• 2009

To facilitate the sustainable forest management, Forest Service in Korea has assigned 2.9 million hectare forests as 'intensive management forests' and encouraged local governments to develop a strategic management plan for their forests. One of problems for the sustainable forest management in Korea is the skewed distribution of forest age classes. Currently the majority of forestlands in Korea is occupied by age classes III and IV. In this study, we intended to find an optimum harvest volume, which enable one to make the intensive management forest in Youngdong-Gun evenly distributed for the age classes and allow an even harvest volume through a 50 year time horizon. To develop an optimization model, we applied the goal programming technique which is adequate for a multi-purpose management planning. The results indicated that it is necessary to harvest 1.2 million cubic meters in each decade to achieve the most stable distribution of age classes for the study site. The harvest volume target resulted from this study would be used in a management planning or an associated policy making process in the future.

• Korean Journal of Ecology and Environment
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• v.39 no.2 s.116
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• pp.145-156
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• 2006

The objective of this study was to evaluate biological health conditions and physicochemical status using multi-metric models at five sites of the Keum-Ho River during August 2004 and June 2005. The research approach was based on a qualitative habitat evaluation index (QHEI), index of biological integrity (IBI) using fish assemblage, and long-term chemical data (1995 ${\sim}$ 2004), which was obtained from the Ministry of Environment, Korea. For the biological health assessments, regional model of the IBI in Korea (An,2003), was applied for this study. Mean IBI in the river was 30 and varied from 23 to 48 depending on the sampling sites. The river health was judged to be "fair condition", according to the stream health criteria of US EPA (1993) and Barbour et al. (1999). According to the analysis of the chemical water quality data of the river, BOD, COD, conductivity, TP, TN, and TSS largely varied epending on the sampling sites, seasons and years. Variabilities of some parameters including BOD, COD, TP, TN, and conductivity were greater in the downstream than in the upstream reach. This phenomenon was evident in the dilution by the rain during the monsoon. This indicates that precipitation is a very important factor of the chemical variations of water quality. Community analyses showed that species diversity index was highest (H=0.78) in the site 1, while community dominance index was highest in the site 3, where Opsariichthys uncirostris largely dominated. In contrast, the proportions of omnivore and tolerant species were greater in the downstream reach, than in the upstream reach. Overall, this study suggests that some sites in the downstream reach may need to restore the aquatic ecosystem for better biological health.