• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.1B
• /
• pp.23-33
• /
• 2009

Climate change, abnormal weather, and unprecedented extreme weather events have appeared globally. Interest in their size, frequency, and changes in spatial distribution has been heightened. However, the events do not display regional or regular patterns or cycles. Therefore, it is difficult to carry out quantified evaluation of their frequency and tendency. For more objective evaluation of extreme weather events, this study proposed a rainfall extreme weather index (STARDEX, 2005). To compare the present and future spatio-temporal distribution of extreme weather events, each index was calculated from the past data collected from 66 observation points nationwide operated by Korea Meteorological Administration (KMA). Tendencies up to now have been analyzed. Then, using SRES B2 scenario and 2045s (2031-2050) data from YONU CGCM simulation were used to compute differences among each of future extreme weather event indices and their tendencies were spatially expressed.The results shows increased rainfall tendency in the East-West inland direction during the summer. In autumn, rainfall tendency increased in some parts of Gangwon-do and the south coast. In the meanwhile, the analysis of the duration of prolonged dry period, which can be contrasted with the occurrence of rainfall or its concentration, showed that the dryness tendency was more pronounced in autumn rather than summer. Geographically, the tendency was more remarkable in Jeju-do and areas near coastal areas.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_2
• /
• pp.747-763
• /
• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.17 no.1
• /
• pp.129-143
• /
• 2014

The purpose of this study is to evaluate the availability of dual-polarization radar rain for flood routing in Chungju Dam watershed($6,625.8km^2$) using KIMSTORM (Grid-based KIneMatic wave STOrm Runoff Model). The Sobaek dual-polarization radar data for 1 heavy rain and 3 typhoon(Khanun, Bolaven, and Sanba) events in 2012 were obtained from Han River Flood Control Office. The spatio-temporal patterns between the two data were similar showing the ratio of radar rain to ground rain with 0.97. The KIMSTORM was set to $500{\times}500m$ resolution and a total of 45,738 cells(198 rows${\times}$231 columns) for the watershed. For radar rain and 41 ground rains, the model was independently calibrated using discharge data at 3 streamflow gauging stations(YW1, YC, and CJD) with coefficient of determination($R^2$), Nash and Sutcliffe Model Efficiency(ME), and Volume Conservation Index(VCI). The $R^2$, ME, and VCI 0.80, 0.62 and 1.08 for radar rain and 0.83, 0.68 and 1.10 for ground rain respectively.

• Korean Journal of Environmental Biology
• /
• v.40 no.1
• /
• pp.25-53
• /
• 2022

In this study, trends in research methods and topics of seabird and marine fish migration were examined. Based on the framework of existing animal migration studies, future research directions were proposed in relation to the migration of seabirds and fish. In terms of research methodology, with the development of science and technology, tracking techniques using radio telemetry, acoustic telemetry, RFID (radio-frequency identification), satellite tracking, and geolocators are widely used to study seabird and fish migration. Research is also conducted indirectly through a population survey and the analysis of substances in the body. Research contents are largely classified into extrinsic factors that affect migration(such as environmental variables and interspecific competition), intrinsic factors such as hormones, anthropogenic activities including fishery and offshore wind farm, and the effect of global climate change. In future studies, physiological factors that influence or cause migration and dispersal should be identified concerning intrinsic factors. For the analysis of migration ability, it is necessary to study effects of changes in the magnetic field on the migration ability of seabirds and fish, interspecific differences in spatiotemporal migration ability, and factors that influence the migration success rate. Regarding extrinsic factors, research studies on effects of anthropogenic disturbances such as fishery and offshore wind farm and global climate change on the migration and dispersal patterns of marine animals are needed. Finally, integrated studies on the migration of seabirds and fish directly or indirectly affecting each other in various ecological aspects are required.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.3
• /
• pp.188-202
• /
• 2011

Due to emissions of greenhouse gases caused by increased use of fossil fuels, the climate change has been detected and this phenomenon would affect even larger changes in temperature and precipitation of South Korea. Especially, the increase of temperature by climate change can affect the amount and pattern of snowfall. Accordingly, we tried to predict future snowfall and the snowfall pattern changes by using the downscaled GCM (general circulation model) scenarios. Causes of snow varies greatly, but the information provided by GCM are maximum / minimum temperature, rainfall, solar radiation. In this study, the possibility of snow was focused on correlation between minimum temperatures and future precipitation. First, we collected the newest fresh snow depth offered by KMA (Korea meteorological administration), then we estimate the temperature of snow falling conditions. These estimated temperature conditions were distributed spatially and regionally by IDW (Inverse Distance Weight) interpolation. Finally, the distributed temperature conditions (or boundaries) were applied to GCM, and the future snowfall was predicted. The results showed a wide range of variation for each scenario. Our models predict that snowfall will decrease in the study region. This may be caused by global warming. Temperature rise caused by global warming highlights the effectiveness of these mechanisms that concerned with the temporal and spatial changes in snow, and would affect the spring water resources.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.49 no.2
• /
• pp.113-121
• /
• 2012

In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.16 no.1
• /
• pp.14-26
• /
• 2011

Surface currents were observed by high-frequency (HF) radars off the Keum River estuary from December 2008 to February 2009. The dataset of observed surface currents had data gaps due to the interference of electromagnetic waves and the deteriorating weather conditions. To fill the data gaps an optimal interpolation procedure was developed. The characteristics of spatial correlation in the surface currents off the Keum River estuary were investigated and the spatial data gaps were filled using the optimal interpolation. Then, the temporal and spatial distribution of the interpolated surface currents and the patterns of interpolation error were examined. The correlation coefficients between the surface currents in the coastal region were higher than 0.7 because tidal currents dominate the surface circulation. The sample data covariance matrix (C), spatially averaged covariance matrix with localization ($C^G_{sm}$) and covariance matrix fitted by an exponential function ($C_{ft}$) were used to interpolate the original dataset. The optimal interpolation filled the data gaps and suppressed the spurious data with spikes in the time series of surface current speed so that the variance of the interpolated time series was smaller than that of the original data. When the spatial data coverage was larger (smaller) than 70% of the region, the interpolation error produced by $C^G_{sm}$ ($C_{ft}$) was smaller compared with that by C.

• Spatial Information Research
• /
• v.22 no.5
• /
• pp.65-75
• /
• 2014

Bus headway plays an important role not only in determining the passenger waiting time and bus service quality, but also in influencing the bus operation cost and passenger demand. Previous research on headway control has considered only an hourly difference in the distribution of ridership between peak and non-peak hours. However, this approach is too simple to help manage ridership demand fluctuations in a short time scale; thus passengers' waiting cost will be generated when ridership demand exceeds the supply of bus services. Moreover, bus ridership demand varies by station location and traffic situation. To address this concern, we propose a headway control algorithm for minimizing the waiting time cost by using Smart Card data. We also provide proof of the convergence of the algorithm to the desired headway allocation using a set of preconditions of political waiting time guarantees and available fleet constraints. For model verification, the data from the No. 143 bus line in Seoul were used. The results show that the total savings in cost totaled approximately 600,000 won per day when we apply the time-value cost of waiting time. Thus, we can expect that cost savings will be more pronounced when the algorithm is applied to larger systems.

• Journal of the Economic Geographical Society of Korea
• /
• v.15 no.1
• /
• pp.26-41
• /
• 2012

This study investigates the time-space characteristics of intra-urban passenger flows in the Metropolitan Seoul area. In particular, we analyze the relationships between transit ridership and land use through the use of the subway passenger flow data obtained from the transit transaction databases. For this purpose, the strength of each subway station, i.e., the number of total in-coming and out-going passengers at each station, in the morning, afternoon, and evening, is calculated and visualized, which reflects urban land use patterns. Then the subway stations are classified into four groups via a hierarchical analysis of the in-coming and out-going passenger flows at 353 stations. Each group appears to have characteristic properties according to the region, e.g., residential areas and central business districts. This has been confirmed by the analysis which probes explicitly the relationship between the local socio-economic variables and station groups. This analysis, disclosing the inter-relationship between the subway network and urban land use, may be useful at various stages in urban as well as transportation planning, and provides analytical tools for a wide spectrum of applications ranging from impact evaluation to decision-making and planning support.

• Journal of Korea Water Resources Association
• /
• v.57 no.3
• /
• pp.165-179
• /
• 2024

It is crucial to have a comprehensive understanding of inundation and water cycle in urban areas for mitigating flood risks and sustainable water resources management. In this study, we developed a Cellular Automata-based integrated Water cycle model (CAW). A comparative analysis with physics-based and conventional cellular automata-based models was performed in an urban watershed in Portland, USA, to evaluate the adequacy of spatiotemporal inundation simulation in the context of a high-resolution setup. A high similarity was found in the maximum inundation maps by CAW and Weighted Cellular Automata 2 Dimension (WCA2D) model presumably due to the same diffuse wave assumption, showing an average Root-Mean-Square-Error (RMSE) value of 1.3 cm and high scores of binary pattern indices (HR 0.91, FAR 0.02, CSI 0.90). Furthermore, through multiple simulation experiments estimating the effects of land cover and soil conditions on inundation and infiltration, as the impermeability rate increased by 41%, the infiltration decreased by 54% (4.16 mm/m²) while the maximum inundation depth increased by 10% (2.19 mm/m²). It was expected that high-resolution integrated inundation and water cycle analysis considering various land cover and soil conditions in urban areas would be feasible using CAW.