• 대한원격탐사학회지
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• 제19권3호
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• pp.191-200
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• 2003

Remote sensing division of satellite technology research center (SaTReC) , Korea advanced institute of science and technology (KAIST) has developed a ground receiving and processing system for high resolution satellite images. The developed system will be adapted and operated to receive, process and distributes images acquired from of the second Korean Multi-purpose Satellite (KOMPSAT-2), which will be launched in 2004. This project had initiated to develop and Koreanize the state-of-the-art technologies for the ground receiving system for high resolution remote sensing images, which range from direct ingestion of image data to the distribution of products through precise image correction. During four years development from Dec. 1998 until Aug. 2002, the system had been verified in various ways including real operation of custom-made systems such as a prototype system for SPOT and a commercialized system for KOMPSAT-1. Currently the system is under customization for installation at KOMPSAT-2 ground station. In this paper, we present accomplished work and future work.

• 대한원격탐사학회지
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• 제19권6호
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• pp.479-490
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• 2003

This study proposed a modified anisotropic diffusion restoration for image classification. The anisotropic diffusion restoration uses a probabilistic model based on Markov random field, which represents geographical connectedness existing in many remotely sensed images, and restores them through an iterative diffusion processing. In every iteration, the bonding-strength coefficient associated with the spatial connectedness is adaptively estimated as a function of brightness gradient. The gradient function involves a constant called "temperature", which determines the amount of discontinuity and is continuously decreased in the iterations. In this study, the proposed method has been extensively evaluated using simulated images that were generated from various patterns. These patterns represent the types of natural and artificial land-use. The simulated images were restored by the modified anisotropic diffusion technique, and then classified by a multistage hierarchical clustering classification. The classification results were compared to them of the non-restored simulation images. The restoration with an appropriate temperature considerably reduces error in classification, especially for noisy images. This study made experiments on the satellite images remotely sensed on the Korean peninsula. The experimental results show that the proposed approach is also very effective on image classification in remote sensing.

• 대한원격탐사학회지
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• 제19권5호
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• pp.351-361
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• 2003

As the launches of a series of remote sensing satellites, there are various multiresolution and multi-spectral images available nowadays. This diversity in remotely sensed image data has created a need to be able to integrate data from different sources. The C-band imaging radar of ERS-2 due to its high sensitivity to coastal wetlands holds tremendous potential in mapping and monitoring coastal wetland features. This paper investigates the advantages of using ERS-2 SAR data combined with IRS-ID LISS-3 data for mapping complex coastal wetland features of Tamil Nadu, southern India. We present a methodology in this paper that highlights the mapping potential of different combinations of filtering and integration techniques. The methodology adopted here consists of three major steps as following: (i) speckle noise reduction by comparative performance of different filtering algorithms, (ii) geometric rectification and coregistration, and (iii) application of different integration techniques. The results obtained from the analysis of optical and microwave image data have proved their potential use in improving interpretability of different coastal wetland features of southern India. Based visual and statistical analyzes, this study suggests that brovey transform will perform well in terms of preserving spatial and spectral content of the original image data. It was also realized that speckle filtering is very important before fusing optical and microwave data for mapping coastal mangrove wetland ecosystem.

• Journal of the Optical Society of Korea
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• 제17권1호
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• pp.103-108
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• 2013

The operation of a Doppler wind LIDAR in a mobile environment is very sensitive to shocks and vibrations, which can cause critical failures such as misalignment of the optical path and damage to optical components. To be able to stabilize the LIDAR and to perform wind field measurements in motion, a shock absorption and vibration isolation system was designed and implemented. The performance of the vehicle-mounted Doppler wind LIDAR was tested in motion, first in a circular test route with a diameter of about 30 m and later in regular expressway traffic. The vibration isolation efficiency of the system was found to be higher than 82% in the main vibration area and shock dynamic deflection was smaller than maximal deflection of the isolator. The stability of the laser locking frequency in the same mobile environment before and after the vibration isolation system installation was also found to be greatly improved. The reliability of the vibration isolation system was confirmed by good results of the analysis of the LIDAR data, in particular the plane position indicator of the line of sight velocity and the wind profile.

• 대한원격탐사학회지
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• 제35권1호
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• pp.163-177
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• 2019

As inter-Korean relations progress, the issue of natural disasters which could directly affect the lives of the people in both Koreas, has not yet been discussed. Considering the current status of inter-Korean relations and the ongoing disaster-related damage in North Korea, it is imperative to establish a technical plan at the pan-governmental level to reduce the damage from natural disasters. The purpose of this study is to secure the Korea Peninsula against natural disasters by organizing South Korea's science and technologies related to natural disasters in order to reduce the damage, and to evaluate the applicability of said technologies. The situation of natural disasters in North Korea for 17 years has been summarized and reclassified based on eight types of natural disasters. Technologies related to natural disasters in South Korea were also investigated and reclassified. Based on the data, a priority evaluation was performed and the prioritization of technology application for each natural disaster type in North Korea was calculated through a quadrant analysis. As a result, the three major categories of high-priority technologies were classified as natural disaster monitoring with remote sensing and spatial information technology, construction of research basis and database based on geographic information system (GIS) and integrated management of complex natural disasters.

• 대한원격탐사학회지
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• 제35권1호
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• pp.137-149
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• 2019

Traffic emissions are the main cause of environmental pollution in cities and respiratory problems amongst people. This study developed a model based on an integration of support vector regression (SVR) algorithm and geographic information system (GIS) to map traffic carbon monoxide (CO) concentrations and produce prediction maps from micro level to macro level at a particular time gap in a day in a very densely populated area (Utara-Selatan Expressway-NKVE, Kuala Lumpur, Malaysia). The proposed model comprised two models: the first model was implemented to estimate traffic CO concentrations using the SVR model, and the second model was applied to create prediction maps at different times a day using the GIS approach. The parameters for analysis were collected from field survey and remote sensing data sources such as very-high-resolution aerial photos and light detection and ranging point clouds. The correlation coefficient was 0.97, the mean absolute error was 1.401 ppm and the root mean square error was 2.45 ppm. The proposed models can be effectively implemented as decision-making tools to find a suitable solution for mitigating traffic jams near tollgates, highways and road networks.

• 대한원격탐사학회지
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• 제35권4호
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• pp.535-544
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• 2019

This study demonstrated the ability of a Landsat-8 OLI multispectral data to identify and delineate hydrothermal alteration zones around auriferous prospects within the crystalline basement, North-western Nigeria. Remote sensing techniques have been widely used in lithological, structural discrimination and alteration rock delineation, and in general geological studies. Several artisanal mining activities for gold deposit occur in the surrounding areas within the basement complex and the search for new possible mineralized zones have heightened in recent times. Systematic Landsat-8 OLI data processing methods such as colour composite, band ratio and minimum noise fraction were used in this study. Colour composite of band 4, 3 and 2 was displayed in Red-Green-Blue colour image to distinguish lithologies. Band ratio ${\frac{4}{2}}$ image displayed in red was used to highlight ferric-ion bearing minerals(hematite, goethite, jarosite) associated with hydrothermal alteration, band ratio ${\frac{5}{6}}$ image displayed in green was used to highlight ferrous-ion bearing minerals such as olivine, amphibole and pyroxenes, while ratio ${\frac{6}{7}}$ image displayed in blue was used to highlight clay minerals, micas, talc-carbonates, etc. Band rationing helped to reduce the topographic illumination effect within images. The result of this study showed the distribution of the lithological units and the hydrothermal alteration zone which can be further prospected for mineral reserves.

• 대한원격탐사학회지
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• 제39권1호
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• pp.99-110
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• 2023

Land surface temperature (LST) is a critical environmental indicator affected by land cover (LC) changes. Currently, the most convenient and fastest way to retrieve LST is to use remote sensing images due to their continuous monitoring of the Earth's surface. The work intended to investigate land cover change and temperature response inAn-Najaf province. Landsat multispectral imageries acquired inAugust 1989, 2004, and 2021 were employed to estimate land cover change and LST responses. The findings exhibited an increase in water bodies, built-up areas, plantations, and croplands by 7.78%, 7.27%, 6.98%, 3.24%, and 7.78%, respectively, while bare soil decreased by 25.27% for the period (1989-2021). This indicates a transition from barren lands to different land cover types. The contribution index (CI) was employed to depict how changes in land cover categories altered mean region surface temperatures. The highest LSTs recorded were in bare lands (42.2℃, 44.25℃, and 46.9℃), followed by built-up zones (41.6℃, 43.96℃, and 44.89℃), cropland (30.9℃, 32.96℃, and 34.76℃), plantations (35.4℃, 36.97℃, and 38.92℃), and water bodies (27.3℃, 29.35℃, and 29.68℃) respectively, in 1989, 2004, and 2021. Consequently, these changes resulted in significant variances in LST between different LC types.

• 대한원격탐사학회지
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• 제39권4호
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• pp.459-466
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• 2023

In the last decade, artificial intelligence's dramatic advancement with the development of various deep learning techniques has significantly contributed to remote sensing fields and satellite image applications. Among many prominent areas, super-resolution research has seen substantial growth with the release of several benchmark datasets and the rise of generative adversarial network-based studies. However, most previously published remote sensing benchmark datasets represent spatial resolution within approximately 10 meters, imposing limitations when directly applying for super-resolution of small objects with cm unit spatial resolution. Furthermore, if the dataset lacks a global spatial distribution and is specialized in particular land covers, the consequent lack of feature diversity can directly impact the quantitative performance and prevent the formation of robust foundation models. To overcome these issues, this paper proposes a method to generate benchmark datasets by simulating the modulation transfer functions of the sensor. The proposed approach leverages the simulation method with a solid theoretical foundation, notably recognized in image fusion. Additionally, the generated benchmark dataset is applied to state-of-the-art super-resolution base models for quantitative and visual analysis and discusses the shortcomings of the existing datasets. Through these efforts, we anticipate that the proposed benchmark dataset will facilitate various super-resolution research shortly in Korea.

• Advances in aircraft and spacecraft science
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• 제10권1호
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• pp.67-82
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• 2023

Linear array imaging sensors are widely used in remote sensing satellites. The final products of an imaging sensor can only be used when they are geometrically, radiometrically, and spectrally calibrated. Therefore, at the first stages of sensor design, a detailed calibration procedure must be carefully planned based on the accuracy requirements. In this paper, focusing on inherent optical distortion, a step-by-step procedure for laboratory geometric calibration of a typical push-broom satellite imaging sensor is simulated. The basis of this work is the simulation of a laboratory procedure in which a linear imager mounted on a rotary table captures images of a pin-hole pattern at different angles. By these images and their corresponding pinhole approximation, the correction function is extracted and applied to the raw images to give the corrected ones. The simulation results illustrate that using this approach, the nonlinear effects of distortion can be minimized and therefore the accuracy of the geometric position of this method on the image screen can be improved to better than the order of sub-pixel. On the other hand, the analyses can be used to proper laboratory facility selection based on the imaging sensor specifications and the accuracy.