• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.285-289
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• 2023

Recently, the demand for lidar systems for autonomous driving is increasing, and research on Shortwave Infrared(SWIR) photodetectors for this purpose is being actively conducted. Most SWIR photodetectors currently being developed are based on InGaAs, and have the disadvantages of complex processes, high prices, and limitations in research due to monopoly. In addition, current SWIR photodetectors use lasers in the 905 nm wavelength band, which can pass through the pupil and cause damage to the retina. Therefore, it is required to develop a SWIR photodetector using a wavelength band of 1400 nm or more to be safe for human eyes, and to develop a material that can replace the proprietary InGaAs. PbS QDs are group 4-6 compound semiconductors whose absorption wavelength band can be adjusted from 1000 to 2700 nm, and have the advantage of being simple to process. Therefore, in this study, PbS QDs having an absorption wavelength peak of 1415 nm were synthesized, and a SWIR photodetector was fabricated using this. In addition, the photodetector's responsivity was improved by applying P3HT and ZnO NPs to improve electron hole mobility. As a result of the experiment, it was confirmed that the synthesized PbS QDs had excellent FWHM characteristics compared to commercial PbS QDs, and it was confirmed that the photodetector had a maximum current change of about 1.6 times.

• 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.

• Economic and Environmental Geology
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• v.57 no.5
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• pp.513-527
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• 2024

Methane is the second most significant greenhouse gas contributing to global warming after carbon dioxide, exerting a substantial impact on climate change. This paper provides a comprehensive review of satellite remote sensing-based methane detection technologies used to efficiently detect and quantify methane emissions. Methane emission sources are broadly categorized into natural sources (such as permafrost and wetlands) and anthropogenic sources (such as agriculture, coal mines, oil and gas fields, and landfills). This study focuses on anthropogenic sources and examines the principles of methane detection using information from various spectral bands, including the shortwave infrared (SWIR) band, and the utilization of key satellite data supporting these technologies. Recently, deep learning techniques have been applied in methane detection research using satellite data, contributing to more accurate analyses of methane emissions. Furthermore, this paper assesses the practicality of satellite-based methane monitoring by synthesizing case studies of methane emission detection at global, regional, and major incident scales, including examples of applying deep learning techniques. At the global scale, research utilizing satellite sensors like the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) was reviewed. At the regional scale, studies were highlighted where TROPOMI data was combined with relatively high-resolution satellite data, such as the Sentinel-2 MultiSpectral Instrument (MSI) and GHGSat Wide-Angle Fabry-Perot (WAF-P) Imaging Spectrometer, to detect methane emissions and sources. Through this comprehensive review, the current state and applicability of satellite-based methane detection technologies are evaluated.