• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.87-96
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• 2011

Carbon emissions and storages that are strongly related to global warming has have emerged as one of the important issues while many governments and researchers have been interested in climate change and pollution. In this regards, forest biomass estimation is quite importance since forest biomass works as an important medium of the global carbon cycle between the atmosphere and soil. Forest biomass estimation through field survey needs lots of time and labors, and has accessibility issues. Hence, many researchers have focused on the forest biomass approaches based on remotely sensed data. This research comprehensively reviewed forty one international studies using remote sensing data according to five different categories (i.e., location of study area, size of study area, biome, used remote sensing data, and estimation technology). It would be expected that the results of this study can be used for suggesting domestic research directions; domestic research in this field is at the beginning stage in terms of level of technologies and useful materials. As results, 39% out of the reviewed studies used the areas located in North America. 59% out of the researches dealt with small size of the study areas (less than 3,600km2). In case of biome, around 30% of the studies focused on the boreal/taiga areas. Moreover, 35% and 16% of the studies were carried out using Landsat series and Lidar data, respectively. Finally, regression analysis method was most frequently used for forest biomass estimation by 71% out of 41 studies.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.2 s.16
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• pp.61-69
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• 2000

Until now, the extraction of information on geographic features and the compilation of maps from satellite imagery has had many limitations because of its lower resolution compared to aerial photos to the recent. However, it is expected that the availability of high resolution satellite imagery whose spatial resolution is about 1m will reduce such limitations. Currently, a compilation of national-wide digital base maps is going on to construct the National Geographic Information Systems in Korea. It will be used for many application field of the social welfare. Therefore, in this study, we suggest that satellite imagery can help it and we have experimented on the possibility of detecting and interpreting geographic data using satellite imagery of various spatial resolutions. The interpretability and detectability of 46 features in 6 categories was experimented with 6 kinds of images of different resolutions. As a subsequent procedure, we have performed the fractal analysis for a quality test of the texture information. Through the fractal analysis, we could show that texture information and probability of discrimination increases as the spatial resolution of the image increases. Based on the results of this experiment, we could suggest the possibility of the renewal and construction of the National-wide Geographic Information Systems database using satellite imagery, as well as of examining appropriate spatial resolutions for objects of interest.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.41-46
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• 2014

Bus service is easily adjusted to accommodate the changed demand. Despite the flexibility of that, its relocation should overcome the following problems: first, Bus line rearrangement should consider the balance between the demand and the supply to enhance the transit equity among the users scattered around the area that supply against demand imbalances. Second, the existing demand analysed is to crude since the demand was analysed based on TAZ. mainly based on the Dong unit. Utilization of the GWR and GIS-T data can resolve the problem. In this paper, the limitation of the conventional transit demand analysis model is overcome by deploying the GWR model which identifies the transit demand based on the geographic relation between the service location and those of the users. GWR model considers the spatial effect of the bus demand in accordance with the distance to the each bus stops using SCD(Smart Card Data) and BIS(Bus Information System). This demand map was then superimposes with the existing bus route which identified the areas where the balance between demand and supply is severly skewed. since the analysis was computed with SCD and BIS at every bus stops. the shortage and surplus of bus service of entire study area could computed. Further. based on this computational result and considering the entire bus service capacity data. Bus routes optimization from the oversupplied areas to the undersupplied area was illustrated thus this study clearly compared the benefits the GIS.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.59-66
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• 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 Korean Society for Geospatial Information Science
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• v.2 no.1 s.3
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• pp.121-129
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• 1994

A number of existing cadastral control stations have been destroyed and shifted by a long lapse of time and careless management. Also, results of them are partly poor owing to dependence on conventional survey method. Because of these, it is very difficult in use of results. Hereupon, correction of cadastral results is necessary in level of government. But it is very consumable to check and adjust results with existing equipments and related techniques only. It is required that this problem can be resolved efficiently. This study analyzed the conformability for cadastral control network to GPS, GPS, which determine precise 3-D coordinates on a short time, to positioning of cadastral stations. We chose DaeJon city for the test area of this study and analyzed the precision of network composed of sixteen cadastral control stations. We made comparision the old result and the new outcome which obtained from coordinate transformation method and horizontal network adjustment method. As a result of this, we detected the blunder of cadastral stations. Furthermore, we suggested effective network type according to precision analysis of GPS observation network. Therefore, there is no doubt that GPS surveying can be applied to checking and adjustment of cadastral control network. Hereafter, it is expected that the practical use of GPS is advanced in a field of cadastration.

• Spatial Information Research
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• v.21 no.4
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• pp.71-81
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• 2013

Due to explosively increasing utilization in spatial information and a rapid development in geospatial technology related to national territorial and housing, there are increasing demands for converging spatial information on not only urban planning and real estate data but also newly generated data from smart phone, GPS to achieve comparative advantage of national territory. In this paper, we prospect the utilization of Converged Spatial Information(CSI) to future national territorial planning for the purpose of enhancing territorial competitiveness. For this purpose, considering the Korea Land and Housing corporation(LH) takes charge most of government's land and housing development projects, CSI usage of this company's 6 future business domains until 2029 were used as a case study. Also, 7 CSIs derived from literature review were surveyed to find the degree of CSI utilization in the national territorial future. In the analysis result, it was found that 3D data and mobile data among others have higher degree of utilization, and urban and regional development is the most highly utilizable domain for CSIs. After all, to revitalize the use of CSI in national territorial future, it is required to do a balanced construction of territorial use spatial information about marine use, coastal use, underground space besides land use.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.223-233
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• 2018

In this study was classified the cadastral control points and parcel boundary points into 40m, 100m by flight altitude of UAV (Unmanned Aerial Vehicle) which compared the coordinates extracted from the orthophoto with the parcel boundary point coordinates by GNSS (Global Navigation Satellite System) ground survey. As a results of this study, first, in the spatial resolution analysis that the average error of the orthoimage by flight altitude were 0.024m at 40m, and 0.034m at 100m which were higher 40m than 100m for spatial resolution of orthophotos and position accuracy. Second, in order to analyze the accuracy of image recognition by airmark of flight altitude that was divided into three cases of nothing, green, and red of RMSE (Root Mean Square Error) were X=0.039m, Y=0.019m and Z=0.055m, the highest accuracy. Third, the result of the comparison between orthophotos and field survey results that showed the total RMSE error of the cadastral control points were X=0.029m, Y=0.028m, H=0.051m, and the parcel boundary points were X=0.041m, Y=0.030m. In conclusion, based on the results of this study, it is expected that if the average error of flight altitude is limited to less than 0.05m in the legal regulations related to orthophotos for cadastral surveying, it will be an economical and efficient method for cadastral survey as well as spatial information acquisition.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.25-33
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• 2016

In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.687-701
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• 2014

Sea ice is generally accepted as an important factor to understand the process of earth climate changes and is the basis of earth system models for analysis and prediction of the climate changes. To continuously monitor sea ice changes at kilometer scale, it is demanded to create more accurate grid data from the current, limited sea ice data. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Sea Ice Concentration (SIC) from 10 km to 1 km resolution using a weighting scheme of sea ice days ratio derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sea ice cover product that has a high correlation with the SIC. In a case study for Okhotsk Sea, the sea ice areas of both data (before and after downscaling) were identical, and the monthly means and standard deviations of SIC exhibited almost the same values. Also, Empirical Orthogonal Function (EOF) analyses showed that three kinds of SIC data (ERA-Interim, original AMSR2, and downscaled AMSR2) had very similar principal components for spatial and temporal variations. Our method can apply to downscaling of other continuous variables in the form of ratio such as percentage and can contribute to monitoring small-scale changes of sea ice by providing finer SIC data.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.819-829
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• 2019

In the disaster of collapse, an immediate response is needed to prevent the damage from worsening, and damage area calculation, response and recovery plan should be established. This requires accurate detection of the damage affected area. This study performed the detection of the damaged area by using UAV which can respond quickly and in real-time to detect the collapse accident. The study area was selected as B-05 housing redevelopment area in Jung-gu, Ulsan, where the demolition of houses and apartments in progress as the redevelopment project began. This area resembles a collapsed state of the building, which clear changes before and after the demolition. UAV images were acquired on May 17 and July 9, 2019, respectively. The changing area was considered as the damaged area before and after the collapse of the building, and the changing area was detected using CVA (Change Vector Analysis) the Representative Change Detection Technique, and SLIC (Simple Linear Iterative Clustering) based superpixel algorithm. In order to accurately perform the detection of the damaged area, the uninterested area (vegetation) was firstly removed using ExG (Excess Green), Among the objects that were detected by change, objects that had been falsely detected by area were finally removed by calculating the minimum area. As a result, the accuracy of the detection of damaged areas was 95.39%. In the future, it is expected to be used for various data such as response and recovery measures for collapse accidents and damage calculation.