• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.61-68
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• 2016

Digital aerial images have been commonly used in a large scale map production owing to their excellent geometry, and high spatial and radiometric resolution in recent years. However, a quality verification process for acquired images should be preceded in order to secure the high precision and reliability of produced results. Several experimental studies to verify digital imaging systems have been vigorously researched by constructing permanent test field in abroad. On the other hand, it is urgently necessary to suggest a practical scheme for an image quality verification, because this related study and experiment are still in its early stage at home. Hence, this study aims to present an easy method to measure the spatial resolution of the image in a visual way using a portable Siemens star. The images used in the study were obtained with three different cameras, two frame array sensors of DMC, UltraCamXp and a linear array sensor of ADS80. The Siemens star target appeared in every image is extracted and then the spatial resolution of image is compared with theoretical GSD(Ground Sample Distance) by a visual method. In addition, the change of spatial resolution depending on the location of the Siemens star from image center and flight direction and cross-flight direction is also compared and analyzed. As study results, while the theoretical GSDs of images taken with each camera are about 6~9cm, the visual resolutions are 1.2~1.3 times as great as the theoretical ones.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.363-371
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• 2014

Most space-borne optical scanning systems adopt linear arrayconfigurations. The well-knownthree different types of space-borne sensors arealong-track line scanner, across-track linescanner, and three line scanner. To acquire accurate location information of an object on the ground withthose sensors, the exterior and interior orientation parameters are critical factors for both of space-borne and airborne missions. Since the imaging geometry of sensors mightchange time to time due to thermal influence, vibration, and wind, it is very important to analyze the Interior Orientation Parameters (IOP) effects on the ground. The experiments based on synthetic datasets arecarried out while the focal length biases are changing. Also, both high and low altitudes of the imagingsensor were applied. In case with the along-track line scanner, the focal length bias caused errors along the scanline direction. In the other case with the across-track one, the focal length bias caused errors alongthe scan line and vertical directions. Lastly, vertical errors were observed in the case ofthree-line scanner. Those results from this study will be able to provide the guideline for developing new linearsensors, so as for improving the accuracy of laboratory or in-flight sensor calibrations.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.309-324
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• 2008

In this study the retrieval algorithms have been developed to retrieve total precipitable water (TPW) from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) infrared measurements using a physical iterative retrieval method and a split-window technique over East Asia. Retrieved results from these algorithms were validated against Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) over ocean and radiosonde observation over land and were analyzed for investigating the key factors affecting the accuracy of results and physical processes of retrieval methods. Atmospheric profiles from Regional Data Assimilation and Prediction System (RDAPS), which produces analysis and prediction field of atmospheric variables over East Asia, were used as first-guess profiles for the physical retrieval algorithm. We used RTTOV-7 radiative transfer model to calculate the upwelling radiance at the top of the atmosphere. For the split-window technique, regression coefficients were obtained by relating the calculated brightness temperature to the paired radiosonde-estimated TPW. Physically retrieved TPWs were validated against SSM/I and radiosonde observations for 14 cases in August and December 2004 and results showed that the physical method improves the accuracy of TPW with smaller bias in comparison to TPWs of RDAPS data, MODIS products, and TPWs from split-window technique. Although physical iterative retrieval can reduce the bias of first-guess profiles and bring in more accurate TPWs, the retrieved results show the dependency upon initial guess fields. It is thought that the dependency is due to the fact that the water vapor absorption channels used in this study may not reflect moisture features in particular near surface.

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.341-369
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• 2005

Hyperspectral images have emerged as a new and promising remote sensing data that can overcome the limitations of existing optical image data. This study was designed to provide a comprehensive review on definition, data processing methods, and applications of hyperspectral data. Various types of airborne, spaceborne, and field hyperspectral image sensors were surveyed from the available literatures and internet search. To understand the current status of hyperspectral remote sensing technology and research development, we collected several hundreds research papers from international journals (IEEE Transactions on Geoscience and Remote Sensing, International Journal of Remote Sensing, Remote Sensing of Environment and AVIRIS Workshop Proceedings), and categorized them by sensor types, data processing techniques, and applications. Although several hyperspectral sensors have been developing, AVIRIS has been a primary data source that the most hyperspectral remote sensing researches were relied on. Since hyperspectral data have very large data volume with many spectral bands, several data processing techniques that are particularly oriented to hyperspectral data have been developed. Although atmospheric correction, spectral mixture analysis, and spectral feature extraction are among those processing techniques, they are still in experimental stage and need further refinement until the fully operational adaptation. Geology and mineral exploration were major application in early stage of hyperspectral sensing because of the distinct spectral features of rock and minerals that could be easily observed with hyperspectral data. The applications of hyperspectral sensing have been expanding to vegetation, water resources, and military areas where the multispectral sensing was not very effective to extract necessary information.

• Journal of Sensor Science and Technology
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• v.28 no.1
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• pp.41-46
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• 2019

In order to develop novel thermal imaging materials for microbolometer applications, $[(Ni_{0.3}Mn_{0.7})_{1-x}Cu_x]_3O_4$ ($0.18{\leq}x{\leq}0.26$) thin films were fabricated using metal-organic decomposition. Effects of Cu content on the electrical properties of the annealed films were investigated. Spinel thin films with a thickness of approximately 100 nm were obtained from the $[(Ni_{0.3}Mn_{0.7})_{1-x}Cu_x]_3O_4$ films annealed at $380^{\circ}C$ for five hours. The resistivity (${\rho}$) of the annealed films was analyzed with respect to the small polaron hopping model. Based on the $Mn^{3+}/Mn^{4+}$ ratio values obtained through x-ray photoelectron spectroscopy analysis, the hopping mechanism between $Mn^{3+}$ and $Mn^{4+}$ cations discussed in the proposed study. The effects of $Cu^+$ and $Cu^{2+}$ cations on the hopping mechanism is also discussed. Obtained results indicate that $[(Ni_{0.3}Mn_{0.7})_{1-x}Cu_x]_3O_4$ thin films with low temperature annealing and superior electrical properties (${\rho}{\leq}54.83{\Omega}{\cdot}cm$, temperature coefficient of resistance > -2.62%/K) can be effectively employed in applications involving complementary metal-oxide semiconductor (CMOS) integrated microbolometer devices.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.375-387
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• 2019

The use of drone-based hyperspectral image offers considerable advantages in high resolution remote sensing applications. The primary objective of this study was to select the optimal bands based on hyperspectral image for the estimation yield of the chinese cabbage. The hyperspectral narrow bands were acquired over 403.36 to 995.19 nm using a 3.97 nm wide, 150 bands, drone-based hyperspectral imaging sensor. Fresh weight data were obtained from 2,031 sample for each field survey. Normalized difference vegetation indices were computed using red, red-edge and near-infrared bands and their relationship with quantitative each fresh weights were established and compared. As a result, predominant proportion of fresh weights are best estimated using data from three narrow bands, in order of importance, centered around 697.29 nm (red band), 717.15 nm (red-edge band) and 808.51 nm (near-infrared band). The study determined three spectral bands that provide optimal chinese cabbage productivity in the visible and near-infrared portion of the spectrum.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.701-709
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• 2019

Recently, heart rate signal, which is one of biological signals, have been used in various fields related to healthcare. Conventionally, most of the proposed heart rate signal detection methods are contact type methods, but there is a problem of discomfort that the subject have to contact with the device. In order to solve the problem, detection study by non-contact method has been progressed recently. The detected heart rate signal can be used for finger vein liveness detection and various application using heart rate. In this paper, we propose a method to obtain heart rate signal by using finger vein imaging system. The proposed method detected the signal from the changes of the brightness value in the time domain of the infrared finger vein images and converted it into the frequency domain using the image processing algorithm. After the conversion, we removed the noise not related to the heart rate signal through band-pass filtering. In order to evaluate the accuracy of the signal, we analyzed the correlation with the signal obtained simultaneously with the finger vein acquisition device and contact type PPG sensor approved by KFDA. As a result, it was possible to confirm that the heart rate signal detected in non-contact method through the finger vein image coincides with the waveform of actual heart rate signal.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.217-226
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• 2022

In the view of the application of high-precision spatial information production, UAV (Umanned Aerial Vehicle)-Photogrammetry has a problem in that it lacks specific procedures and detailed regulations for quantitative quality verification methods or certification of captured images. In addition, test tools for UAV image quality assessment use only the GSD (Ground Sample Distance), not MTF (Modulation Transfer Function), which reflects image resolution and contrast at the same time. This fact makes often the quality of UAV image inferior to that of manned aerial image. We performed MTF and GSD analysis simultaneously using a siemens star to confirm the necessity of MTF analysis in UAV image quality assessment. The analyzing results of UAV images taken with different payload and sensors show that there is a big difference in σ_MTF values, representing image resolution and the degree of contrast, but slightly different in GSD. It concluded that the MTF analysis is a more objective and reliable analysis method than just the GSD analysis method, and high-quality drone images can only be obtained when the operator make images after judging the proper selection the sensor performance, image overlaps, and payload type. However, the results of this study are derived from analyzing only images acquired by limited sensors and imaging conditions. It is therefore expected that more objective and reliable results will be obtained if continuous research is conducted by accumulating various experimental data in related fields in the future.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.301-308
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• 2022

Algae is an indispensable primary producer in the ecosystem by supplying energy to consumers in the aquatic ecosystem, and is largely divided into green algae, blue-green algae, and diatoms. In the case of blue-green algae, the water temperature rises, which occurs in the summer and overgrows, which is the main cause of the algae bloom. Recently, the change in the occurrence time and frequency of the algae bloom is increasing due to climate change. Existing algae survey methods are performed by collecting water and measuring through sensors, and time, cost and manpower are limited. In order to overcome the limitations of these existing monitoring methods, research has been conducted to perform remote monitoring using spectroscopic devices such as multispectral and hyperspectral using satellite image, UAV, etc. In this study, we tried to confirm the possibility of species classification of remote monitoring through laboratory-scale experiments through algal culture and river water collection. In order to acquire hyperspectral images, a hyperspectral sensor capable of analyzing at 400-1000 nm was used. In order to extract the spectral characteristics of the collected river water for classification of algae species, filtration was performed using a GF/C filter to prepare a sample and images were collected. Radiation correction and base removal of the collected images were performed, and spectral information for each sample was extracted and analyzed through the process of extracting spectral information of algae to identify and compare and analyze the spectral characteristics of algae, and remote sensing based on hyperspectral images in rivers and lakes. We tried to review the applicability of monitoring.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.135-143
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• 2009

Integrating the Global Positioning System (GPS) and Inertial Navigation System (INS) sensor technologies using the precise GPS Carrier phase measurements is a methodology that has been widely applied in those application fields requiring accurate and reliable positioning and attitude determination; ranging from 'kinematic geodesy', to mobile mapping and imaging, to precise navigation. However, such integrated system may not fulfil the demanding performance requirements when the baseline length between reference and mobil user GPS receiver is grater than a few tens of kilometers. This is because their positioning/attitude determination is still very dependent on the errors of the GPS observations, so-called "baseline dependent errors". This limitation can be remedied by the integration of GPS and INS sensors, using multiple reference stations. Hence, in order to derive the GPS distance dependent errors, this research proposes measurement processing algorithms for multiple reference stations, such as a reference station ambiguity resolution procedure using linear combination techniques, a error estimation based on Kalman filter and a error interpolation. In addition, all the algorithms are evaluated by processing real observations and results are summarized in this paper.