• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1299-1308
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• 2023

Forest fires are becoming more frequent and larger around the world due to climate change. Remote sensing such as satellite images can be used as an alternative or assistance data because it reduces various difficulties of field survey. Forest burn severity (differenced normalized burn ratio, dNBR) is calculated through the difference in normalized burn ratio (NBR) before and after a forest fire. The images used in the NBR formula are based on Landsat's near-infrared (NIR) and short-wavelength infrared (SWIR) bands. South Korea's satellite images don't have a SWIR band. So domestic studies related to forest burn severity calculated dNBR using overseas images or indirectly using the normalized difference vegetation index (NDVI) using South Korea's satellite images. Therefore, in this study, dNBR was calculated by substituting the mid-wavelength infrared (MWIR) band of Kompsat-3A (K3A) instead of the SWIR band in the NBR formula. The results were compared with the dNBR results obtained through Landsat which is the standard for dNBR formula. As a result, it was shown that dNBR using K3A's MWIR band has a wider range of values and can be expressed in more detail than dNBR using Landsat's SWIR band. Therefore, it is considered that K3A images will be highly useful in surveying burn areas and severity affected by forest fires. In addition, this study used the K3A's MWIR band images degraded to 30 m. It is considered that much better results will be obtained if a higher-resolution MWIR band is used.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.130-133
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• 2005

This paper presents the efficient method to detect the defective detectors of the SWIR band of SPOT 4. The key of this method are to flatten the baseline of the data using high pass band filter instead of differentiation. This method is made up six steps. First step is to apply image enhancement techniques to enhance the lines imaged by defective detector and improve the quality of an image. Second step is processed by summing the enhanced image in line direction. These summed data have the peaks that represent the defective detectors and the curved baseline characterized by the reflectivity of Earth surface. In order to exactly detect these peaks, third step is to flatten the curved baseline using high pass filtering in the frequency domain. In fourth step, the data with flat baseline is normalized to have zero mean and unity standard deviation. In fifth step, the defective detectors are detected using $99.9\%$ confidence interval. Finally, after removing the detected ones in summed data, the steps from third to five are iterated. Three SPOT 4 images, which have different reflectivity of Earth surface and different sensor, were used to validate this method. The overall accuracy of detection for three images was $97.9\%$. This result shows that this method can detect efficiently the lines made by defective detectors.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.305-311
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• 2006

Although there have been several attempts to estimate forest LAI using optical remote sensor data, there are still not enough evidences whether the NDVI is effective to estimate forest LAI, particularly in fully closed canopy situation. In this study, we have conducted a simple correlation analysis between LAI and spectral reflectance at two different settings: 1) laboratory spectral measurements on the multiple-layers of leaf samples and 2) Landsat ETM+ reflectance in the close canopy forest stands with fieldmeasured LAI. In both cases, the correlation coefficients between LAI and spectral reflectance were higher in short-wave infrared (SWIR) and visible wavelength regions. Although the near-IR reflectance showed positive correlations with LAI, the correlations strength is weaker than in SWIR and visible region. The higher correlations were found with the spectral reflectance data measured on the simulated vegetation samples than with the ETM+ reflectance on the actual forests. In addition, there was no significant correlation between the forest.LAI and NDVI, in particular when the LAI values were larger than three. The SWIR reflectance may be important factor to improve the potential of optical remote sensor data to estimate forest LAI in close canopy situation.

• Journal of Sensor Science and Technology
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• v.31 no.2
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• pp.125-130
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• 2022

We describe the importance of zinc oxide nanoparticle (ZnO NP) concentration in the enhancement of electrical properties in a lead sulfide quantum dot (PbS QD)-based shortwave infrared (SWIR) photodetector. ZnO NPs were synthesized using the sol-gel method. The concentration of the ZnO NPs was controlled as 20, 30 and 40 mg/mL in this study. Note that the ZnO NPs layer is commonly used as an electron transport layer in PbS QDs SWIR photodetectors. The photo-to-dark ratio, which is an important parameter of a photodetector, was intensively examined to evaluate the electrical performance. The 20 mg/mL condition of ZnO NPs exhibited the highest photo-to-dark ratio value of 5 at -1 V, compared with 1.8 and 0.4 for 30 mg/mL and 40 mg/mL, respectively. This resulted because the electron mobility decreased when the concentration of ZnO NPs was higher than the optimized value. Based on our results, the concentration of ZnO NPs was observed to play an important role in the electrical performance of the PbS QDs SWIR photodetector.

• Economic and Environmental Geology
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• v.49 no.5
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• pp.335-347
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• 2016

The mineralogical and geochemical characteristics of diverse carbonate rocks can be investigated by using VNIRSWIR(visible near infrared-short wavelength infrared) spectroscopic analysis as a rapid, nondestructive, and inexpensive tool. Comparing whole rock analysis to VNIR-SWIR spectroscopic analysis, the analytical method was investigated to estimate CaO contents, mud impurity, and whiteness of carbonate rocks involved in high-grade limestones in the field. We classify typical carbonate rocks in the upper Pungchon Formation in high-grade limestone mine area such as the Gangweon, Chungmu and Baegun mine in the Jeongseon area. The results show that powdered specimen has much higher reflectance than cutted specimen between the same sample. Whiteness is highly correlated with reflectance(0.99) for powdered specimen. The absorption of mineral mixtures shifts in position as a result of the mass ratio of calcite and dolomite in the Chungmu mine by changing to 75:25, 50:50, and 25:75. The absorption peak position in carbonate mixtures is highly correlated with CaO contents(0.98~0.99). Based on color system, the carbonate rocks are grouped into (milky) white, light grey, light brown, grey, and dark grey. The absorption peak position shifts from 2340 nm to 2320 nm as CaO contents decrease from 55.86 wt.% to 29.71 wt.%. We confirmed that absorption peak position shifts depending on the amount of Ca, which is bonded to $CO{_3}^{-2}$, Mg, and Fe contents replacing Ca. This result suggests that CaO contents in carbonate rocks can be considered to quantitative analysis in the field by spectroscopic analysis.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.2
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• pp.328-335
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• 2010

A hyperspectral imaging spectrometer has shown significant advantages in performance over other existing ones for remote sensing applications. It can collect hundreds of narrow, adjacent spectral bands for each image, which provides a wealth of information on unique spectral characteristics of objects. We have developed a compact hyperspectral imaging system that successively shows high spatial and spectral resolutions and fast data processing performance. In this paper, we present an overview of the hyperspectral imaging system including the strucure of geometrical optics and several image processing schemes such as wavelength calibration and noise reduction for image data on Visible and Near-Infrared(VNIR) and Shortwave-Infrared(SWIR) band.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1027-1029
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• 2003

The primary uses of SWIR bands of ASTER data are to analyze geological features. In this study, we are attempting to evaluate the effect of using the narrow band A STER data for extracting information related to biophysical information of forest vegetation. ASTER and ETM+ data have been obtained simultaneously over the study area in Kyongan-River basin on May 8, 2003. Two data sets were initially processed to reduce atmospheric effects and converted to percent reflectance values, which make them comparable each other. ASTER and ETM+ reflectance were then analyzed by using the field survey data that include forest leaf area index (LAI), cover types, species composition, and stand density. Preliminary results show that ASTER reflectance were not much different to ETM+ reflectance to explain LAI.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1005-1005
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• 2003

The purpose of this study is to evaluate the potential application of TERRA-ASTER data in Thailand. ASTER VNIR, SWIR and TIR data covering greater Bangkok and Chiangmai province were processed with various techniques in the spatial domain to study the applicability to various disciplines. ASTER data was also combined with other satellite data in order to utilize multi-sensor methods. It was found that VNIR data can clearly identify urban pattern including road network and vegetation index. While SWIR and TIR data can well separate between urban and non urban area and TIR data can differentiate among thermal surfaces. Furthermore, dense urban areas such as central business area could be highlighted. Land utilization, vegetable distribution and differences of temperature distribution were investigated.

• Proceedings of the KSEEG Conference
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• 2002.04a
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• pp.341-343
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• 2002

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.43-43
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• 2017

종자산업은 농작물 생산에 중요한 역할을 끼치는 좌우하는 요소 중에 하나로, 우량종자의 확보는 농작물 수급에 중요한 역할을 하는 농업부문의 원천산업이다. 오이 녹반 모자이크 바이러스(CGMMV)는 박과류에 가장 많은 피해를 끼치는 바이러스로 종자전염을 방지하고, 우량종자의 공급을 위해서는 감염종자와 비 감염종자의 판별은 필수적이다. 이에 본 연구에서는 초분광 영상 시스템을 이용하여 수박종자의 CGMMV의 감염 및 비 감염종자를 판별할 수 있는 기술을 개발하고자 하였다. 본 연구에서 사용된 바이러스 감염 종자는 CGMMV 바이러스 감염 수박종자를 사용하였으며, 생산된 종자를 초분광 영상 시스템을 통해 스크린 후, RNA를 추출하여 PCR분석법으로 바이러스의 감염유무를 확인하였으며, 이후 바이러스의 감염유무와 획득된 스펙트럼을 비교 분석하여 판별모델을 개발하고 이를 선별 시스템에 적용하였다. 모델개발에 사용된 초분광 영상 기술은 초분광 SWIR(Shortwave infraed : 1000-2500nm)영상 기술이 다. 획득된 초분광 SWIR 영상을 분석한 결과 바이러스 감염 종자가 유의미한 정확도로 판별이 되는 것으로 나타났다. 초분광 SWIR 영상기술이 바이러스 감염종자와 비감염종자를 비파괴적으로 선별하는데 효과적으로 적용이 가능할 것으로 판단된다.