• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.117-124
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• 2010

Lots of changes in Weolmido have occurred in the historical and cultural aspects owing w the geographical features. This study aims at restoring Weolmido to the past shape three-dimensionally and analyzing its changes. For achieving this goal, I made use of paper maps made in 1918, 1928, and 1969, a digital map produced in 2008, and aerial photos photographed in 1954. And I attempted to grasp the architectural shape and the topographical limn by using photos in those times and put them to practical use for restitution. Image restitution was carried out under the method of mapping and photogrammetry. As the result of restitution, I could restore each shape of Weolmido for those past times to the original condition three-dimensionally and catch its changes according to the difference of times.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2786-2796
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• 1998

Extraction of interesting and general knowledge from large spatial database is an important task in the development of geographical information system and knowledge-base systems. In this paper, we propose a spatial data mining system using generalization method; In this system, we extend an existing generalization mining and design a rulebase to support deriving new spatial knowledge. For this purpose, we propose an interleaved method which integrates spatial data dominated and nonspatial data dominated mining and construct a rulebase to extract topological relationship between spatial objects.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.231-237
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• 2007

To monitor process of vegetation rehabilitation at the damaged area after large-fire is required a lot of manpowers and budgets. However the analysis of vegetation recovery using satellite imagery can be obtaining rapid and objective result remotely in the large damaged area. Space and airbone sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. Burn severity incorporates both short- and long-term post-fire effects on the local and regional environment. Burn severity is defined by the degree to which an ecosystem has changed owing to the fire. To classify fire damaged area and analyze burn severity of Samcheok fire area occurred in 2000, Cheongyang fire 2002, and Yangyang fire 2005 was utilized Landsat TM and ETM+ imagery. Therefore the objective of the present paper is to quantitatively classify fire damaged area and analyze burn severity using normalized burn index(NBR) of pre- and post-fire's Landsat satellite imagery.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.2
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• pp.11-18
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• 2016

Global Positioning System (GPS) is currently widely used for aviation applications. Single-frequency GPS receivers are highly affected by the ionospheric delay error, and the ionospheric delay should be corrected for accurate positioning. Single-frequency GPS receivers use the Klobuchar model, whose model parameters are transmitted from GPS satellites. In this paper, the long-term accuracy of the Klobuchar model from 2002 to 2014 is analyzed. The IGS global ionosphere map is considered as true ionospheric delay, and hourly, seasonal, and geographical error variations are analyzed. Histogram of the ionospheric delay error is also analyzed. The influence of solar and geomagnetic activity on the Klobuchar model error is analyzed, and the Klobuchar model error is highly correlated with solar activity. The results show that the Klobuchar model estimates 8 total electron content unit (TECU) over the true ionosphere delay in average. The Klobuchar model error is greater than 12 TECU within $20^{\circ}$ latitude, and the error is less than 6 TECU at high latitude.

• Plant Biotechnology Reports
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• v.2 no.3
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• pp.191-198
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• 2008

Germplasm characterization and evolutionary process in viable populations are important links between the conservation and utilization of plant genetic resources. Here, an investigation is made, based on molecular and biochemical techniques for assessing and exploiting the genetic variability in germplasm characterization of taro, which would be useful in plant breeding and ex situ conservation of taro plant genetic resources. Geographical differentiation and phylogenetic relationships of Indian taro, Colocasia esculenta (L.) Schott, were analyzed by random amplified polymorphic DNA (RAPD) and isozyme of seven enzyme systems with specific reference to the Muktakeshi accession, which has been to be proved resistant to taro leaf blight caused by P. colocasiae. The significant differentiations in Indian taro cultivars were clearly demonstrated by RAPD and isozyme analysis. RAPD markers showed higher values for genetic differentiation among taro cultivars and lower coefficient of variation than those obtained from isozymes. Genetic differentiation was evident in the taro accessions collected from different regions of India. It appears that when taro cultivation was introduced to a new area, only a small fraction of genetic variability in heterogeneous taro populations was transferred, possibly causing random differentiation among locally adapted taro populations. The selected primers will be useful for future genetic analysis and provide taro breeders with a genetic basis for selection of parents for crop improvement. Polymorphic markers identified in the DNA fingerprinting study will be useful for screening a segregating population, which is being generated in our laboratory aimed at developing a taro genetic linkage map.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.605-609
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• 2005

This study is to perform the rainfall-runoff analysis of the basin of Yongdam dam where is loacted in the Geumriver basin. The model used is the SAC-SMA model which was developed by U.S. National Weather Service. The Precipitation data used as the input data of the model are daily ones observed in 2002 and the mean of values recorded in 5 rainfall stations. The evaporation data are used observed in Daejeon meteorological station. The geographical data such as basin slope and stream gradient are elicited from the numerical map analysis. In the verification through the comparison of calculated daily inflow with observed one, parameters used in the model are estimated manually. As the result of verification, total annual calculated inflow is 13,547CMS and agree accurately with the observed one. During the period of one year of 2002, before 100 days and after 250 days, the soil moisture condition in the upper zone was significantly dry and in spite of the rainfall in this period, the runoff was not generated. Through this result, we can observe that the moisture condition in the soil affects strongly the runoff in a basin.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1248-1251
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• 2002

Logistics optimization problems related with vehicle routing such as warehouse locating, track scheduling, customer order delivery, wastage pickup etc. are very interesting and important issues to date. Many Vehicle Routing and Scheduling Systems (VRSS) have been developed/proposed to optimize the logistics problems. But majority of them are dedicated to a particular problem and are unable to handle the real world spatial data directly. The system developed for one problem may not be suitable for others due to inter-problem constraint variations. The constraints may include geographical, environmental and road traffic nature of the working region along with other constraints related with the problem. So the developer always needs to modify the original routing algorithm in order to fulfill the purpose. In our study, we propose a general-purpose platform by combining GIS road map and Database Management System (DBMS), so that VRSS can interact with real world spatial data directly to solve different kinds of vehicle routing problems. Using the features of our developed system, the developer can frequently modify the existing algorithm or create a new one to serve the purpose.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.83-92
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• 2020

The purpose of this work was to apply geographical information system (GIS) for geostatistical analyzing by selecting a semi-variogram model to quantify the spatial correlation of the population distribution with residential neighborhoods in the both sides of Mosul city. Two hundred and sixty-eight sample sites in 240 ㎢ are adopted. After determining the population distribution with respect to neighborhoods, data were inserted to ArcGIS10.3 software. Afterward, the datasets was subjected to the semi-variogram model using ordinary kriging interpolation. The results obtained from interpolation method showed that among the various models, Spherical model gives best fit of the data by cross-validation. The kriging prediction map obtained by this study, shows a particular spatial dependence of the population distribution with the neighborhoods. The results obtained from interpolation method also indicates an unbalanced population distribution, as there is no balance between the size of the population neighborhoods and their share of the size of the population, where the results showed that the right side is more densely populated because of the small area of residential homes which occupied by more than one family, as well as the right side is concentrated in economic and social activities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.3
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• pp.385-392
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• 2010

A LiDAR technique has the merits that survey engineers can get a large number of measurements with high precision quickly. Aerial photos and satellite sensor images are used for generating 3D spatial images which are matched with the map coordinates and elevation data from digital topographic files. Also, those images are used for matching with 3D spatial image contents through perspective view condition composed along to the designated roads until arrival the corresponding location. Recently, 3D aviation image could be generated by various digital data. The advanced geographical methods for guidance of the destination road are experimented under the GIS environments. More information and access designated are guided by the multimedia contents on internet or from the public tour information desk using the simulation images. The height data based on LiDAR is transformed into DEM, and the real time unification of the vector via digital image mapping and raster via extract evaluation are transformed to trace the generated model of 3-dimensional downtown building along to the long distance for 3D tract model generation.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.85-93
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• 2015

This paper mainly introduces the methods of extracting landslide information using ALOS(Advanced Land Observing Satellite) images and GIS(Geographical Information System) technology. In this study, we classified images using three different methods which are the unsupervised the supervised and the PCA(Principal Components Analysis) for extracting landslide information based on characteristics of ALOS image. From the image classification results, we found out that the quality of classified image extracted with PCA supervised method was superior than the other images extracted with the other methods. But the accuracy of landslide information extracted from this image classification was still very low as the pixels were very similar between the landslide and safety regions. It means that it is really difficult to distinguish those areas with an image classification method alone because the values of pixels between the landslide and other areas were similar, particularly in a region where the landslide and other areas coexist. To solve this problem, we used the LSM(Landslide Susceptibility Map) created with ArcView software through weighted overlay GIS method in the areas. Finally, the developed LSM was applied to the image classification process using the ALOS images. The accuracy of the extracted landslide information was improved after adopting the PCA and LSM methods. Finally, we found that the landslide region in the study area can be calculated and the accuracy can also be improved with the LSM and PCA image classification methods using GIS tools.