• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.101-108
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• 2011

Construction of the Jangbogo antarctic station was planned, and it requires detailed information on topography of the area around the station. The purpose of this research is to generate the topographic map to construct the Jangbogo antarctic station using the satellite image. To do this, surveying and pre-test of equipment were conducted. In addition, for sensor modeling of the GeoEye-1 satellite image, RPC-bias correction was done, and it showed that at least two control points are required. In generating the map, a 1/2,500 scale was deemed suitable in consideration of resolution of the image and the fact that supplementary topographic surveying would be impossible. In order to provide detailed information on the topography around the Jangbogo station, the digital elevation model based on image matching was created, and compared with GPS-RTK data, accuracy of vertical location about 0.6m was exhibited.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.21-31
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• 2020

This study analyzed the spatio-temporal change pattern of greenhouse areas for Sangnam-myeon and Samrangjin-eup of Miryang-si in Gyeongnam, which is one of major greenhouse area. First, in order to overcome the lack of statistical data of the distribution of greenhouses, aerial and satellite images were interpreted from 1987 to 2018, and the spatial distribution of the greenhouse parcels which has continuously increased was mapped based on the digital cadastral map. Next, through the emerging hot spot tool in ArcGIS Desktop, the spatio-temporal change in transition from open-field to greenhouse cultivation was classified into 9 clusters. About 67.7% of the target area was categorized as a hot spot, and the pattern of New hot spot, which were recently converted to greenhouse parcels, covered about 34.1%. While, about 11.3% of parcels were expected to keep the existing open-field cultivation practice for a while. Overall, the greenhouse parcels have been densely developed along a river and were lately expanding even to the far neighbor. It implied that, in the future, the competition of water intake among farms would be more serious and the environmental responsibility in consideration of water quality as well as quantity would be getting strengthened due to increasing pollution loads and river intake.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.57-81
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• 2019

Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.

• Spatial Information Research
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• v.14 no.3 s.38
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• pp.285-297
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• 2006

We aim to investigate the morphological and environmental characteristics of royal tombs of Chosun Dynasty by using GIS technique and remotely-sensed data. Most of the royal tombs are located on the banded gneiss and granite and over the south- and east. facing slopes and have altitudinal ranges of 150 to 200 meters. Due to the time gaps, exact locational preferences of the royal families can not be understood at this moment and also proximity to the running water is hard to be quantified. Close examination of Gwangneung indicates that the artificial modification and weathering have severe impacts on the slope and stone artefacts. The results from this research can be useful to preserve the valueless cultural heritages.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.49-60
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• 1995

Features of geological lineaments generally play an important role at the data interpretation concerned geological processes, mineral exploration or natural hazard risk estimation. However, there are intrinsically discordances between lineaments-related features extracted from surficial geological syrvey and those from satellite imagery;nevertheless, any data set contained those information should not be considred as less meaningful within their own task. For the purpose of effective utilization task of extracted lineaments, the mathematical scheme, based on fuzzy set theory, for practical integration of various types of rasterized data sets is studied. As a real application, the geological map named Homyeong sheet(1:50,000) and the Landset TM imageries covering same area were used, and then lineaments-related data sets such as lineaments on the geological map, lineaments extracted from a false-color image composite satellite, and major drainage pattern were utilized. For data fusion process, fuzzy membership functions of pixel values in each data set were experimentally assigned by percentile, and then fuzzy algebraic sum operator was tested. As a result, integrated lineaments by this well-known operator are regarded as newly-generated reasonable ones. Conclusively, it was thought that the implementation within available GISs, or the stand-alone module for general applications of this simple scheme can be utilized as an effective scheme can be utilized as an effective scheme for further studies for spatial integration task for providing decision-supporting information, or as a kind of spatial reasoning scheme.

• Proceedings of the KSRS Conference
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• v.2
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• pp.647-650
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• 2006

Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed (1756 square miles) in Ohio, U.S.A., which is one of the largest hyperspectral image acquisition. For the development of a 4m-resolution land cover dataset, a hierarchical approach was employed using two different classification algorithms: 'Image Object Segmentation' for level-1 and 'Spectral Angle Mapper' for level-2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination. The land cover class members were lentic, lotic, forest, corn, soybean, wheat, dry herbaceous, grass, urban barren, rural barren, urban/built, and unclassified. The final phase of processing was completed after an extensive Quality Assurance and Quality Control (QA/QC) phase. With respect to the eleven land cover class members, the overall accuracy with a total of 902 reference points was 83.9% at 4m resolution. The dataset is available for public research, and applications of this product will represent an improvement over more commonly utilized data of coarser spatial resolution such as National Land Cover Data (NLCD).

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2006.05a
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• pp.152-157
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• 2006

Satellite imagery is generally used for investigating the damage from natural disaster for wide area and remotely piloted vehicle or aerial photos are used for the local damage. But for more detailed information such as damages of public facilities, these methods are inadequate and so in this case field surveying has been carried out. We tried to estimate the damage of public facilities faster and more accurately using photogrammetric method. We developed a digital stereo camera system by fixing two digital cameras on a frame, and with this system the photos of actually damaged areas were collected. The damages were estimated from these stereo photos. Then the estimated data was compared with field surveying data in order to verify our system.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.234-237
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• 2007

Road networks are important geospatial databases for various GIS (Geographic Information System) applications. Road digital maps may contain geometric spatial errors due to human and scanning errors, but manually updating roads information is time consuming. In this paper, we developed a new road features updating methodology using from multispectral high-resolution satellite image and pre-existing vector map. The approach is based on initial seed point generation using line segment matching and a modified double snake algorithm. Firstly, we conducted line segment matching between the road vector data and the edges of image obtained by Canny operator. Then, the translated road data was used to initialize the seed points of the double snake model in order to refine the updating of road features. The double snake algorithm is composed of two open snake models which are evolving jointly to keep a parallel between them. In the proposed algorithm, a new energy term was added which behaved as a constraint. It forced the snake nodes not to be out of potential road pixels in multispectral image. The experiment was accomplished using a QuickBird pan-sharpened multispectral image and 1:5,000 digital road maps of Daejeon. We showed the feasibility of the approach by presenting results in this urban area.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.2 s.16
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• pp.23-33
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• 2000

On this study, Among the classification methods of land cover using satellite imagery, we compared the classification accuracy of Neural Network Classifier and that of Maximum Likelihood Classifier which has the characteristics of parametric and non-parametric classification method. In the assessment of classification accuracy, we analyzed the classification accuracy about testing area as well as training area that many analysts use generally when assess the classification accuracy. As a result, Neural Network Classifier is superior to Maximum Likelihood Classifier as much as 3% in the classification of training data. When ground reference data is used, we could get poor result from both of classification methods, but we could reach conclusion that the classification result of Neural Network Classifier is superior to the classification result of Maximum Likelihood Classifier as much as 10%.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.2 s.16
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• pp.47-60
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• 2000

On this study, Among the classification methods of land cover using satellite imagery, we compared the classification accuracy of Neural Network Classifier and that of Maximum Likelihood Classifier which has the characteristics of parametric and non-parametric classification method. In the assessment of classification accuracy, we analyzed the classification accuracy about testing area as well as training area that many analysts use generally when assess the classification accuracy. As a result, Neural Network Classifier is superior to Maximum Likelihood Classifier as much as 3% in the classification of training data. When ground reference data is used, we could get poor result from both of classification methods, but we could reach conclusion that the classification result of Neural Network Classifier is superior to the classification result of Maximum Likelihood Classifier as much as 10%.