• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.3B
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• pp.193-201
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• 2012

In the last decade, heavy rainfall induced debris flow events have been remarkably occurred in Korea. Consequently, debris flow is becoming one of the most dangerous natural phenomena in mountainous area. Understanding and correct predicting of the runout distance of debris flow is an essential prerequisite for developing debris flow hazard map and prevention technology. Based on the simple and widely used sled model, in this study, we analyse the net efficiency of debris flows which is a dimensionless constant (=1/R) and defined by the ratio of the horizontal runout distance L from the debris flow source to deposit and the vertical elevation H of the source above the deposit. The analysis of field data observed in total 238 debris flow events occurred from 2002 to 2011 reveals that the representative value of the net efficiency of debris flows in Korea is 4.3. The data observed in Gangwon province where is the most debris flow-prone area in Korea shows that debris flows in Inje area have the runout distance longer than those in Pyongchang and Gangneung. Overall features of the net efficiency of debris flows observed in the central Korea are similar to those in the southern Korea. The estimation based on aerial photographs and available depositional conditions appears to overestimate the net efficiency compared to estimation based on the field observations, which indicates that appropriate depositional conditions need to be developed for debris flows in Korea.

• Journal of Korean Society of Forest Science
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• v.98 no.4
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• pp.409-416
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• 2009

Forest biomass estimation is essential for greenhouse gas inventories and terrestrial carbon accounting. Remote sensing allows for estimating forest biomass over a large area. This study was conducted to estimate forest biomass and to produce a forest biomass map for Muju county using forest biomass conversion table developed by field plot data from the 5th National Forest Inventory and Landsat TM-5. Correlation analysis was carried out to select suitable independent variables for developing regression models. It was resulted that the height class, crown closure density, and age class were highly correlated with forest biomass. Six regression models were used with the combination of these three stand variables and verified by validation statistics such as root mean square error (RMSE) and mean bias. It was found that a regression model with crown closure density and height class (Model V) was better than others for estimating forest biomass. A biomass conversion table by model V was produced and then used for estimating forest biomass in the study site. The total forest biomass of the Muju county was estimated about 8.8 million ton, or 128.3 ton/ha by the conversion table.

• Journal of The Geomorphological Association of Korea
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• v.18 no.1
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• pp.41-56
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• 2011

This study analyzes the change in land-cover based on satellite imagery to draw up land-cover map in the future, and estimates the change in land category using statistical data of the land category. To estimate land category, this study applied the double exponentially smoothing method. The result of the land cover classification according to year using satellite imagery showed that the type with the largest increase in area of land cover change in the cities of Cheonan and Asan was artificial structure, followed by water, grass field and bare land. However forest, paddy, marsh and dry field were reduced. Further, the result of the time-series analysis of the land category was found to be similar to the result of the land cover classification using satellite imagery. Especially, the result of the estimation of the land category change using the double exponentially smoothing method showed that paddy, dry field, forest and marsh are anticipated to consistently decrease in area from 2010 to 2100, whereas artificial structure, water, bare land and grass field are anticipated to consistently increase. Such results can be utilized as basic data to estimate the change in land cover according to climate change in order to prepare climate change response strategies.

• Journal of IKEEE
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• v.16 no.1
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• pp.7-14
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• 2012

In this paper, a reception rate of terrestrial digital TV broadcasting service is analyzed and a novel method which can estimate the broadcasting coverage rate more objectively and reliably than the existing method is proposed. Previous method measures the reception rate by means of electric field intensity measurement or subjective video quality assessment. Because of limited measuring points, it inherently has measurement error and cannot consider the viewer's receiving conditions in real-time. In order to consider the viewer's population and receiving environment, morphology which characterizes the viewer's receiving environment is extracted using household census data of National Statistical Office and the land cover map of Ministry of Environment. Using the extracted geographical morphology, the reception rate of terrestrial digital TV broadcasting service is calculated with Spectrum Management Intelligence System (SMIs). Proposed method can calculate the reception rate more objectively and reliably than the existing methods because it fully considers the viewer's receiving environments in real-time.

• Journal of the Korean Society of Groundwater Environment
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• v.1 no.2
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• pp.113-120
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• 1994

One of the delicate problems in aquifer management is the identification of the spatial distribution of tile hydrological parameters. The observed data are insufficient to identify the distribution of transmissivities in LAN aquifer. To determine the distribution of the transmissivity in LAN aquifer, it would be required to transform the observed heads at the pilot points into transmissivities. Therefore, three procedures wire tackled for the identification of the spatial distribution of the hydrological parameters; geostatistical estimate of the parameter field on the basis of known well point, heads reconstructed by a numerical model, and modification of the values at pilot points by a minimization algorithm. The variogram of Kriging has been applied to a total of 258 transmissivity value in attempt to quantify their distribution of LAN aquifer. Variogram of the observed and optimized transmissivities at pilot points are adapted to the exponential form. So, it is fitted by theoretical one with coefficients of w=0.623, a=2.743. Values of head obtained through numerical analysis are adjusted to the observed values so that heads have been transformed completely into the transmissivities at the observation wells. The procedure represented contour map of the estimated transmissivities and the calculated head.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.439-448
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• 2020

In this paper, we propose a modified optimization algorithm for point cloud matching of multi-view RGB-D cameras. In general, in the computer vision field, it is very important to accurately estimate the position of the camera. The 3D model generation methods proposed in the previous research require a large number of cameras or expensive 3D cameras. Also, the methods of obtaining the external parameters of the camera through the 2D image have a large error. In this paper, we propose a matching technique for generating a 3D point cloud and mesh model that can provide omnidirectional free viewpoint using 8 low-cost RGB-D cameras. We propose a method that uses a depth map-based function optimization method with RGB images and obtains coordinate transformation parameters that can generate a high-quality 3D model without obtaining initial parameters.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.63-71
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• 2013

This study calculated vegetation indexes such as SR, NDVI, SAVI, and LAI to figure out correlations regarding vegetation by using high resolution KOMPSAT-2 images and LANDSAT images based on the forest biomass distribution map that utilized field survey data, satellite images and LiDAR data and then analyzed correlations between their values and forest biomass. The analysis results reveal that the vegetation indexes of high resolution KOMPSAT-2 images had higher correlations than those of LANDSAT images and that NDVI recorded high correlations among the vegetation indexes. In addition, the study analyzed the characteristics of hyperspectral images by using the COMIS of STSAT-3 and Hyperion images of a similar sensor, EO-1, and further the usability of biomass estimation in hyperspectral images by comparing vegetation index, which had relatively high correlations with biomass, with the vegetation indexes of LANDSAT with the same GSD conditions.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.119-129
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• 2010

The joint use of remotely sensed data and field measurements has been widely used to estimate aboveground carbon stock in many countries. Recently, Korea Forest Research Institute has developed new carbon emission factors for kind of tree, thus more accurate estimate is possible. In this study, the aboveground carbon stock of Danyang area in South Korea was estimated using k-Nearest Neighbor(kNN) algorithm with the 5th National Forest Inventory(NFI) data. Considering the spectral response of forested area under the climate condition in Korea peninsular which has 4 distinct seasons, Landsat TM seasonal satellite images were collected. As a result, the estimated total carbon stock of Danyang area was ranged from 3542768.49tonC to 3329037.51tonC but seasonal trends were not found.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.320-326
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• 2016

From the perspective of climate-smart agriculture, it is becoming more critical to accurately estimate the amount of greenhouse gas emissions in the agricultural sector. In order to accurately ascertain the methane emissions from rice paddies, which account for a significant portion of the emission from the agricultural sector, we used the data from the 2010 Agriculture, Forestry and Fisheries Census, the revised water management scaling factors and their calculation program. In order to facilitate the analyses and understanding, the results were mapped using the ArcGIS software. The fact that the validation of the mapped values against the actual field measurements at one site showed little difference encourages the necessity to further this study. The administrative districts-based map of methane emission can help clearly identify the regional differences. Furthermore, the analysis of their major controlling factors will provide important scientific basis for the practical policy makings for methane mitigation.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.95-101
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• 2023

Colmap is one of the innovative artificial intelligence technologies, highly effective as a tool in 3D reconstruction tasks. Moreover, it excels at constructing intricate 3D models by utilizing images and corresponding metadata. Colmap generates 3D models by merging 2D images, camera position data, depth information, and so on. Through this, it achieves detailed and precise 3D reconstructions, inclusive of objects from the real world. Additionally, Colmap provides rapid processing by leveraging GPUs, allowing for efficient operation even within large data sets. In this paper, we have presented a method of collecting 2D images of traditional Korean towers and reconstructing them into 3D models using Colmap. This study applied this technology in the restoration process of traditional stone towers in South Korea. As a result, we confirmed the potential applicability of Colmap in the field of cultural heritage restoration.