• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.4
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• pp.372-380
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• 2022

This study proposes a distributed parallel processing system, called the Fast Analysis System for remote sensing daTa(FAST), for large-scale satellite image processing and analysis. FAST is a system that designs jobs in vertices and sequences, and distributes and processes them simultaneously. FAST manages data based on the Hadoop Distributed File System, controls entire jobs based on Apache Spark, and performs tasks in parallel in multiple slave nodes based on a docker container design. FAST enables the high-performance processing of progressively accumulated large-volume satellite images. Because the unit task is performed based on Docker, it is possible to reuse existing source codes for designing and implementing unit tasks. Additionally, the system is robust against software/hardware faults. To prove the capability of the proposed system, we performed an experiment to generate the original satellite images as ortho-images, which is a pre-processing step for all image analyses. In the experiment, when FAST was configured with eight slave nodes, it was found that the processing of a satellite image took less than 30 sec. Through these results, we proved the suitability and practical applicability of the FAST design.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.87-94
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• 2015

The increasing demands and utilization of the multi-purpose satellites have led to diverse research activities with regards to satellite image processing and applications. In the domestic development project for the Compact Advanced Satellite, it is a goal to develop the satellite with the domestic individual technique performing a various tasks such as the earth observation, the monitoring of the weather, climate and environment. In particular, the Compact Advanced Satellite is expect to be widely used in the agricultural sector, which account for a substantial part of public demand. This paper aims at establishing the way to utilize the satellite imagery in the domestic institution and the strategy for securing the specialized satellite payload in the agriculture sector. The technical element of satellite has a high value, so that it is hard to be transferred technology. For this reason, it is required to establish the domestic development planning. Furthermore, this paper can be utilized to identify and support the incoming Compact Advanced Satellite development plan utilizing satellite images capabilities specially in agricultural sector.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.137-143
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• 2013

The high resolution satellite images are used in many fields such as weather observation, remote sensing, military facilities monitoring, cultural properties protection etc. Although satellite images are obtained in same satellite imaging system, the satellite images are degraded depending on the condition of hardware(optical device, satellite operation altitude, image sensor, etc.). Due to the fact that changing the hardware of satellite imaging system is impossible for resolution enhancement of these degraded satellite after launching a satellite, therefore the method of resolution enhancement with satellite images is necessary. In this paper the resolution is enhances by using a Super Resolution(SR) algorithm. The SR algorithm is an algorithm to enhance the resolution of an image by uniting many low resolution images, so an output image has higher resolution than using other interpolation methods. But It is difficult to obtain many images of the same area. Therefore, to solve this problem, we applied SR after by applying the affine and projection transform. As a results, we found that the images applied SR after affine and projection transform have higher resolution than the images only applied SR.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1931-1942
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• 2021

As the utility of an optical satellite image with a high spatial resolution (i.e., fine-scale) has been emphasized, recently, various studies of the land surface monitoring using those have been widely carried out. However, the usefulness of fine-scale satellite images is limited because those are acquired at a low temporal resolution. To compensate for this limitation, the spatiotemporal data fusion can be applied to generate a synthetic image with a high spatio-temporal resolution by fusing multiple satellite images with different spatial and temporal resolutions. Since the spatio-temporal data fusion models have been developed for mid or low spatial resolution satellite images in the previous studies, it is necessary to evaluate the applicability of the developed models to the satellite images with a high spatial resolution. For this, this study evaluated the applicability of the developed spatio-temporal fusion models for KOMPSAT-3A and Sentinel-2 images. Here, an Enhanced Spatial and Temporal Adaptive Fusion Model (ESTARFM) and Spatial Time-series Geostatistical Deconvolution/Fusion Model (STGDFM), which use the different information for prediction, were applied. As a result of this study, it was found that the prediction performance of STGDFM, which combines temporally continuous reflectance values, was better than that of ESTARFM. Particularly, the prediction performance of STGDFM was significantly improved when it is difficult to simultaneously acquire KOMPSAT and Sentinel-2 images at a same date due to the low temporal resolution of KOMPSAT images. From the results of this study, it was confirmed that STGDFM, which has relatively better prediction performance by combining continuous temporal information, can compensate for the limitation to the low revisit time of fine-scale satellite images.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.2
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• pp.90-98
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• 2008

In recent, image data compression method of high resolution satellite image is the important issue for its application and development. The CCSDS (Consultative Committee for Space Data Systems) published a standard for the high resolution image data compression, CCSDS 122.0-B-1, in the end of 2005, which is expected to be widely applied in process of compression for the high resolution satellite images. In this paper, it is explained that the current trends of image compression methods for high resolution satellites, and then the comparison results between CCSDS 122.0-B-1 standard and JPEG are described.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.210-221
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• 2022

In order to promptly respond to disasters, the era of new spaces has opened where satellite images with various characteristics can be used. As the number of satellites in operation at home and abroad increases and the characteristics of satellite sensors vary, it is necessary to find satellite images optimized for disaster types. Disaster types were divided into typhoons, heavy rains, droughts, forest fires, etc., and the optimal satellite images were selected for each type of disaster considering satellite orbits, active/passive sensors, spatial resolution, wavelength bands, and revisit cycles. Each satellite orbit TLE (Two Line Element) information was applied to the SGP4 (Simplified General Perturbations version 4) model to develop a satellite orbit simulation algorithm. The developed algorithm simulated the satellite orbit at 10-second intervals and selected an accurate observation area by considering the angle of incidence of each sensor. The satellite orbit simulation algorithm was applied to the case of Typhoon Mitag in 2019 and compared with the actual satellite list. Through the analyzed results, the time and area of the captured image and the image to be recorded were analyzed within a few seconds to select the optimal satellite image according to the type of disaster. In the future, it is intended to serve as a basis for building a system that can promptly request and secure satellite images in the event of a disaster.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1157-1158
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• 2008

This paper describes the interface designs of Optical-Camera Electronic unit with a DFPA(Detector Focal Plane Assembly) and IDHU(Image Data Handling Unit) which meet the top-level requirement of a satellite system. Especially, the designs on the image format and timing of the Header information for the correct reconstruction of the image in the Groundstation are explained in detail.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1383-1385
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• 2003

Remote sensing has been widely used in the exploration of groundwater. In this paper, on the establishment of empirical function between ground water and soil moisture content 6S code is used to reduce uncertainties in the remote sensing of groundwater. Then ground water levels are calculated using 6S corrected and uncorrected ETM+ image along with isochronous meteorological information. Greater correspondence between field examined and satellite monitoring data is obtained from corrected image than from the uncorrected image.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.141-144
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• 2007

Satellite image for national land monitoring is required high resolution and natural color with multi spectral band. the image is expensive as higher resolution. We need cheap image relatively in economic viewpoint but the image serves sufficient resolution to monitor national land. We merged two images to one image and evaluated the result. the two images which are used at the merge test are high resolution(2.5m per pixel) panchromatic and low resolution(10m per pixel) multi spectral image of SPOT-5 satellite. The result of this study. We made the merge image to have sufficient resolution for national monitoring.

• Journal of the Korean Geographical Society
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• v.47 no.2
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• pp.282-296
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• 2012

This study compared effects of spatial resolution ratio in image fusion by Korea Multi-Purpose SATellite 2 (KOMPSAT II), also known as Arirang-2. Image fusion techniques, also called pansharpening, are required to obtain color imagery with high spatial resolution imagery using panchromatic and multi-spectral images. The higher quality satellite images generated by an image fusion technique enable interpreters to produce better application results. Thus, image fusions categorized in 3 domains were applied to find out significantly improved fused images using KOMPSAT 2. In addition, all fused images were evaluated to satisfy both spectral and spatial quality to investigate an optimum fused image. Additionally, this research compared Pixel-Based Image Analysis (PBIA) with the GEOgraphic Object-Based Image Analysis (GEOBIA) to make better classification results. Specifically, a roof top of building was extracted by both image analysis approaches and was finally evaluated to obtain the best accurate result. This research, therefore, provides the effective use for very high resolution satellite imagery with image interpreter to be used for many applications such as coastal area, urban and regional planning.