• 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.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.867-879
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• 2020

As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.1
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• pp.11-22
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• 2013

EAREF(East-Asia Reference Frame) is based on the Eurasian Plate which is considered relatively stable. It is managing the coordinate reference system by a specific epoch through the networking of GNSS CORS of the East-Asia region covering North-east and South-east Asia. Also it'll be the goal to assist integrating the geospatial information management. This study aims to estimate the precise coordinates of EAREF in the East-Asia region at the epoch of January 1st of 2012 (2012.0) after the Great East Japan Earthquake. It is related to 1st stage study for construction of data sets and made up the data processing techniques through the various experiments to upgrade the accuracy. Based on the results of the study, we calculated the initial precise coordinates of the EAREF network from the 2012.0 epoch covering the East-Asia region. The accuracy of the estimated coordinates was compared with the weekly solution provided by the IGS analysis centre. The differences were 0.004m, 0.007m and 0.009m at the directions of X, Y and Z respectively. In addition, this study reviews the next procedure how to implement and upgrade the EAREF network.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.175-181
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• 2014

Korean government proposed a new initiative 'government 3.0' with which the administration will open its dataset to the public before requests. City of Seoul is the front runner in disclosure of government data. If we know what kind of attributes are governing factors for any given segmentation, these outcomes can be applied to real world problems of marketing and business strategy, and administrative decision makings. However, with respect to city of Seoul, selection of optimal variables from the open dataset up to several thousands of attributes would require a humongous amount of computation time because it might require a combinatorial optimization while maximizing dissimilarity measures between clusters. In this study, we acquired 718 attribute dataset from Statistics Korea and conducted an analysis to select the most suitable variables, which differentiate Gangnam from other districts, using the Genetic algorithm and Dunn's index. Also, we utilized the Microsoft Azure cloud computing system to speed up the process time. As the result, the optimal 28 variables were finally selected, and the validation result showed that those 28 variables effectively group the Gangnam from other districts using the Ward's minimum variance and K-means algorithm.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.83-93
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• 2013

Land Suitability Assessment can help to evaluate whether to preserve or to develop through analysis of various land characteristics. So, the evaluation index and method are very important for making the best result. The principle objective of this dissertation is to identify effective method that can make up for the distortion of land suitability value in the forest bordering the management area. The objective area of this study is comparative flat Jeungpyeong-gun. The procedures of the study are as follows. First, implement land suitability assessment as the normal index on Guideline. Second, verify land suitability grade about the forest bordering the management area. The third, redo land suitability assessment as two alternative index on $^*$Guideline. The fourth, identify effective method between normal index and alternative index. The results of this tests show that the development suitability value is higher than preservation suitability value in the forest bordering the management area near existing development area. For that reason, this study needed to use substitution index in order to make up for the weakness. The level of land price and distance from road were main considerations. Finally, the derivative model is as follows. The derivative model confirmed the best assessment method in the forest bordering the management area near existing development area.

• Journal of the Korean Geographical Society
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• v.47 no.5
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• pp.755-774
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• 2012

The main objective of the study is to propose GIS-based methods to assess the population distribution criteria for undesirable facilities such as nuclear power plants. First of all, a review of the relevant criteria was conducted for the official documents compiled by such institutions as IAEA (International Atomic Energy Agency), U.S. NRC (Nuclear Regulatory Commission), and some national institutes including the Korea Institute of Nuclear Safety. It is informed from the review that the fundamental principle underlying the various criteria is to maximize the distance between a plant and the nearest population center. It is realized that two interrelated GIS-based techniques need to be devised to put the principle into practice; sophisticated ways of representing population distribution and identifying population centers. A dasymetric areal interpolation is proposed for the former and cell-based and area-based critical density methods are introduced. Grid-based population distributions at various spatial resolutions are created by means of the dasymetric areal interpolation. By applying the critical density methods to the gridded population distribution, some population centers satisfying the population size and density criteria can be identified. These methods were applied to the case of the Gori-1 nuclear power plant and their strengths and limitations were discussed. It was revealed that the assessment results could vary depending upon which method was employed and what values were chosen for various parameters. This study is expected to contribute to foster the applications of methods and techniques developed in geospatial analysis and modeling to the site selection and evaluation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.110-119
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• 2017

The agroclimatic indices are produced by statistical analysis based on primary climate data (e.g., temperature, precipitation, and solar irradiance) or driving agronomic models. This study was carried out to evaluate how selection of daily temperature for a climate normal (1983-2012) affected the precision of the agroclimatic indices. As a first step, averaged daily 0600 and 1500 LST temperature for a climate normal were produced by geospatial schemes based on topo-climatology ($365days{\times}1$ set, EST normal year). For comparison, 30 years daily temperature data were generated by applying the same process ($365days{\times}30sets$), and calculated mean of daily temperature (OBS normal year). The flowering date of apple 'Fuji' cultivar, the last frost date, and the risk of late frost were estimated based on EST normal year data and compared with the results from OBS normal year. The results on flowering date showed 2.9 days of error on average. The last frost date was of 11.4 days of error on average, which was relatively large. Additionally, the risk of the late frost was determined by the difference between the flowering and the last frost date. When it was determined based on the temperature of EST normal year, Akyang was classified as a risk area because the results showed that the last frost date would be the same or later than the flowering date in the 12.5% of area. However, the temperature of OBS normal year indicated that the area did not have the risk of a late frost. The results of this study implied that it would be necessary to reduce the error by replacing the EST method with the OBS method in the future.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.67-74
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• 2016

Drone images with high spatial resolution are emerging as an alternative to previous studies with extraction limits in high density forests. Individual tree in the dense forests were extracted from drone images. To detect the individual tree extracted through the image segmentation process, the image segmentation results were compared between the combination of DSM and all R,G,B band and the combination of DSM and R,G,B band separately. The changes in the tree density of a deciduous forest was experimented by time and image. Especially the image of May when the forests are dense, among the images of March, April, May, the individual tree extraction rate based on the trees surveyed on the site was 50%. The analysis results of the width of crown showed that the RMSE was less than 1.5m, which was the best result. For extraction of the experimental area, the two sizes of medium and small trees were extracted, and the extraction accuracy of the small trees was higher. The forest tree volume and forest biomass could be estimated if the tree height is extracted based on the above data and the DBH(diameter at breast height) is estimated using the relational expression between crown width and DBH.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.97-104
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• 2016

In this study, analyze and monitor the change of the ecological restoration area inside the open-pit mine in Gangwon-do. and to analyze and monitor the change of ecological restoration area. analyzed the distribution of vegetation using high-resolution orthophoto of various periods and analyzed terrain change using DSM/DEM in study area. Therefore, orthophoto and 포인트 클라우드 were collected from 2014 aerial laser surveying and 2015 fixed-wing drone photogrammetry. In addition, orhtophoto and 포인트 클라우드 were produced by using rotary-wing drone photogrammety in 2016, and change of ecological restoration area was analyzed using this. As a result, it's possible to perform change monitoring of the open-pit mine ecological restoration area. using nEGI and VARI, about 10-30% of the area ratio of the result of extracting vegetation distribution area is distributed, and the comparison DSM and DEM cross section and restoration plan line, the cross section made by using the drone were similar, and the earth-volume analysis was possible.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.89-96
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• 2016

By reviewing preceding studies of big data and spatial big data, spatial big data was defined as one part of big data, which spatialize location information and systematize time series data. Spatial big data, as one part of big data, should not be separated with big data and application methods within the system is to be examined. Therefore in this study, services that spatial big data is required to provide were suggested. Spatial big data must be available of various spatial analysis and is in need of services that considers present and future spatial information. Not only should spatial big data be able to detect time series changes in location, but also analyze various type of big data using attribute information of spatial data. To successfully provide the requirements of spatial big data and link various type of big data with spatial big data, methods of forming sample points and extracting attribute information were proposed in this study. The increasing application of spatial information related to big data is expected to attribute to the development of spatial data industry and technological advancement.