• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.281-289
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• 1998

Korea is developing a Korea Multi-Purpose Satellite I (KOMPSAT-1) as one of Korea National Space Program, which will be launched in 1999. The EOC (Electro-Optical Camera) is the primary payload for KOMP-SAT-1. The main mission of EOC is to provide the images for the production of scale maps of Korean territory. This research is focused on methodology and possibility for the production of topographic maps using EOC sensor. Since the imagery from EOC is not yet available, SPOT Level 1A image data which are quite similar to those of EOC, and Intergraph Imagestation (Digital Photogrammetric Workstation) are implemented in the process of sample digital map generation. The sample digital maps generated from SPOT stereoimages were compared and analyzed with the existing 1:50,000 scale digital map produced by National Geography Institute. The feasibility and problem encountered in 1:50,000 scale digital mapping using SPOT stereoimages were presented. Based on results, the feasibility and further research areas for KOMPSAT-EOC in the line of 1:25,000 and 1;50,000 digital mapping were discussed.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.693-703
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• 2019

Long-term coastal topographical data is critical for analyzing temporal and spatial changes in shorelines. Especially understanding the change trends is essential for future coastal management. For this research, in the data preparation, we obtained digital aerial images, terrestrial laser scanning data and UAV images in the year of 2009. 2018 and 2019 respectively. Also tidal observation data obtained by the Korea Hydrographic and Oceanographic Agency were used for Bangamoeri beach located in Ansan, Gyeonggi-do. In the process of it, we applied the photogrammetric technique to extract the coastline of 4.40 m from the stereo images of 2009 by stereoscopic viewing. In 2018, digital elevation model was generated by using the raw data obtained from the laser scanner and the corresponding shoreline was semi-automatically extracted. In 2019, a digital elevation model was generated from the drone images to extract the coastline. Finally the change rate of shorelines was calculated using Digital Shoreline Analysis System. Also qualitative analysis was presented.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.429-438
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• 2021

In recent, realistic content has been applied in various ways due to the development of display technology and hologram, the final realistic content technology, have been used limitedly in accordance with the growing public demand. However, most realistic content requires additional devices of HMD (head mounted device) or glasses type, and other realistic content display technologies deliver a single image plane in the experience space to the user, providing a monotonous content experience. Various realistic contents with hologram technology are introduced in this work. In addition, we propose an interaction based realistic hologram service based that combines projection mapping and floating holograms. Projection-mapped screens and multi-floating hologram device provide a three-dimensional volumetric space with extended depth orientation from the user's point of view, while allowing users' entire and partial motions to be recognizable through multiple sensors.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1311-1317
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• 2018

The ultimate goal of satellite development is to use information obtained from satellites. Therefore, national-levelsatellite development program should include not only hardware development, but also infrastructure establishment and application technology development for information utilization. Until now, Korea has developed various satellites and has been very useful in weather and maritime surveillance as well as various disasters. In particular, KOMPSAT (Korea Multi-purpose Satellite) images have been used extensively in agriculture, forestry and marine fields based on high spatial resolution, and has been widely used in research related to precision mapping and change detection. This special issue aims to introduce a variety of recent studies conducted using KOMPSAT optical and SAR (Synthetic Aperture Radar) images and to disseminate related satellite image application technologies to the public sector.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.837-847
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• 2023

In this study, we explored a method for assessing the extent of damage caused by chemical substances at an accident site through the use of a vegetation index. Data collection involved the deployment of two different drone types, and the damaged area was determined using photogrammetry technology from the 3D point cloud data. To create a vegetation index image, we utilized spectral band data from a multi-spectral sensor to generate an orthoimage. Subsequently, we conducted statistical analyses of the accident site with respect to the damaged area using a predefined threshold value. The Kappa values for the vegetation index, based on the near-infrared band and the green band, were found to be 0.79 and 0.76, respectively. These results suggest that the vegetation index-based approach for analyzing damage areas can be effectively applied in investigations of chemical accidents.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1523-1535
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• 2020

In order to produce crop information using remote sensing, we use classification and growth monitoring based on crop phenology. Therefore, time-series satellite images with a short period are required. However, there are limitations to acquiring time-series satellite data, so it is necessary to use fusion with other earth observation satellites. Before fusion of various satellite image data, it is necessary to overcome the inherent difference in radiometric characteristics of satellites. This study performed Korea Multi-Purpose Satellite-3 (KOMPSAT-3) cross calibration with Landsat-8 as the first step for fusion. Top of Atmosphere (TOA) Reflectance was compared by applying Spectral Band Adjustment Factor (SBAF) to each satellite using hyperspectral sensor band aggregation. As a result of cross calibration, KOMPSAT-3 and Landsat-8 satellites showed a difference in reflectance of less than 4% in Blue, Green, and Red bands, and 6% in NIR bands. KOMPSAT-3, without on-board calibrator, idicate lower radiometric stability compared to ladnsat-8. In the future, efforts are needed to produce normalized reflectance data through BRDF (Bidirectional reflectance distribution function) correction and SBAF application for spectral characteristics of agricultural land.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.3
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• pp.13-21
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• 2004

The dissemination of commercial satellite images. which have the high spatial resolution such as aerial photos, are the active trend in remote sensing community because of the recent development in satellite and sensor technology. Such high resolution satellite images provide a unique tool for the monitoring of ongoing urban land use change. Especially KOMPSAT-1, which was launched at December 1999 and successfully operated up to now, provides repeatedly panchromatic images over Korean peninsula, which has the spatial resolution of 6.6m. Based upon this KOMPSAT-1 EOC image data we can try to analyze and assess the temporal urban land use change, which could not be done because lack of such data. The aim of this paper is to analyze and assess the spatial land use characteristics of Daejeon Metropolitan City based on KOMPSAT-1 EOC data. The land use map of year 2001 is generated through the modification of the year 2000 land use map, which is published by National Geographic Information Institute, using visual interpretation of KOMPSAT-1 EOC image which is acquired in year 2001. This study can be the start point of the time series analysis of the long term land use change monitoring mit KOMPSAT-1 EOC data.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.435-444
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• 2011

The land cover map derived from spectral features of high resolution optical images has low spectral resolution and heterogeneity in the same land cover class. For this reason, despite the same land cover class, the land cover can be classified into various land cover classes especially in vegetation area. In order to overcome these problems, detailed vegetation classification is applied to optical satellite image and SAR(Synthetic Aperture Radar) integrated data in vegetation area which is the result of pre-classification from optical image. The pre-classification and vegetation classification were performed with MLC(Maximum Likelihood Classification) method. The hierarchical land cover classification was proposed from fusion of detailed vegetation classes and non-vegetation classes of pre-classification. We can verify the facts that the proposed method has higher accuracy than not only general SAR data and GLCM(Gray Level Co-occurrence Matrix) texture integrated methods but also hierarchical GLCM integrated method. Especially the proposed method has high accuracy with respect to both vegetation and non-vegetation classification.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.989-1006
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• 2020

Building change monitoring based on building detection is one of the most important fields in terms of monitoring artificial structures using high-resolution multi-temporal images such as CAS500-1 and 2, which are scheduled to be launched. However, not only the various shapes and sizes of buildings located on the surface of the Earth, but also the shadows or trees around them make it difficult to detect the buildings accurately. Also, a large number of misdetection are caused by relief displacement according to the azimuth and elevation angles of the platform. In this study, object-based building detection was performed using the azimuth angle of the Sun and the corresponding main direction of shadows to improve the results of building change detection. After that, the platform's azimuth and elevation angles were used to detect changed buildings. The object-based segmentation was performed on a high-resolution imagery, and then shadow objects were classified through the shadow intensity, and feature information such as rectangular fit, Gray-Level Co-occurrence Matrix (GLCM) homogeneity and area of each object were calculated for building candidate detection. Then, the final buildings were detected using the direction and distance relationship between the center of building candidate object and its shadow according to the azimuth angle of the Sun. A total of three methods were proposed for the building change detection between building objects detected in each image: simple overlay between objects, comparison of the object sizes according to the elevation angle of the platform, and consideration of direction between objects according to the azimuth angle of the platform. In this study, residential area was selected as study area using high-resolution imagery acquired from KOMPSAT-3 and Unmanned Aerial Vehicle (UAV). Experimental results have shown that F1-scores of building detection results detected using feature information were 0.488 and 0.696 respectively in KOMPSAT-3 image and UAV image, whereas F1-scores of building detection results considering shadows were 0.876 and 0.867, respectively, indicating that the accuracy of building detection method considering shadows is higher. Also among the three proposed building change detection methods, the F1-score of the consideration of direction between objects according to the azimuth angles was the highest at 0.891.