• Journal of Korean Society for Geospatial Information Science
• /
• v.24 no.3
• /
• pp.59-66
• /
• 2016

The 2011 debris flow in Mt. Umyeonsan in Seoul, South Korea caused significant damages to the surrounding urban area, unlike other similar incidents reported to have occurred in the past in the country's mountainous regions. Accordingly, landslides and debris flows cause damage in various surroundings, regardless of mountainous area and urban area, at a great speed and with enormous impact. Hence, many researchers attempted to forecast the extent of impact of debris flows to help minimize the damage. The most fundamental part in forecasting the impact extent of debris flow is to understand the debris flow behavior and sedimentation mechanism in complex three-dimensional topography. To understand sedimentation mechanism, in particular, it is necessary to calculate the amount of energy and erosion according to debris flow behavior. The previously developed debris flow models, however, are limited in their ability to calculate the erosion amount of debris flow. This study calculated the extent of damage caused by a massive debris flow that occurred in 2011 in Seoul's urban area adjacent to Mt. Umyeonsan by using DEM, created from aerial photography and airborne LiDAR data, for both before and after the damage; and developed and compared a debris flow behavioral analysis model that can assess the amount of erosion based on energy theory. In addition, simulations using the existing debris flow model (RWM, Debris 2D) and a comprehensive comparison of debris flow-stricken areas were performed in the same study area.

• Journal of Korea Water Resources Association
• /
• v.43 no.3
• /
• pp.309-323
• /
• 2010

As climate changes and abnormal climates have drawn research interest recently, many countries utilize the GCM, which is based on SRES suggested by IPCC, to obtain more accurate forecast for future climate changes. Especially, many research attempts have been made to simulate localized geographical characteristics by using RCM with the high resolution data globally. To evaluate the impacts of climate and landuse change on water resources in the Han-river basin, we carried out the procedure consisting of the CA-Markov Chain, the Multi-Regression equation using two independent variables of temperature and rainfall, the downscaling technique based on the RegCM3 RCM, and SLURP. From the CA-Markov Chain, the future landuse change is forecasted and the future NDVI is predicted by the Multi-Regression equation. Also, RegCM3 RCM 50 sets were generated by the downscaling technique based on the RegCM3 RCM provided by KMA. With them, 90 year runoff scenarios whose period is from 2001 to 2090 are simulated for the Han-river basin by SLURP. Finally, the 90-year simulated monthly runoffs are compared with the historical monthly runoffs for each dam in the basin. At Paldang dam, the runoffs in September show higher increase than the ones in August which is due to the change of rainfall pattern in future. Additionally, after exploring the impact of the climate change on the structure of water circulation, we find that water management will become more difficult by the changes in the water circulation factors such as precipitation, evaporation, transpiration, and runoff in the Han-river basin.

• Spatial Information Research
• /
• v.19 no.4
• /
• pp.11-20
• /
• 2011

In accordance with low carbon and green growth paradigm, a subway is one of major public transit systems for resolving traffic congestion and decreasing traffic accidents. In addition, as subway networks expand, passengers' travel pattern in the subway network change and consequently affect the urban structure. Generally, new subway route has been planned and developed, mainly considering a travel demand forecast. However, it is desired to conduct an empirical analysis on the forecast model regarding change of travel accessibility and passenger demand pattern according to new subway line. Therefore, in this paper, an alternative method, developed based upon a spatial syntax model, is proposed for evaluating new subway route in terms of passenger's mobility and network accessibility. In a case study, we constructed subway network data, mainly targeting the no 9 subway line opened in 2009. With an axial-map analysis, we calculated spatial characteristics to describe topological movement interface. We then analyzed actual modal shift and change on demand of passengers through the number of subway passenger between subway stations and the number of passenger according to comparative bus line from Smart Card to validate suggested methods. Results show that the proposed method provides quantitative means of visualizing passenger flow in subway route planning and of analyzing the time-space characteristics of network. Also, it is expected that the proposed method can be utilized for predicting a passengers' pattern and its impact on public transportation.

• Tunnel and Underground Space
• /
• v.23 no.6
• /
• pp.480-492
• /
• 2013

After the introduction of geothermal power generation technology based on engineering reservoir creation that can be applied on non-volcanic region, industrial need for studies on the efficient and economic execution of costly deep-depth drilling work becomes manifest increasingly. However, since it is very difficult to predict duration and cost of boring work with acceptable reliability because of many uncertain events during the execution, efficient and organized work management for drilling is not easily achievable. Especially, the round trip that discretely occurs because of the abrasion of bit takes more time as the depth goes deeper and it has a great impact on the work performance. Therefore, a technology that can simulate the occurrence timing and depth of round trip in advance and therefore optimize them is essentially required. This study divided the abrasion state of bit into eight steps for simulation cases and developed a forecast algorithm, i.e., TOSA which can analyze the depth and timing of round trip occurrence. A methodology that can divide a unit section for simulation has been suggested; while the Bourgoyne and Young model has been used for the forecast of drilling rates and bit abrasion extent by section. Lastly, the designed algorithm has been systemized for the convenience of the user.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.4
• /
• pp.50-63
• /
• 2018

The rapid urbanization had led to a distortion of natural hydrological cycle system. The change in hydrological cycle structure is causing streamflow depletion, changing the existing use tendency of water resources. To manage such phenomena, a streamflow depletion impact assessment technology to forecast depletion is required. For performing such technology, it is indispensable to build GIS-based spatial data as fundamental data, but there is a shortage of related research. Therefore, this study was conducted to use the use of GIS-based time series spatial data for streamflow depletion assessment. For this study, GIS data over decades of changes on a national scale were constructed, targeting 6 streamflow depletion impact factors (weather, soil depth, forest density, road network, groundwater usage and landuse) and the data were used as the basic data for the operation of continuous hydrologic model. Focusing on these impact factors, the causes for streamflow depletion were analyzed depending on time series. Then, using distributed continuous hydrologic model based DrySAT, annual runoff of each streamflow depletion impact factor was measured and depletion assessment was conducted. As a result, the default value of annual runoff was measured at 977.9mm under the given weather condition without considering other factors. When considering the decrease in soil depth, the increase in forest density, road development, and groundwater usage, along with the change in land use and development, and annual runoff were measured at 1,003.5mm, 942.1mm, 961.9mm, 915.5mm, and 1003.7mm, respectively. The results showed that the major causes of the streaflow depletion were lowered soil depth to decrease the infiltration volume and surface runoff thereby decreasing streamflow; the increased forest density to decrease surface runoff; the increased road network to decrease the sub-surface flow; the increased groundwater use from undiscriminated development to decrease the baseflow; increased impervious areas to increase surface runoff. Also, each standard watershed depending on the grade of depletion was indicated, based on the definition of streamflow depletion and the range of grade. Considering the weather, the decrease in soil depth, the increase in forest density, road development, and groundwater usage, and the change in land use and development, the grade of depletion were 2.1, 2.2, 2.5, 2.3, 2.8, 2.2, respectively. Among the five streamflow depletion impact factors except rainfall condition, the change in groundwater usage showed the biggest influence on depletion, followed by the change in forest density, road construction, land use, and soil depth. In conclusion, it is anticipated that a national streamflow depletion assessment system to be develop in the future would provide customized depletion management and prevention plans based on the system assessment results regarding future data changes of the six streamflow depletion impact factors and the prospect of depletion progress.

• Journal of Korean Society of Transportation
• /
• v.33 no.3
• /
• pp.294-303
• /
• 2015

This paper describes a method that can be used for estimating future carbon emissions and environmental effects. To forecast future land use and transportation changes under various low carbon policies, a DELTA and OmniTRANS combination (a land use-transport integrated model) was applied. Appropriate emission estimation methods and dispersion models were selected and applied in the method. It was designed that the estimated emissions from land use and transportation activity as well as the estimated concentrations of air pollutants and comprehensive air quality index (CAI) are presented on a GIS-based map. The prototype was developed for the city of Suwon and the outcome examples were presented in this paper; it demonstrates what kinds of analysis results are presented in this method. It is expected that the developed method will be very useful for decision makers who want to know the effect of environmental policies in cities.

• Atmosphere
• /
• v.26 no.3
• /
• pp.401-412
• /
• 2016

A 3D sonic anemometer has been installed at Yongpyong alpine slope since Oct. 23th 2014 to observe the slope winds and to analyze turbulent characteristics with the change in surface cover (grass and snow) and the synoptic wind strength. Eddy covariance method has been applied to calculate the turbulent quantity after coordinate transformation of a planar-fit rotation. We have carefully selected 3 good episodes in the winter season (23 October 2014 to 28 February 2015) for each category (9 days in total), such as grass and snow covers in case of weak synoptic wind condition, and grass cover of strong synoptic wind. The diurnal variations of the slope winds were well developed like the upslope wind in the daytime and downslope wind in the nighttime for both surface covers (grass and snow) in the weak synoptic forcing, when accordingly both heat and momentum fluxes significantly increased in the daytime and decreased in the nighttime. Meanwhile, diurnal variation of heat flux was not present on the snow cover probably in associated with significant fraction of sunlight reflection due to high albedo especially during the daytime in comparison to those on the grass cover. In the strong synoptic regime, the most dominant feature at Yongpyong, only the southeasterly downslope winds were steadily generated irrespective of day and night with significant increases in momentum flux and turbulent kinetic energy as well, which could suggest that local circulations are suppressed by the synoptic scale forcing. In spite of only one season analysis applied to the limited domain, this kind of an observation-based study will provide the basis for understanding of the local wind circulation in the complex mountain domain such as Gangwon in Korea.

• Journal of Internet Computing and Services
• /
• v.21 no.5
• /
• pp.119-127
• /
• 2020

As the electric vehicle (EV) market in South Korea grows, it is required to expand charging facilities to respond to rapidly increasing EV charging demand. In order to conduct a comprehensive facility planning, it is necessary to forecast future demand for electricity and systematically analyze the impact on the load capacity of facilities based on this. In this paper, we design and develop a Long Short-Term Memory (LSTM) neural network model that predicts the daily peak electric load at each charging station using the EV charging data of KEPCO. First, we obtain refined data through data preprocessing and outlier removal. Next, our model is trained by extracting daily features per charging station and constructing a training set. Finally, our model is verified through performance analysis using a test set for each charging station type, and the limitations of our model are discussed.

• Journal of Climate Change Research
• /
• v.7 no.3
• /
• pp.325-334
• /
• 2016

We projected the distribution of Hedera rhombea, an evergreen broad-leaved climbing plant, under current climate conditions and predicted its future distributions under global warming. Inaddition, weexplained model uncertainty by employing 9 single Species Distribution model (SDM)s to model the distribution of Hedera rhombea. 9 single SDMs were constructed with 736 presence/absence data and 3 temperature and 3 precipitation data. Uncertainty of each SDM was assessed with TSS (Ture Skill Statistics) and AUC (the Area under the curve) value of ROC (receiver operating characteristic) analyses. To reduce model uncertainty, we combined 9 single SDMs weighted by TSS and resulted in an ensemble forecast, a TSS weighted ensemble. We predicted future distributions of Hedera rhombea under future climate conditions for the period of 2050 (2040~2060), which were estimated with HadGEM2-AO. RF (Random Forest), GBM (Generalized Boosted Model) and TSS weighted ensemble model showed higher prediction accuracies (AUC > 0.95, TSS > 0.80) than other SDMs. Based on the projections of TSS weighted ensemble, potential habitats under current climate conditions showed a discrepancy with actual habitats, especially in the northern distribution limit. The observed northern boundary of Hedera rhombea is Ulsan in the eastern Korean Peninsula, but the projected limit was eastern coast of Gangwon province. Geomorphological conditions and the dispersal limitations mediated by birds, the lack of bird habitats at eastern coast of Gangwon Province, account for such discrepancy. In general, potential habitats of Hedera rhombea expanded under future climate conditions, but the extent of expansions depend on RCP scenarios. Potential Habitat of Hedera rhombea expanded into Jeolla-inland area under RCP 4.5, and into Chungnam and Wonsan under RCP 8.5. Our results would be fundamental information for understanding the potential effects of climate change on the distribution of Hedera rhombea.

• Atmosphere
• /
• v.33 no.1
• /
• pp.21-32
• /
• 2023

Characteristics of downslope windstorm (DW) has been examined mainly based on 1-min average wind and the other meteorological conditions in the Yeongdong region for 2000~2020. First, a classification procedure for the downslope windstorm is proposed using surface wind speed (greater than 99 percentile), 1-hour longevity of strong wind (SW), westerly wind direction, low humidity (less than 20 percentile), and leeside warming. The number of DW days satisfying the proposed criteria is 221 (2.9% of total days and 47.5% of SW days) while the number of SW days is 465 (6.1% of total days) for 2000~2020. The occurrences of both SW and DW shows distinctive annual variation with its peak in April. In addition, mean wind speed of DW days is 8.2 m s^-1 with its duration of 2 hr 30 min and relative humidity of 28% at Gangneung. An episode (7 May 2021) was selected by applying the proposed criteria to SW days of 2021. The sounding shows that the layer of wind speed greater than 25 m s^-1 was lowered down to 925 hPa at Gangneung (leeside) relative to 850 hPa at Hoengseong (Wonju), in the afternoon along with significant warming and drying. Froude numbers of Wonju and Gangneung for the DW events were increased 4 and 5 times greater than those of normal days, respectively. This kind of DW long-term statistics in the leeside of the mountains is thought to build a foundation of further understanding DW mechanism.