• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.4
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• pp.261-265
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• 2003

Cold air accumulation plays a critical role in formulating daily minimum temperature in complex terrain on radiative cooling nights, and spatial interpolation can be improved by accommodating this important topoclimatic variable. Little is known about the spatial scale for computing cold air accumulation which influences daily minimum temperature. Air temperature was measured at 10-minute intervals during September 2002- February 2003 at eight locations within a 1 by 1 km hilly orchard area. Minimum temperature data for suspected radiative cooling nights were collected, and the deviations from reference observations at a near-by KMA automated weather station were calculated. A digital elevation model with a 10m cell size was used to calculate the cold air accumulation at 8 locations. Zonal averages of the cold air accumulation were computed for each location by increasing the cell radius from 1 to 10. Temperature deviations were regressed to a common logarithm of the smoothed averages of cold air accumulation to derive a linear relationship between the local temperature deviation and the site topography. The highest coefficient of determination ($r^2$ = 0.78) was found at a cell radius of 5, which corresponds to an approximately 1 ha boundary surrounding the point of interest.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.17-36
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• 1998

The Radon transform has been widely used in various techniques of digital image processing such as the computerized topography, lineament analysis in a remotely sensed image, slant-stack processing of seismic data, and so on. Compared to the Fourier transform, the utility of two-dimensional convolutional or correlational properties of the Radon transform, however, has been underestimated. We show that the two-dimensional convolution and correlation is respectively reduced to be one-dimensional convolution and correlation with respect to ρ in the Radon space. Therefore, one can achieve a two dimensional filtering by applying a simple one-dimensional convolution in the Radon space followed by an inverse Radon transform. Tests of the approach using FIR filters are carried out specifically for enhancing the ship wake in a RADARSAT SAR image. The test results demonstrate that the two-dimensional filtering through the Radon transform effectively enhance the ship wake features as well as reducing sea speckle in the image. Although two-dimensional convolution and correlation through the Radon transform are not so much useful as those through the courier transform in views of efficiency and effectiveness, it can be utilized to improve the quality of a digitally processed output when the process should be accompanied by the Radon transform such as topography and lineament analysis of SAR image.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.2
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• pp.72-78
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• 2009

The demand for rainfall data in gridded digital formats has increased in recent years due to the close linkage between hydrological models and decision support systems using the geographic information system. One of the most widely used tools for digital rainfall mapping is the PRISM (parameter-elevation regressions on independent slopes model) which uses point data (rain gauge stations), a digital elevation model (DEM), and other spatial datasets to generate repeatable estimates of monthly and annual precipitation. In the PRISM, rain gauge stations are assigned with weights that account for other climatically important factors besides elevation, and aspects and the topographic exposure are simulated by dividing the terrain into topographic facets. The size of facet or grid cell resolution is determined by the density of rain gauge stations and a $5{\times}5km$ grid cell is considered as the lowest limit under the situation in Korea. The PRISM algorithms using a 270m DEM for South Korea were implemented in a script language environment (Python) and relevant weights for each 270m grid cell were derived from the monthly data from 432 official rain gauge stations. Weighted monthly precipitation data from at least 5 nearby stations for each grid cell were regressed to the elevation and the selected linear regression equations with the 270m DEM were used to generate a digital precipitation map of South Korea at 270m resolution. Among 1.25 million grid cells, precipitation estimates at 166 cells, where the measurements were made by the Korea Water Corporation rain gauge network, were extracted and the monthly estimation errors were evaluated. An average of 10% reduction in the root mean square error (RMSE) was found for any months with more than 100mm monthly precipitation compared to the RMSE associated with the original 5km PRISM estimates. This modified PRISM may be used for rainfall mapping in rainy season (May to September) at much higher spatial resolution than the original PRISM without losing the data accuracy.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.481-490
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• 2018

Recently, the spatiotemporal patterns of flood disasters have become more complex and unpredictable due to climate change. Flood hazard map including information on flood risk level has been widely used as an unstructured measure against flooding damages. In order to product a high-precision flood hazard map by combination of hydrologic and hydraulic modeling, huge digital information such as topography, geology, climate, landuse and various database related to social economic are required. However, in some areas, especially in developing countries, flood hazard mapping is difficult or impossible and its accuracy is insufficient because such data is lacking or inaccessible. Therefore, this study suggests a method to delineate large scale flood-prone area based on topographic factors produced by linear binary classifier and ROC (Receiver Operation Characteristics) using globally-available geographic data such as ASTER or SRTM. We applied the proposed methodology to five different countries: North Korea Bangladesh, Indonesia, Thailand and Myanmar. The results show that model performances on flood area detection ranges from 38% (Bangladesh) to 78% (Thailand). The flood-prone area detection based on the topographical factors has a great advantage in order to easily distinguish the large-scale inundation-potent area using only digital elevation model (DEM) for ungauged watersheds.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.675-686
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• 2021

This study investigated the ground displacement occurring in a slope below a waste-rock dumping site and estimated the likelihood of a disaster due to a landslide. To start with, photogrammetry was conducted by unmanned aerial vehicles (UAVs) to investigate the size and extent of the ground displacement. From April 2019 to July 2020, the average error rate of the five UAV surveys was 0.011-0.034 m, and an elevation change of 2.97 m occurred due to the movement of the soil layer. Only some areas of the slope showedelevation change, and this was believed to be due to thegroundwater generated during rainfall rather than the effect of the waste-rock load at the top. Sensitivity analysis for LS-RAPID simulation was performed, and the simulation results were compared and analyzed by applying a digital elevation model (DEM) and a digital surface model (DSM)as terrain data with 10 m, 5 m, and 4 m grids. When data with high spatial resolution were used, the extent of the sedimentation of landslide material tended to be excessively expanded in the DEM. In contrast, in the result of applying a DSM, which reflects the topography in detail, the diffusion range was not significantly affected even when the spatial resolution was changed, and the sedimentation behavior according to the river shape could be accurately expressed. As a result, it was concluded that applying a DSM rather than a DEM does not significantly expand the sedimentation range, and results that reflect the site situation well can be obtained.

• Ocean and Polar Research
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• v.36 no.2
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• pp.87-101
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• 2014

Recently, more attention has been paid to the geomorphological changes in the Nakdong River Estuary, because those changes are caused by artificial activities including weirs, reclamation and construction. In order to analyze quantitatively the recent geomorphological variability in the Nakdong River Estuary, we surveyed the depth and elevation of submarine topography near Jinwoodo and Sinjado from March 2007 to February 2012. A statistical method (based on Digital Shoreline Analysis System) and an Empirical Orthogonal Functions method were used to evaluate the morphological changes. According to the statistical variables (DCE, NDC, EPR, LRR), the highest amount and rate of accumulation were recorded around the Gadeokdo whereas the greatest amount of erosion appeared around the coast off the eastern part of Sinjado. In particular, a dynamic variation of morphology was clearly observed in the vicinity of the sub-tidal channel located between Jinwoodo and Sinjado, which seems to be attributable to channel migration. As a result of the EOF method, the first mode (48.7%) is most closely related to the pattern of morphological variability that might be associated with the westerly movement of sediment by longshore current. The spatial variability of the second mode (16.6%) was high in the shoreface of Sinjado, showing a 4-year periodicity of temporal variability. The strong correlation (coefficient 0.73) between the time coefficient and suspended sediment discharge from Nakdong River emphasizes the role of sediment discharge to deposition in this area. The spatial variability of the third mode (11.3%) was distributed mainly around the coast off the eastern part of Sinjado, which is related to the movement of the coastline of Sinjado. Based on the last 5 year's data, our results suggest that the study area is characterized on the whole by a depositional pattern, but the extent of sedimentation is different locally.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.121-131
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• 2008

Two dimensional road design is connoting danger factor because different point between design standard and driver's reaction. Consequently two dimensional road design is difficult to recognize problem that happen beforehand when before construction. Therefore three dimensional road design that can grasp problem after completion is required. In this study, three dimensional road was designed to evaluate road that is designed. Road designed by Inroad that is road design program. DTM is created using digital map and elevation data. Three dimensional road was designed by integrated DTM of road and topography. Road design evaluation was performed in three dimension. Driving simulation and sight distance assessment were carried out to estimate stability of alignment. Shadow simulation was executed on icy road section for bad section of icy road surface. As a result of evaluation, this study could confirm shape of road after completion. And sight distance could be calculated and visually confirmed. Also, icy road sections were extracted through shadow simulation.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.184-189
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• 2004

A soil moisture measuring method for a hillslope of Korean watershed was developed to configure spatial-temporal distribution of soil moisture. Intensive surveying of topography had been performed to make a refined digital elevation model(DEM) and the hydrological interpretation from flow distribution algorithm was incorporated through reverse surveying. Moreover, A long term measurement system was established to maximize representative features of spatial variation of soil moisture and operated from October 19 to 21, 2003. TDR(Time Domain Reflectometry) with a multiplex monitoring system has been operated for accurate measurements. Measurements were performed at the right side hillslope of Buprunsa located at the sulmachun watershed. The data of temporal and spatial soil moisture variation by rainfall event were collected and the variations of soil moisture were well captured.

• Journal of the Korean association of regional geographers
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• v.12 no.2
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• pp.281-290
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• 2006

Map uses graphic language of dot, line and area to represent surface of the earth. Map has been adopted as tools for regional and cartography learning to improve graphicacy in geography education. Due to the rapid development in GIS and internet, practical use of maps has been extended in various study area. This Study is to develope web-based leaning materials for self-controled geography instruction. As learning materials for this aim, it has been constructed WebGIS for topography and thematic maps with boundary map of Chungbuk, digital map of Jochiwon(1:25,000), statistic data and field images. Function of WebGIS intend to improve skills on geo-information collection and spatial query, regional difference of spatial distribution. Individual learning using internet can make an improvement of learner centeredness and problem-solving. Finally, it will be expected to be suggest one of the education guide as blueprint in info-society.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.47-57
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• 2010

The aim of this study is to detect landslide using digital aerial photography and apply the landslide to landslide susceptibility mapping by artificial neural network (ANN) and geographic information system (GIS) at Jinbu area where many landslides have occurred in 2006 by typhoon Ewiniar, Bilis and Kaemi. Landslide locations were identified by visual interpretation of aerial photography taken before and after landslide occurrence, and checked in field. For landslide susceptibility mapping, maps of the topography, geology, soil, forest, lineament, and landuse were constructed from the spatial data sets. Using the factors and landslide location and artificial neural network, the relative weight for the each factors was determinated by back-propagation algorithm. As the result, the aspect and slope factor showed higher weight in 1.2-1.5 times than other factors. Then, landslide susceptibility map was drawn using the weights and finally, the map was validated by comparing with landslide locations that were not used directly in the analysis. As the validation result, the prediction accuracy showed 81.44%.