• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.95-104
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• 2022

This study aims to find the exact area of the forest fire in Okgye-myeon, Gangneung, April 4, 2019. Since there is a gradient in our country's forests, we should find a surface area that takes into account The 5th numerical clinical map provided by the DEM and the Korea Forest Service provided by the National Geographic Information Service was used. In DEM, the center point of each pixel was created and all points were connected. The length of the connecting line is determined by the spatial resolution of the pixel and the cosine value, and the surface area is obtained along with the height value, which is called the Slope-Aspect algorithm. The surface area and floor area of the forest were shown according to the tree species and types of forest, and their quantitative numerical differences proved the validity of this study.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.29-42
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• 2016

Remote sensing allows acquisition of information across a large area without contacting objects, and has thus been rapidly developed by application to different areas. Thus, with the development of remote sensing, satellites are able to rapidly advance in terms of their image resolution. As a result, satellites that use remote sensing have been applied to conduct research across many areas of the world. However, while research on remote sensing is being implemented across various areas, research on data processing is presently insufficient; that is, as satellite resources are further developed, data processing continues to lag behind. Accordingly, this paper discusses plans to maximize the performance of satellite image processing by utilizing the CUDA(Compute Unified Device Architecture) Library of NVIDIA, a parallel processing technique. The discussion in this paper proceeds as follows. First, standard KOMPSAT(Korea Multi-Purpose Satellite) images of various sizes are subdivided into five types. NDVI(Normalized Difference Vegetation Index) is implemented to the subdivided images. Next, ArcMap and the two techniques, each based on CPU or GPU, are used to implement NDVI. The histograms of each image are then compared after each implementation to analyze the different processing speeds when using CPU and GPU. The results indicate that both the CPU version and GPU version images are equal with the ArcMap images, and after the histogram comparison, the NDVI code was correctly implemented. In terms of the processing speed, GPU showed 5 times faster results than CPU. Accordingly, this research shows that a parallel processing technique using CUDA Library can enhance the data processing speed of satellites images, and that this data processing benefits from multiple advanced remote sensing techniques as compared to a simple pixel computation like NDVI.

• Korean Journal of Agricultural Science
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• v.37 no.1
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• pp.81-86
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• 2010

The urban thermal environment can be an important index to detect heat island phenomena and manage it to improve urban life quality. Cheongju is a typical plain-city that main part has been formed and developed in lowland. The Mushim stream crosses the city from south to north. We reviewed the use of thermal remote sensing in stream around areas and the thermal environments, focusing primarily on the Urban Heat Island(UHI) effect. The purpose of this study is to determine the relationship between the stream nearby urban area and the stream cooling effect of UHI. The objectives are to determine the usefulness of KOMPSAT-2 bands MS3 and MS4 for vegetation cover mapping, and the usefulness of LANDSAT TM band 6 in identifying thermal environmental characteristics and UHI. Land Surface Temperatures (LST) are retrieved by single-channel algorithm to study the UHI from the 6th band (thermal infrared band) of LANDSAT TM images and thermal radiance thermometer based on remote sensing method and the LST distribution maps are accomplished according to the retrieval results. There is also comparison of satellite-derived and in situ measured temperature. The results indicated that the LST of urban center is higher than that of suburban area, the temperature of mountain and water are the lowest area, so it is clearly proved that there are obvious UHI effects by stream. The surface temperature distribution of Mushim stream is detected $2^{\circ}C$ lower than urban area.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.2
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• pp.31-39
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• 2008

In this paper, the definition and the requirement from Users of standardization of high resolution satellite image data will be presented. If Users do not use the satellite image data, the satellite will be useless thing though it has been developed and operated now. The standardization of the satellite image data will make Users use the image data with no problem, so KARI has to do the standardization of it as a space agency that has developed and operated the satellite. For the standardization of it, the technical requirement to develop the satellite, the international standardization for the satellite image data and the requirement from Users will be reflected into the satellite development, and then the format and content of the satellite image data to Users have to be accommodated with the standard format of it. In addition to it, the calibration and validation just make sure of the quality of the satellite image data. For this, KARI has just been doing the standardization of KOMPSAT series in stages.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.130-133
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• 2007

In order to get high quality and high resolution image data from the space-borne camera system, the image chain from the sensor to the user in the ground-station need to be designed and controlled with extreme care. The behavior of the camera system needs to be controlled by ground commands to support on-orbit calibration and to adjust imaging parameters and to perform early stage on-orbit image correction, like gain and offset control, non-uniformity correction, etc. The operation status including the temperature of the sensor needs to be transferred to the ground-station. The preparation time of the camera system for imaging with specific parameters should be minimized. The camera controller needs to synchronize the operation of cameras for every channel and for every spectral band. Detail timing information of the image data needs to be provided for image data correction at ground-station. In this paper, the design of the camera controller for the AEISS on KOMPSAT-3 will be introduced. It will be described how the image chain is controlled and which imaging parameters are to be adjusted The camera controller will have software for the flexible operation of the camera by the ground-station operators and it can be reconfigured by ground commands. A simple concept of the camera operations and the design of the camera controller, not only with hardware but also with controller software are to be introduced in this paper.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1943-1949
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• 2021

In recent years, as the demand of high-resolution satellite images increases due to the miniaturization and constellation of satellites, various efforts to support users to utilize satellite images more conveniently are performed. Accordingly, the Korea Aerospace Research Institute produces and provides mosaic images on the Korean Peninsula every year to improve the convenience of users in the public sector and activate the use of satellite images. In order to increase the utilization of mosaic images on the Korean Peninsula, a study on satellite image segmentation and classification using mosaic images was attempted. However, since mosaic images provide only R, G, and B bands and processes such as image sharpening and color balancing are applied, there is a limitation that the spectral information of original images is distorted, so various indices were extracted and classified using R, G, and B bands to compensate for this. As a result of the study, the accuracy of image classification results using only mosaic images was about 72%, while the accuracy of image classification results using indices extracted from R, G, and B bands together was about 79%. Through this, it was confirmed that when performing image classification using mosaic images on the Korean Peninsula, the image classification results can be improved if the indices extracted from R, G, and B bands are used together. These research results are expected to be applied not only to mosaic images but also to images in which spectral information is limited or only R, G, and B bands are provided.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1101-1117
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• 2018

The clear sky radiance (CSR) is one of the baseline products of the Himawari-8 which was launched on October, 2014. The CSR contributes to numerical weather prediction (NWP) accuracy through the data assimilation; especially water vapor channel CSR has good impact on the forecast in high level atmosphere. The focus of this study is the quality analysis of the CSR of the Himawari-8 geostationary satellite. We used the operational CSR (or clear sky brightness temperature) products in JMA (Japan Meteorological Agency) as observation data; for a background field, we employed the CSR simulated using the Radiative Transfer for TOVS (RTTOV) with the atmospheric state from the global model of KMA (Korea Meteorological Administration). We investigated data characteristics and analyzed observation minus background statistics of each channel with respect to regional and seasonal variability. Overall results for the analysis period showed that the water vapor channels (6.2, 6.9, and $7.3{\mu}m$) had a positive mean bias where as the window channels(10.4, 11.2, and $12.4{\mu}m$) had a negative mean bias. The magnitude of biases and Uncertainty result varied with the regional and the seasonal conditions, thus these should be taken into account when using CSR data. This study is helpful for the pre-processing of Himawari-8/Advanced Himawari Imager (AHI) CSR data assimilation. Furthermore, this study also can contribute to preparing for the utilization of products from the Geo-Kompsat-2A (GK-2A), which will be launched in 2018 by the National Meteorological Satellite Center (NMSC) of KMA.

• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.26-38
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• 2021

In this paper, DLKF (Deep Learning Keypoint Filtering), the deep learning-based keypoint filtering method for the rapidization of the image registration method for remote sensing images is proposed. The complexity of the conventional feature-based image registration method arises during the feature matching step. To reduce this complexity, this paper proposes to filter only the keypoints detected in the artificial structure among the keypoints detected in the keypoint detector by ensuring that the feature matching is matched with the keypoints detected in the artificial structure of the image. For reducing the number of keypoints points as preserving essential keypoints, we preserve keypoints adjacent to the boundaries of the artificial structure, and use reduced images, and crop image patches overlapping to eliminate noise from the patch boundary as a result of the image segmentation method. the proposed method improves the speed and accuracy of registration. To verify the performance of DLKF, the speed and accuracy of the conventional keypoints extraction method were compared using the remote sensing image of KOMPSAT-3 satellite. Based on the SIFT-based registration method, which is commonly used in households, the SURF-based registration method, which improved the speed of the SIFT method, improved the speed by 2.6 times while reducing the number of keypoints by about 18%, but the accuracy decreased from 3.42 to 5.43. Became. However, when the proposed method, DLKF, was used, the number of keypoints was reduced by about 82%, improving the speed by about 20.5 times, while reducing the accuracy to 4.51.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1283-1298
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• 2018

KOPRI(Korea Polar Research Institute) have researhed Arctic sea ice by using satellite remote sensing data since 2017 as a mission of KOPRI. The title of the reseach is "Development of Satellite Observation and Analysis for Arctc sea-ice". This project has three major aims; 1) development of prototype satellite data archive/manage system for Arctic sea ice monitoring, 2) development of sea ice remote sensing data processing and analysis technique, and 3) development of international satellite observing network for Arcitc. This reseach will give us that 1) deveolpment of sea ice observing system for northern sea route, 2) development of optimal remote sensing data processing technique for sea ice and selected satelite sensors, 3) development of international satellite onbservation network. I hope that this letter of introducton KOPRI satellite program for Arctic will help to understand Arctic remote sensing and will introduce you to step into the Arctic remote sensing, which Iis like a blue ocean of remote sensing.