Hong, Seung Hwan;Sohn, Hong Gyoo;Kim, Sang Pil;Jang, Hyo Seon
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.31
no.6_1
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pp.447-454
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2013
The geolocation accuracy of SAR satellite imagery is affected by orbit and sensor information and external variables such as DEM accuracy and atmospheric delay. To predict geolocation accuracy of KOMPSAT-5 and KOMPSAT-6, this paper uses TerraSAR-X imagery which has similar spec. Simulation data for sensitivity analysis are generated using range equation and doppler equation with several key error sources. As a result of simulation analysis, the effect of sensor information error is larger than orbit information error. Especially, onboard electronic delay needs to be monitored periodically because this error affects geolocation accuracy of slant range direction by 30m. Additionally, DEM accuracy causes geolocation error by 20~30m in mountainous area and atmospheric delay can occur by 5m in response to atmospheric condition and incidence angle.
In Korea, more than 60% of the whole lands are mountainous area. Since many decades ago, hydroelectric power plants have been constructed and eco-friendly energy has been produced. Hydropower can cope with the rapidly changing energy supply and demand, and produce eco-friendly energy. However, when the reservoir is built, it is often inevitable to damage the environment due to construction of large structure. In this study, the optimal reservoir operation model was developed to maximize power generation by monthly operation for long-term operation planning. The dam operation model was developed using the linear programming which is widely used in the optimal resources allocation problems. And the reservoir operation model can establish monthly operation plan for 1 year. Linear programming requires both object function and constraints to be linear. However, since the power generation equation is nonlinear, it is linearized using the Taylor Expansion technique. The optimization results were compared with the 2009-2018 historical data of five hydropower reservoirs. As a result, the total optimal generation is about 10~37% higher than the historical generation.
In hydrologic modeling, prediction uncertainty generally stems from various uncertainty sources associated with model structure, data, and parameters, etc. This study aims to assess the parameter uncertainty effect on hydrologic prediction results. For this objective, a distributed rainfall-sediment yield-runoff model, which consists of rainfall-runoff module for simulation of surface and subsurface flows and sediment yield module based on unit stream power theory, was applied to the mesoscale mountainous area (Cheoncheon catchment; 289.9 $km^2$). For parameter uncertainty evaluation, the model was calibrated by a multi-objective optimization algorithm (MOSCEM) with two different objective functions (RMSE and HMLE) and Pareto optimal solutions of each case were then estimated. In Case I, the rainfall-runoff module was calibrated to investigate the effect of parameter uncertainty on hydrograph reproduction whereas in Case II, sediment yield module was calibrated to show the propagation of parameter uncertainty into sedigraph estimation. Additionally, in Case III, all parameters of both modules were simultaneously calibrated in order to take account of prediction uncertainty in rainfall-sediment yield-runoff modeling. The results showed that hydrograph prediction uncertainty of Case I was observed over the low-flow periods while the sedigraph of high-flow periods was sensitive to uncertainty of the sediment yield module parameters in Case II. In Case III, prediction uncertainty ranges of both hydrograph and sedigraph were larger than the other cases. Furthermore, prediction uncertainty in terms of spatial distribution of erosion and deposition drastically varied with the applied model parameters for all cases.
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.3
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pp.155-160
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2018
The unmanned aerial vehicle (UAV) is used in various fields, such as land surveying, facility management, and disaster monitoring and restoration because it has low operational costs, fast data acquisition, and can generate a digital surface model (DSM). Recently, the UAV has been applied to process management in construction projects. Construction projects are widely distributed not only in urban areas but also in mountainous areas and rural areas where people are rarely in traffic or in vehicles. Projects range from a few hundred meters to several kilometers long. In order to perform a reconnaissance survey, a surveying method using a global positioning system (GPS) or a total station has mainly been used. However, these methods have a disadvantage in that a lot of time is required for data acquisition. This study's purpose is to evaluate the usability of a UAV DSM for surveying a construction area. Data was acquired using the UAV and a three-dimensional (3D) laser scanner, and the DSM of the construction site was created through data processing. The UAV DSM showed accuracy to within 30 cm based on the 3D laser scanner data, and a process comparison between the two work methods was able to present the usability of the UAV DSM in the field of construction surveying. Future utilization of the UAV DSM is expected to greatly improve the efficiency of work in construction projects.
This study was conducted to develope calculation method of standard rainfall, which was used for predicting the outbreaking time of disaster by using Tank model, on warning and evacuation for soil sediment disaster. We investigate adeption possibility of developed method through comparing storage function method with Tank model. We calculated storage amount rainfall by storage function method and Tank model with 36 hillslope failures which have record on outbreaking time of disaster. The result in case of Sedimentary (quarternary period) showed that the difference of outbreaking time was 1.6 hour in case of tank model, but 3.2 hour in case of storage function method. In addition, the deviation of the peak storage were 7% in case of tank model, but 63% in case of storage function method. Total evacuation period was analyzed by using observed 5 years (1993-1997) rainfall data as well as each standard rainfalls which were determinated by two methods. The result showed that evacuation time by storage function method was about twice as many as that by tank model. Therefore, we concluded that calculation by tank model for predicting the outbreaking time of disaster was more useful and accurate than storage function method.
Construction of road closed to mountains is inevitable in Korea because the mountainous region in Korea is more than 70% in area. Recently, due to global warming, typhoons or heavy rainfalls frequently occur, and accordingly, mountain roads are seriously damaged by landslides, debris flows, and uplift pressure below pavement. in this study, damage on pavement by uplift pressure was investigated. Various influencing factors such as slope angle, reinforcement of slope surface, thickness of soil cover underlain by rock, and types of drainage system were considered to evaluate uplift pressure acting on the bottom of pavement. Raising of water table up to the surface of slope may depend on the duration and intensity of rainfall. It shows that the installation of subdrain can reduce the uplift water pressure. Therefore, It is concluded that the use of subdrain system is effective to decrease uplift pressure and cement treated base is more endurable than typical crushed-stone base.
Recently, weather changes in Korea have intensified due to global warming, and the five major natural disasters that occur mostly include heavy rains, typhoons, storms, heavy snow, and earthquakes. Busan is vulnerable to snow disaster, given that the amount of natural disaster damage in Busan accounts for more than 50% of the total amount in the entire metropolitan cities in Korea, and that the Busan area includes many hilly mountains. In this study, we attempted to identify vulnerable areas for snowfall disasters in Busan areas using the geographic information system (GIS) with the data for both geographical and anthropogenic characteristics. We produced the maps of vulnerable areas for evaluating factors that include altitude, slope, land cover, road networks, and demographics, and overlapped those maps to rank the vulnerability to snowfall disasters as the 5th levels finally. To weight each evaluating factor, we used an entropy method. The riskiest areas are characterized by being located in mountainous areas with roads, including Sansung-ro in Geumjeong-gu, Mandeok tunnel in Buk-gu, Hwangnyeongsan-ro in Suyeong-gu, and others, where road restrictions were actually enforced due to snowfall events in the past. This method is simple and easy to be updated, and thus we think this methodology can be adapted to identify vulnerable areas for other environmental disasters.
Korean Journal of Agricultural and Forest Meteorology
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v.9
no.3
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pp.195-202
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2007
The normalized difference in incident solar energy between a target surface and a level surface (overheating index, OHI) is useful in eliminating estimation error of site-specific maximum temperature in complex terrain. Due to the complexity in its calculation, however, an empirical proxy variable called northern exposure index (NEI) which combines slope and aspect has been used to estimate OHI based on empirical relationships between the two. An experiment with real-world landscape and temperature data was carried out to evaluate performance of the NEI - derived OHI (N-OHI) in reduction of spatial interpolation error for daily maximum temperature compared with that by the original OHI. We collected daily maximum temperature data from 7 sites in a mountainous watershed with a $149 km^2$ area and a 795m elevation range ($651{\sim}1,445m$) in Pyongchang, Kangwon province. Northern exposure index was calculated for the entire 166,050 grid cells constituting the watershed based on a 30-m digital elevation model. Daily OHI was calculated for the same watershed ana regressed to the variation of NEI. The regression equations were used to estimate N-OHI for 15th of each month. Deviations in daily maximum temperature at 7 sites from those measured at the nearby synoptic station were calculated from June 2006 to February 2007 and regressed to the N-OHI. The same procedure was repeated with the original OHI values. The ratio sum of square errors contributable by the N-OHI were 0.46 (winter), 0.24 (fall), and 0.01 (summer), while those by the original OHI were 0.52, 0.37 and 0.15, respectively.
During the last century, most scientific questions related to climate change were focused on the evidence of anthropogenic global warming (IPCC, 2001). There are robust evidences of warming and also human-induced climate change. We now understand the global, mean change a little bit better; however, the uncertainties for regional climate change still remains large. The purpose of this study is to understand the past climate change over Korea based on the observational data and to project future regional climate change over East Asia using ECHAM4/HOPE model and MM5 for downscaling. There are significant evidences on regional climate change in Korea, from several variables. The mean annual temperature over Korea has increased about 1.5∼$1.7^{\circ}C$ during the 20th century, including urbanization effect in large cities which can account for 20-30% of warming in the second half of the 20th century. Cold extreme temperature events occurred less frequently especially in the late 20th century, while hot extreme temperature events were more common than earlier in the century. The seasonal and annual precipitation was analyzed to examine long-term trend on precipitation intensity and extreme events. The number of rainy days shows a significant negative trend, which is more evident in summer and fall. Annual precipitation amount tends to increase slightly during the same period. This suggests an increase of precipitation intensity in this area. These changes may influence on growing seasons, floods and droughts, diseases and insects, marketing of seasonal products, energy consumption, and socio-economic sectors. The Korean Peninsular is located at the eastern coast of the largest continent on the earth withmeso-scale mountainous complex topography and itspopulation density is very high. And most people want to hear what will happen in their back yards. It is necessary to produce climate change scenario to fit forhigh-resolution (in meteorological sense, but low-resolution in socio-economic sense) impact assessment. We produced one hundred-year, high-resolution (∼27 km), regional climate change scenario with MM5 and recognized some obstacles to be used in application. The boundary conditions were provided from the 240-year simulation using the ECHAM4/HOPE-G model with SRES A2 scenario. Both observation and simulation data will compose past and future regional climate change scenario over Korea.
The Kunang cave paleolithic site is located at Tanyang [$N37^{\circ}2'$, $128^{\circ}21'E$], Chungbuk Province, which is in the Central part of the Korean peninsula. The cave is developed at 312 amsl in a karstic mountainous area. The South Han River flows across this region and other caves can also be found near the river. The site was discovered in 1986 and excavated 3 times by the Chungbuk National University Museum until now. The cave was wellpreserved from modem human activities until the first discovery. The full length of the cave is estimated to be ca. 140 m. However, a spacious part up to 11 m from the entrance has been excavated. Eight lithological units are divided over the vertical profile at a depth of 5 m. Each unit is deposited in ascending order as follow: mud layer (Unit 9), lower complex (Unit 8) which is composed of angular blocks and fragments with a muddy matrix, lower travertine layer (Unit 7; flowstone), middle complex (Unit 6; cultural layer) which is composed of fragments with a muddy matrix, middle travertine layer (Unit 5; flowstone), yellowish muddy layer (Unit 4), upper complex (Unit 3; cultural layer) which has a similar composition to Unit 8. the upper travertine layer (Unit 2; flowstone), and finally surface soil layer (Unit 1). The most abundant vestiges in the cultural layers are the animal bones. They are small fractured pieces and mostly less than 3 cm in length. About 3,800 bone pieces from 25 animal species have been collected so far, 90 percent of them belonging to young deers. Previous archaeological study of these bone pieces shows thatprehistoric people occupied the cavenot for permanent dwelling but for temporary shelter during their seasonal hunting activity. More extensive studies of these bones together with pollen analysis are in progress to reconstruct the paleoenvironment of this cave. Only a single date (12,500 BP) obtained from a U-Th measurement of the upper travertine layer was previously available. In spite of the importance of the cave stratigraphy, there was no detail chronological investigation to establish the depositional process of the cultural layers and to understand the periodic structure of the cave strata, alternating travertine floor and complex layers. We have measured five 14C age dating (38900+/-1000, 36400+/-900, 40600+/-1600, more than 51000 and 52000 14C BP) using Seoul National University 14C AMS facility, conducted systematic process of the collagen extraction from bone fragments samples. From the result, we estimate that sedimentation rate of the cave earth is constant, and that the travertine layers, Unit 2 and Unit 3, was formed during MIS 5a(ca. 80 kBP) and MIS 5c (ca. 100 kBP) respectively. The Kunang Cave site is located at Yochonli of the region of Danyang in the mid-eastern part of Korea. This region is compased of limestones in which many caves were found and the Nam-han river flows meanderingly. The excavations were carried out three times in 1986, 1988, and 1998.
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