• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1283-1297
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• 2023

Mid-wave infrared (MWIR) imagery, due to its ability to capture the temperature of land cover and objects, serves as a crucial data source in various fields including environmental monitoring and defense. The KOMPSAT-3A satellite acquires MWIR imagery with high spatial resolution compared to other satellites. However, the limited spatial resolution of MWIR imagery, in comparison to electro-optical (EO) imagery, constrains the optimal utilization of the KOMPSAT-3A data. This study aims to create a highly visible MWIR fusion image by leveraging the edge information from the KOMPSAT-3A panchromatic (PAN) image. Preprocessing is implemented to mitigate the relative geometric errors between the PAN and MWIR images. Subsequently, we employ a pre-trained pixel difference network (PiDiNet), a deep learning-based edge information extraction technique, to extract the boundaries of objects from the preprocessed PAN images. The MWIR fusion imagery is then generated by emphasizing the brightness value corresponding to the edge information of the PAN image. To evaluate the proposed method, the MWIR fusion images were generated in three different sites. As a result, the boundaries of terrain and objects in the MWIR fusion images were emphasized to provide detailed thermal information of the interest area. Especially, the MWIR fusion image provided the thermal information of objects such as airplanes and ships which are hard to detect in the original MWIR images. This study demonstrated that the proposed method could generate a single image that combines visible details from an EO image and thermal information from an MWIR image, which contributes to increasing the usage of MWIR imagery.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.233-242
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• 2010

SEBAL (Surface Energy Balance Algorithm for Land) developed by Bastiaanssen (1995) is an image-processing model comprisedof twenty-five sub models that calculates spatial evapotranspiration (ET) and other energy exchanges at the surface. SEBAL uses image data from Landsat or other satellites measuring thermal infrared radiation, visible and near infrared. In this study, the model was applied to Gyeongancheon watershed, the main tributary of Han river Basin. ET was computed on apixel-by-pixel basis from an energy balance using 4 years (2001-2004) Landsat and MODIS images. The scale effect between Landsat (30 m) and MODIS (1 km) was evaluated. The results both from Landsat and MODIS were compared with FAO Penman-Monteith ET. The absolute errors between satellite ETs and Penman-Monteith ET were within 12%. The spatial and temporal characteristics of ET distribution within the watershed were also analyzed.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.15-21
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• 2017

Following the successful launch of KOMPSAT-3 in May 2012, KOMPSAT-5 in August 2013, and KOMPSAT-3A in March 2015 have succeeded in launching the integrated operation of optical, radar and thermal infrared sensors in Korea. We have established a foundation to utilize the characteristics of each sensors. In order to overcome limitations in the range of application and accuracy of the application of a single sensor, multi-sensor image fusion techniques have been developed which take advantage of multiple sensors and complement each other. In this paper, we introduce the development of software (InFusion) for multi-sensor image fusion and valued-added product generation using KOMPSAT series. First, we describe the characteristics of each sensor and the necessity of fusion software development, and describe the entire development process. It aims to increase the data utilization of KOMPSAT series and to inform the superiority of domestic software through creation of high value-added products.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.123-131
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• 2011

Characteristics of sea surface temperature(SST) difference around Gwang-Yang steel Mill where can affect marine ecosystem in Gwang-Yang bay using 25 collected Landsat-7 ETM+ thermal infrared band data from 2000 to 2010. To analyze accuracy of SST from the Landsat-7 ETM+ thermal infrared image， satellite-induced SST was verfied by compared Yeo-Su tide station and Landsat thermal image. As a result, SST from Landsat-7 ETM+ is $1.22^{\circ}C$ lower than sea temperature from Yeo-Su tide station and correlation coefficient resulted in above 0.991 which means that correlation coefficient between Landsat image temperature and field sea temperature is relatively high. Five regions were selected to analyze sea surface temperature between near Gwang-Yang steel mill and the open sea and analyzed timeseries of sea surface temperature seasonally and regionally. Moreover, the additional analysis has been carried out by comparing the averaged temperatures of Gwang-Yang and Soon-Cheon bays using the dataset over a year.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.931-946
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• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.589-601
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• 2016

Sea surface currents were estimated by applying the Maximum Cross Correlation (MCC), Zero-mean Sum of Absolute Distances (ZSAD), and Zero-mean Sum of Squared Distances (ZSSD) algorithms to Himawari-8/Advanced Himawari Imager (AHI) thermal infrared channel data, and the comparative analysis was performed between the results of these algorithms. The sea surface currents of the Kuroshio Current region that were retrieved using each algorithm showed similar results. The ratio of errors to the total number of estimated surface current vectors had little difference according to the algorithms, and the time required for sea surface current calculation was reduced by 24% and 18%, relative to the MCC algorithm, for the ZSAD and ZSSD algorithms, respectively. The estimated surface currents were validated against those from satellite-tracked surface drifter and altimeter data, and the accuracy evaluation of these algorithms showed results within similar ranges. In addition, the accuracy was affected by the magnitude of brightness temperature gradients and the time interval between satellite image data.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.197-207
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• 2013

Difficulties of emissivity determination and atmospheric correction degrade the estimation accuracy of land surface temperature (LST). That is, since the emissivity determination of land surface material and the correction of atmospheric effect are not perfect, it is very difficult to estimate the precise LST from a thermal infrared image such as Landsat TM and ETM+, ASTER, etc. In this study, we propose an efficient method to estimate land surface temperature difference (LSTD) rather than LST from Landsat thermal band images. This method is based on the assumptions that 1) atmospheric effects are same over a image and 2) the emissivity of vegetation region is 0.99. To validate the performance of the proposed method, error sensitive analysis according to error variations of reference land surface temperature and the water vapor is performed. The results show that the estimated LSTD have respectively the errors of ${\pm}0.06K$, ${\pm}0.15K$ and ${\pm}0.30K$ when the water vapor error of ${\pm}0.302g/cm^2$ and the radiance differences of 0.2, 0.5 and $1.0Wm^{-2}sr^{-1}{\mu}m$ are considered. And also the errors of the LSTD estimation are respectively ${\pm}0.037K$, ${\pm}0.089K$, ${\pm}0.168K$ in the reference land surface temperature error of ${\pm}2.41K$. Therefore, the proposed method enables to estimate the LSTD with the accuracy of less than 0.5K.

• Publications of The Korean Astronomical Society
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• v.27 no.4
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• pp.111-116
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• 2012

Far-infrared observations provide crucial data for the investigation and characterisation of the properties of dusty material in the Interstellar Medium (ISM), since most of its energy is emitted between ~ 100 and $200{\mu}m$. We present the first all-sky image from a sensitive all-sky survey using the Japanese AKARI satellite, in the wavelength range $50-180{\mu}m$. Covering > 99% of the sky in four photometric bands with four filters centred at $65{\mu}m$, $90{\mu}m$, $140{\mu}m$, and $160{\mu}m$ wavelengths, this achieved spatial resolutions from 1 to 2 arcmin and a detection limit of < 10 MJy $sr^{-1}$, with absolute and relative photometric accuracies of < 20%. All-sky images of the Galactic dust continuum emission enable astronomers to map the large-scale distribution of the diffuse ISM cirrus, to study its thermal dust temperature, emissivity and column density, and to measure the interaction of the Galactic radiation field and embedded objects with the surrounding ISM. In addition to the point source population of stars, protostars, star-forming regions, and galaxies, the high Galactic latitude sky is shown to be covered with a diffuse filamentary-web of dusty emission that traces the potential sites of high latitude star formation. We show that the temperature of dust particles in thermal equilibrium with the ambient interstellar radiation field can be estimated by using $90{\mu}m$, $140{\mu}m$, and $160{\mu}m$ data. The FIR AKARI full-sky maps provide a rich new data set within which astronomers can investigate the distribution of interstellar matter throughout our Galaxy, and beyond.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.2
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• pp.52-61
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• 2018

Urban heat islands occur due to increases in the extent of artificial surfaces such as concrete, asphalt and high-rise buildings. In this regard, research into the use of satellite thermal infrared images for thermal environment analysis of urban areas is being carried out. However, such analysis of the characteristics of individual land cover with low-resolution satellite images suffers from limitations because land cover patterns in urban areas are complicated. Recently, UAV has been widely used, which can compensate for this limitation as it is able to acquire high-resolution images. In this paper, the accuracy of UAV infrared images is verified and the applicability of UAV in urban thermal environment analysis is examined by comparing the results with land surface temperatures from Landsat 8 thermal images. The results show a high positive correlation of temperature values at 0.95, and no statistically significant difference between the two groups. Comparisons of land surface temperature according to land cover showed that the largest difference observed was $4.63^{\circ}C$ in the Used area, and UAV images with small cell units reflected various surface temperatures. Furthermore, it was possible to analyze the surface temperatures of various green spaces such as wetlands and street tree areas, which can lower surface temperatures in urban areas, with street tree shadows reducing surface temperatures by about $4-6^{\circ}C$. UAV can easily and rapidly measure the surface temperature of urban areas and is able to analyze various types of green spaces. Thus, this is an effective tool for thermal environment analysis in urban areas to aid in the design or management of urban green spaces, as it can allow for land cover and the effects of the various green spaces.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.65.1-65.1
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• 2012

MIRIS (Multipurpose Infra-Red Imaging System) is the first Korean Infrared Space Telescope developed by KASI (Korea Astronomy and Space Science Institute), and is the main payload of STSAT-3 (Science and Technology Satellite-3). The FM (fight model) of MIRIS has been recently completed, and various performance tests have been made to measure system parameters such as readout noise, system gain, linearity, and dark current. Final thermal-vacumm test of the MIRIS and the vibration test of the electronics box have been performed. Band response tests showed good agreement with the initial design requirements. No significant dark difference was measured within the expected temperature variation range during observation in orbit. Using Pa-alpha band from a uniform source, the readout noise and system gain were measured by mean variance test. To obtain uniform flat image, flat fielding tests were made for each band, and the data will be compared to that obtained in orbit for calibration. The final version of MIRIS FM will be delivered in March, and it will be integrated into the satellite system for the AIT (Assembly Integration, Test) procedure. The launch of MIRIS is expected in November 2012.