• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.529-542
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• 2000

Recent years, the use of multimedia information is rapidly increasing, and the video media is the most rising one than any others, and this field Integrates all the media into a single data stream. Though the availability of digital video is raised largely, it is very difficult for users to make the effective video access, due to its length and unstructured video format. Thus, the minimal interaction of users and the explicit definition of video structure is a key requirement in the lately developing image and video management systems. This paper defines the terms and hierarchical video structure, and presents the system, which construct the clustering-based video hierarchy, which facilitate users by browsing the summary and do a random access to the video content. Instead of using a single feature and domain-specific thresholds, we use multiple features that have complementary relationship for each other and clustering-based methods that use normalization so as to interact with users minimally. The stage of shot boundary detection extracts multiple features, performs the adaptive filtering process for each features to enhance the performance by eliminating the false factors, and does k-means clustering with two classes. The shot list of a result after the proposed procedure is represented as the video hierarchy by the intelligent unsupervised clustering technique. We experimented the static and the dynamic movie videos that represent characteristics of various video types. In the result of shot boundary detection, we had almost more than 95% good performance, and had also rood result in the video hierarchy.

• Journal of the Korean earth science society
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• v.27 no.1
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• pp.83-94
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• 2006

The objective of this paper is to extract and analyze the sediment environment change information in the Sachencheon, Gangneung, Korea that was seriously damaged as a result of typhoon Rusa aftermath early in September, 2002 using multi-temporal remote sensing data. For the extraction of change information, an unsupervised approach based on the automatic determination of thresholding values was applied. As the change detection results, turbidity changes right after typhoon Rusa, the decrease of wetlands, the increase of dry sand and channel width and changes of relative level in the stream due to seasonal variation were observed. Sedimentation in the cultivated areas and restoration works also affected the change near the Sacheoncheon. In addition to the change detection analysis, several environmental thematic maps including microtopographic map, distributions of estimated amount of flood deposits and flood hazard landform classification map were generated by using remote sensing and field survey data. In conclusion, multi-temporal remote sensing data can be effectively used for natural hazard analysis and damage information extraction and specific data processing techniques for high-resolution remote sensing data should also be developed.

• Spatial Information Research
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• v.17 no.2
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• pp.201-212
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• 2009

As GIS analysis method began to be introduced in late 1980's, studies of land development applying the GIS also started to be proceeded in various fields. Since 2003, Land Suitability Assesment has been adopted in order to prevent national land from development thoughtless for the environment and to plan appropriate national land management in terms of green development. Land Suitability Assessment System II based on diverse GIS analysis method such as Contour Analysis, Overlay Analysis, Network Analysis was particularly adopted to draft plans of specifying and altering of exclusionary zoning as well as installing and maintaining of urban planning facilities. But there has been a lot of problem, like an inaccurate basic data and assessment indicators, unmatched threshold, and contradicted evaluation result between each evaluating systems. Even though it is suited to an evaluation criteria, grade distribution is applied to start at 20, and development-centered evaluation result is offered. Now, we observed how suitability values and grading were changed, ordering to change grade distribution system from $20{\sim}100$ to $0{\sim}100$. In result, it showed changes of grades in some parcels. And in case of suitability values, 87% of parcels decreased to minimum 1 point, maximum 70 points. It means that changing grade distribution system of assessment system II doesn't have only influence on suitability values and grading but it is also an empirical analysis because of considering both development and maintenance.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.2
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• pp.75-87
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• 2013

This study developed a GIS-based suitability assessment model of coastal zoning system that is needed in the substantial classification of coastal zoning system according to the establishment of law about coastal zoning system. First, this study investigated several kinds of regulations, GIS database and application system related coastal area. Also, grid data model was selected as the GIS analytical model for calculating items of suitability assessment of coastal zoning system. And Grid-based analytical method was suggested for calculating items composing of sea and spatial location characteristics including physical one. Critical values of items were presented using standards that were suggested in coastal regulations and land suitability assessment. Especially, this study presented a calculation method of continuous pattern as fuzzy set function for reflecting the characteristics of GIS data. And this study classified the suitability grade using Z-score and developed model designating coastal zone as conservation management priority, utilization management priority, and planning management priority. This study is judged that very efficient business performance is possible if we consider the spatial coverage of study area and GIS database when the suitability assessment model of coastal zoning system that is suggested in this study, is applied to business works.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.441-449
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• 2002

For multimedia traffics to be supported successfully in wireless network environment, it is necessary to provide Qualify-of-Service(QoS) guarantees among mobile hosts(clients). In order to guarantee the QoS, we have to keep the call blocking probability below a target value during hand-off session. However, the QoS negotiated between the client and the network may not be guaranteed due to lack of available channels for traffic of a new cell, since on service mobile clients should be able to continue their sessions. In this paper, we propose an efficient load-balancing algorithm based on the adaptive bandwidth reservation scheme for enlarging available channels in a cell. Proposed algorithm predicts the direction of clients in a cell and adjusts the amount of the channel to be reserved according to the load status of the cell. This method is used to reserve a part of bandwidths of a cell for hand-off calls to its adjacent cells and this reserved bandwidth can be used for hand-off call prior to new connection requests. If the number of free channels is also under a low threshold value, our scheme use a load-balancing algorithm with an adaptive bandwidth reservation. In order to evaluate the performance of our algorithm, we measure metrics such as the blocking probability of new calls and dropping probability of hand-off calls, and compare with those of existing schemes.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.1-11
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• 2021

Detection of surface water features including river, wetland, reservoir from the satellite imagery can be utilized for sustainable management and survey of water resources. This research compared the water indices derived from the multispectral bands and the machine learning technique for detecting the surface water features from he Landsat-8 satellite image acquired in Daegu through the following steps. First, the NDWI(Normalized Difference Water Index) image and the MNDWI(Modified Normalized Difference Water Index) image were separately generated using the multispectral bands of the given Landsat-8 satellite image, and the two binary images were generated from these NDWI and MNDWI images, respectively. Then SVM(Support Vector Machine), the widely used machine learning techniques, were employed to generate the land cover image and the binary image was also generated from the generated land cover image. Finally the error matrices were used for measuring the accuracy of the three binary images for detecting the surface water features. The statistical results showed that the binary image generated from the MNDWI image(84%) had the relatively low accuracy than the binary image generated from the NDWI image(94%) and generated by SVM(96%). And some misclassification errors occurred in all three binary images where the land features were misclassified as the surface water features because of the shadow effects.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1235-1243
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• 2023

This study proposes the detection algorithm for the cold water mass (CWM) along the eastern coast of the Korean Peninsula using sea surface temperature (SST) data provided by the Korea Institute of Ocean Science and Technology (KIOST). Considering the occurrence and distribution of the CWM, the eastern coast of the Korean Peninsula is classified into 3 regions("Goseong-Uljin", "Samcheok-Guryongpo", "Pohang-Gijang"), and the K-means clustering is first applied to SST field of each region. Three groups, K-means clusters are used to determine CWM through applying a double threshold filter predetermined using the standard deviation and the difference of average SST for the 3 groups. The estimated sea area is judged by the CWM if the standard deviation in the sea area is 0.6℃ or higher and the average water temperature difference is 2℃ or higher. As a result of the CWM detection in 2022, the number of CWM occurrences in "Pohang-Gijang" was the most frequent on 77 days and performance indicators of the confusion matrix were calculated for quantitative evaluation. The accuracy of the three regions was 0.83 or higher, and the F1 score recorded a maximum of 0.95 in "Pohang-Gijang". The detection algorithm proposed in this study has been applied to the KIOST SST system providing a CWM map by email.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.387-396
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• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.1-15
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• 2015

Urban flooding threatens human beings and facilities with chemical and physical hazards since the beginning of human civilization. Recent studies have emphasized the integration of data and models for effective urban flood inundation modeling. However, the model set-up process is tend to be time consuming and to require a high level of data processing skill. Furthermore, in spite of the use of high resolution grid data, inundation depth and velocity are varied with building treatment methods in 2-D inundation model, because undesirable grids are generated and resulted in the reliability decline of the simulation results. Thus, it requires building generalization process or enhancing building orthogonality to minimize the distortion of building before converting building footprint into grid data. This study aims to develop building generalization method for 2-dimensional inundation analysis to enhance the model reliability, and to investigate the effect of building generalization method on urban inundation in terms of geographical engineering and hydraulic engineering. As a result to improve the reliability of 2-dimensional inundation analysis, the building generalization method developed in this study should be adapted using Digital Building Model(DBM) before model implementation in urban area. The proposed building generalization sequence was aggregation-simplification, and the threshold of the each method should be determined by considering spatial characteristics, which should not exceed the summation of building gap average and standard deviation.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.57-70
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• 2012

The aim of this study is to analyse the landslide susceptibility and the future hazard in Inje, Korea using probability rainfalls and artificial neural network (ANN) environment based on geographic information system (GIS). Data for rainfall probability, topography, and geology were collected, processed, and compiled in a spatial database using GIS. Deokjeok-ri that had experienced 694 landslides by Typhoon Ewinia in 2006 was selected for analysis and verification. The 50% of landslide data were randomly selected to use as training data while the other 50% being used for verification. The probability of landslides for target years (1 year, 3 years, 10 years, 50 years, and 100 years) was calculated assuming that landslides are triggered by 1-day rainfall of 202 mm or 3-day cumulative rainfalls of 449 mm.