• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.189-197
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• 2012

This research attempted to find possibilities of the practical use utilizing geospatial methods for the balanced promotion of sustainable coastal development and preservation through a case study of Jekyll Island, one of Georgia's barrier islands. In response, this research provided ways for practical use in sustainable development and preservation plans. First this research thoroughly investigated the 1996 master plan of Jekyll Island and tried to recalculate developed and undeveloped areas. Second, new estimations for developed areas were investigated through field survey. Third, this research proposed the use of the satellite images with different levels of spatial resolutions and tested different classification schemes to find possibilities for practical use. For these purposes, first, we classified developed and undeveloped features by manual digitization using an aerial photo image with 0.5m spatial resolution. Second, a Landsat 7 ETM+ and a QuickBird satellite images with mid- and high-levels of spatial resolutions were applied to identify developed and undeveloped areas using both the National Land Cover Data (NLCD) and the Coastal Change Analysis Program (CCAP) classification schemes. Also, GEOBIA (Geographic Object-Based Image Analysis) was conducted to accurately identify developed and undeveloped areas.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.61-69
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• 2009

By the advent of the high resolution satellite imagery, a ground-coverage included by a single satellite image is decreased. By the reason, there are increasing needs in image mosaicking technology to use images to various GIS fields. This paper describes an edge-based seamline extraction algorithm using edge information such as rivers, roads, buildings for image mosaicking. For this, we developed a method to track and link discontinuous edges extracted by edge detection operator. To estimate the effectiveness of the proposed algorithm, we applied the algorithm to IKONOS, KOMPSAT-1 and SPOT-5 satellite images. The experimental results showed that the algorithm successfully dealts with discontinuities caused by geometric differences in two images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.321-327
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• 2008

In recently, researches which appling satellite image are introduced target to the forest area. Especially, it is satellite image analysis's advantage that collecting information of terrain at the direct accesses are dangerous and impassible area. But, the studies approaching to a inflectional paradigm of forests and change detection system for the distinguished forests type are leaves much to be desired. In this study, therefore, change of forests type was analyzed using Landsat TM satellite image which have multi-spectral bands. Furthermore, change detection system for forests type was constructed on web for the periodical monitoring.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.690-706
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• 2021

Classification is a substantial operation in data mining, and each element is distributed taking into account its feature values in the corresponding class. Metaheuristics have been widely used in attempts to solve satellite image classification problems. This article proposes a hybrid approach, the flower pigeons-inspired optimization algorithm (FPIO), and the local search method of the flower pollination algorithm is integrated into the pigeon-inspired algorithm. The efficiency and power of the proposed FPIO approach are displayed with a series of images, supported by computational results that demonstrate the cogency of the proposed classification method on satellite imagery. For this work, the Davies-Bouldin Index is used as an objective function. FPIO is applied to different types of images (synthetic, Alsat-2B, and Sentinel-2). Moreover, a comparative experiment between FPIO and the genetic algorithm genetic algorithm is conducted. Experimental results showed that GA outperformed FPIO in matters of time computing. However, FPIO provided better quality results with less confusion. The overall experimental results demonstrate that the proposed approach is an efficient method for satellite imagery classification.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.8
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• pp.590-598
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• 2019

Today, satellites are widely used in many fields like communication and image recoding. The image acquired by satellites contains variety information of wide region. Therefore, they are used for agriculture, resource exploitation and management, and military purpose. The satellite is required to acquire images effectively in a given time period. Because the period that satellites can acquire images is very restrictive. In this study, the modeling of processing time and attitude maneuvering for satellite image acquisition is performed. From this modeling, mission planning algorithm using heuristic evaluation function is suggested and performance of the proposed algorithm is verified by numerical simulation.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.645-648
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• 2005

The COMS(Communication, Ocean and Meteorological Satellite), a multi-mission geo-stationary satellite, is being developed by KARl. The first mission of the COMS is the meteorological image and data gathering for weather forecast by using a five channel meteorological imager. The second mission is the oceanographic image and data gathering for marine environment monitoring around Korean Peninsula by using an eight channel Geostationary Ocean Color Imager(GOCI). The third mission is newly developed Ka-Band communication payload certification test in space by providing communication service in Korean Peninsula and Manjurian area. There were many low Earth orbit satellites for ocean monitoring. However, there has never been any geostationary satellite for ocean monitoring. The COMS is going to be the first satellite for ocean monitoring mission on the geo-stationary orbit. The meteorological image and data obtained by the COMS will be distributed to end users in Asia-Pacific area and it will contribute to the improved weather forecast.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.605-612
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• 2010

Numberous satellites have monitored the Earth in order to detect changes in a large area. These satellites provide orbit information such as ephemeris data, RPC coefficients and etc. besides image data. If we can use such orbit data afforded by satellite, we can reduce the number of control point for geo-referencing. This paper shows the efficient geometric correction method of strip-satellite RADARSAT-l SAR images acquired by same orbit using ephemeris data, single control point and virtual control points. For accuracy analysis of proposed method, this paper compared the image geometrically corrected by the proposed method to the image corrected by ERDAS Imagine.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.803-803
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• 2002

Several environmental problems have occurred and extremely affected throughout the East Asia region. Satellite imageries and spatial information have been used in the applications of environmental and natural hazard management for years. Sharing these data and resources in the community is considered as one of the optimal solution. It would consequently bring cost saving to all participated countries and eventually be beneficial to mankind as a whole. Encouraged by these factors, ASEAN＋3 Satellite Image Archive for Environmental Study project was submitted by Thailand in the 3rd Senior Official Meeting between ASEAN, China, Japan and Korea (SEOM＋3 Meeting) and approved by the SEOM＋3. The main objectives of this project are to share satellite images, information related to natural resources and environmental issues, and to provide data information services to all ASEAN＋3 countries. The proposed system is basically embedded by distributed system. The network of data users, data providers, and the center will be established using the Internet. User can access, navigate, display, and even download some archived contents. Its service site can be generally categorized into two parts, which are environmental related data archive and the Integrated satellite image catalogue. The extension of web based GIS is also planned for future development so that GIS users can conduct some preliminary analysis directly on line. This presentation will indicate scope of work, system, working scenario, and work plan of the project.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.69-73
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• 2017

In this paper, we developed a real-time image recognition algorithm based on machine learning and tested the performance of the algorithm. The real-time image recognition algorithm recognizes the input image in real-time based on the machine-learned image data. In order to test the performance of the real-time image recognition algorithm, we applied the real-time image recognition algorithm to the autonomous vehicle and showed the performance of the real-time image recognition algorithm through the application of the autonomous vehicle.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.53-56
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• 2008

Generally, the quality of satellite images is expressed by GSD (Ground Sample Distance), MTF (Modulation Transfer Function) and SNR (Signal to Noise Ratio). However, these factors are technology-oriented and do not explain interpretability of satellite images. We need a standardized index which shows standard of interpretability. In this study, we estimated NIIRS (National Imagery Interpretability Rating Scale) through the GIQE (General Image Quality Equation) which is able to judge image interpretability with the standardized index. Traditionally, NIIRS has been determined manually by specialized image analysts. We used the GIQE in order to reduce inefficiency and high costs cause by manual interpretation and to produce accurate NIIRS. For monitoring image degradation, we estimated GIQE physical parameters from image analysis and carried out time series analysis about the quality of the KOMPSAT-1 images. On all of the tests, we were able to identify the image degradation due to the changing time. This indicates that NIIRS derived from GIQE will be used for image degradation indicator.