• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• Journal of Computing Science and Engineering
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• v.2 no.1
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• pp.98-108
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• 2008

Terrain reconstruction from images is an ill-posed, yet commonly desired Structure from Motion task when compositing visual effects into live-action photography. These surfaces are required for choreography of a scene, casting physically accurate shadows of CG elements, and occlusions. We present a novel framework for generating the geometry of landscapes from extremely noisy point cloud datasets obtained via limited resolution techniques, particularly optical flow based vision algorithms applied to live-action video plates. Our contribution is a new statistical approach to remove erroneous tracks ('outliers') by employing a unique combination of well established techniques-including Gaussian Mixture Models (GMMs) for robust parameter estimation and Radial Basis Functions (REFs) for scattered data interpolation-to exploit the natural constraints of this problem. Our algorithm offsets the tremendously laborious task of modeling these landscapes by hand, automatically generating a visually consistent, camera position dependent, thin-shell surface mesh within seconds for a typical tracking shot.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.3
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• pp.99-105
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• 2008

The analysis of LOS(Line-Of-Sight) is defined as an "unobstructed view between two points". The LOS results may be influenced by terrain source, algorithm/interpolation method, etc. In the area denies any access and flight over, LOS results would be doubtful because of low precision of terrain data therefore have limitations of referring to many military applications. Using LIDAR data, LOS Analysis was performed by changing DTED resolution(1$\sim$30m) and LOS distance(50$\sim$2000m). The results of experiment shows that LOS analysis for small area, such as DMZ surveillance, were heavily influenced by DTED resolution.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.12 no.2
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• pp.219-226
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• 1994

When a route is planned, the distance of route and earthwork volume have an important role as an economic factor. In this paper, an investigation is made on the selection of optimum route with respect to two factors above mentioned. For this investigation, a numerical test is also executed to two different types of terrain, i.e. terrain with constant slope and no undulation and terrain with slope and undulation. The results show that the shortest route is determined by the degree of undulation with no relation to the slope of topographic model, and the earthwork volume is affected by the amount of undulation and interpolation function.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.207-213
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• 1997

The purpose of this study is to aim at presenting efficient technique of 3-D Terrain Modelling through multilateral approach methods and to compare with raw data, using low-densed randomly located point data. The subject religion of this study are selected two sites and take into consideration for degree of freedom about low-densed randomly located point data. The result of this study by precision analysis of digital cartographic map-ping using low-densed randomly located point data bave shown that . First, making digital cartographic map, the technique of making it using low-desned randomly located point data by TIN-based results to good and fast run-time in A and B sites all together. Second, the visualization analysis results of digital cartographic map using TIN and GRID-based terrain modeling techniqus similar exacts A and B sites, but the terrain modeling techniqus by TIN-based are small data size than GRID-based with the data with the data size of saving with DXF files. Third, making digital catographic map using terrain modeling techniques by Grid-based, the standard errors of low-densed randomly located point data and interpolated data using gridding method have more good results by radial basis function interpolation techniques at A and B sites all together.

• The Korean Journal of Ecology
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• v.19 no.5
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• pp.403-416
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• 1996

Global natural vegetation mapping (GNVM) system was developed for estimating potential forest area of the globe. With input of monthly mean temperature and monthly precipitation observed at weather stations, the system spherically interpolates them into 1°×1°grid points on a blobe, converts them into vegetation types, and produces a potential vegetation map and a potenital vegetation area. The spherical interpolation was based on negative exponential function fed from the constant radius stations with oval weighing method which is latitudinally elongated weighing in temperature and longitudinally elongated weighing in precipitation. The temperature values were corrected for altitude by applying a linear lapse-rate (0.65℃ / 100m) with reference to a built-in digital terrain map of the globe. The vegetation classification was based upon Koppen’s sKDICe. The potential forest area is estimated for 6.96 Gha (46.24％) of the global land area (15.05 Gha).

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.110-117
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• 2023

Reconstructing underwater geometry in real time with forward-looking sonar is critical for applications such as localization, mapping, and path planning. Geometrical data must be repeatedly calculated and overwritten in real time because the reliability of the acoustic data is affected by various factors. Moreover, scattering of signal data during the coordinate conversion process may lead to geometrical errors, which lowers the accuracy of the information obtained by the sensor system. In this study, we propose a three-step data processing method with low computational cost for real-time operation. First, the number of data points to be interpolated is determined with respect to the distance between each point and the size of the data grid in a Cartesian coordinate system. Then, the data are processed with a nonlinear interpolation so that they exhibit linear properties in the coordinate system. Finally, the data are transformed based on variations in the position and orientation of the sonar over time. The results of an evaluation of our proposed approach in a simulation show that the nonlinear interpolation operation constructed a continuous underwater geometry dataset with low geometrical error.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.1
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• pp.97-105
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• 2005

In order to reduce the uncertainties and improve the air flow field, objective analysis using asynoptic observational data is chosen as a method that enhances the reality of meteorology. In surficial data and their numerical interpolation for improving the interpretation of meteorological components, objective analysis scheme should perform a smooth interpolation, detect and remove the bad data and carry out internal consistency analysis. For objective analysis technique which related to data reliability and error suppression, we carried out two quality control methods. In site quality control, asynoptic observational data at urban area revealed low representation by the complex terrain and buildings. In case of wind field, it was more effective than temperature field when it were interpolated near waterbody data. Many roads, buildings, subways, vehicles are bring about artificial heat which left out of consideration on the simulation of air flow field. Therefore, in temperature field, objective analysis for more effective result was obtained when surficial data were interpolated as many as possible using value quality control rather than the selection of representative site.

• Journal of the Korean association of regional geographers
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• v.11 no.6
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• pp.530-542
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• 2005

In this study, GIS method has been used to get fractal characteristics. Using the projected area and surface area, 2 dimensional fractal characteristic of terrain was found out. Correlation of fractal dimension and mean slope were also checked over. Results are as below. 1) To get a fractal dimension, the method which is using the surface area is also directly proportional to complexity of the terrain as other fractal dimension. 2) Fractal dimensions using the surface area, that is proposed in this thesis are carried out as below : Uiseong : $2.02{\sim}2.15$ Yeongcheon : $2.10{\sim}2.24$. These values are in a range of fractal $2.10{\sim}2.20$ dimensions which has known. 3) Correlation of mean slope and fractal dimension is diminished about 30% in a region which is more than $25^{\circ}$ of mean slope. So, in this region using the fractal dimension method is better than using the mean slope. From this study, on formula using the projected area and surface area is still good to get a fractal dimension that has been found. But to confirm this method the region of research should be wider and be set up the correlation of mean slope, surface area and fractal dimension. It can be applicable to restoration of terrain and traffic flow analysis in the future research.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.499-506
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• 2019

NDSM (Normalized Digital Surface Model) is key information for the detailed analysis of remote sensing data. Although NDSM can be simply obtained by subtracting a DTM (Digital Terrain Model) from a DSM (Digital Surface Model), in case of UAV (Unmanned Aerial Vehicle) data, it is difficult to get an accurate DTM due to high resolution characteristics of UAV data containing a large number of complex objects on the ground such as vegetation and urban structures. In this study, RGB-based UAV vegetation index, ExG (Excess Green) was used to extract initial seed points having low ExG values for region growing such that a DTM can be generated cost-effectively based on high resolution UAV data. For this process, local window analysis was applied to resolve the problem of erroneous seed point extraction from local low ExG points. Using the DSM values of seed points, region growing was applied to merge neighboring terrain pixels. Slope criteria were adopted for the region growing process and the seed points were determined as terrain points in case the size of segments is larger than 0.25 ㎡. Various slope criteria were tested to derive the optimized value for UAV data-based NDSM generation. Finally, the extracted terrain points were evaluated and interpolation was performed using the terrain points to generate an NDSM. The proposed method was applied to agricultural area in order to extract the above ground heights of crops and check feasibility of agricultural monitoring.