• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.547-553
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• 2020

As aging infrastructures increase along with time, the efficient maintenance becomes more significant and accurate responses from the sensors are pre-requisite. Among various responses, strain is commonly used to detect damage such as crack and fatigue. Optical fiber sensor is one of the promising sensing techniques to measure strains with high-durability, immunity for electrical noise, long transmission distance. Fiber Bragg Grating (FBG) is a point sensor to measure the strain based on reflected signals from the grating, while Brillouin Optic Correlation Domain Analysis (BOCDA) is a distributed sensor to measure the strain along with the optical fiber based on scattering signals. Although the FBG provides the signal with high accuracy and reproducibility, the number of sensing points is limited. On the other hand, the BOCDA can measure a quasi-continuous strain along with the optical fiber. However, the measured signals from BOCDA have low accuracy and reproducibility. This paper proposed a multi-fidelity data-fusion method based on Gaussian Process Regression to improve the fidelity of the strain distribution by fusing the advantages of both systems. The proposed method was evaluated by laboratory test. The result shows that the proposed method is promising to improve the fidelity of the strain.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1025-1034
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• 2022

In this paper, we propose a post-processing method through interpolation of hole regions that occur when extracting point clouds. When image matching is performed on stereo image data, holes occur due to occlusion and building façade area. This area may become an obstacle to the creation of additional products based on the point cloud in the future, so an effective processing technique is required. First, an initial point cloud is extracted based on the disparity map generated by applying stereo image matching. We transform the point cloud into a grid. Then a hole area is extracted due to occlusion and building façade area. By repeating the process of creating Triangulated Irregular Network (TIN) triangle in the hall area and processing the inner value of the triangle as the minimum height value of the area, it is possible to perform interpolation without awkwardness between the building and the ground surface around the building. A new point cloud is created by adding the location information corresponding to the interpolated area from the grid data as a point. To minimize the addition of unnecessary points during the interpolation process, the interpolated data to an area outside the initial point cloud area was not processed. The RGB brightness value applied to the interpolated point cloud was processed by setting the image with the closest pixel distance to the shooting center among the stereo images used for matching. It was confirmed that the shielded area generated after generating the point cloud of the target area was effectively processed through the proposed technique.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1257-1271
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• 2022

Recently, many Earth observation optical satellites have been developed, as their demands were increasing. Therefore, a rapid preprocessing of satellites became one of the most important problem for an active utilization of satellite images. Satellite image matching is a technique in which two images are transformed and represented in one specific coordinate system. This technique is used for aligning different bands or correcting of relative positions error between two satellite images. In this paper, we propose an automatic image matching method among satellite images with different ground sampling distances (GSDs). Our method is based on improved feature matching and robust estimation of transformation between satellite images. The proposed method consists of five processes: calculation of overlapping area, improved feature detection, feature matching, robust estimation of transformation, and image resampling. For feature detection, we extract overlapping areas and resample them to equalize their GSDs. For feature matching, we used Oriented FAST and rotated BRIEF (ORB) to improve matching performance. We performed image registration experiments with images KOMPSAT-3A and RapidEye. The performance verification of the proposed method was checked in qualitative and quantitative methods. The reprojection errors of image matching were in the range of 1.277 to 1.608 pixels accuracy with respect to the GSD of RapidEye images. Finally, we confirmed the possibility of satellite image matching with heterogeneous GSDs through the proposed method.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.471-484
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• 2022

This study examined the effects of topography and buildings around the automated synoptic observing system (ASOS) on the observation environment of air temperatures and wind speeds and directions using a computational fluid dynamics(CFD) model. For this, we selected 10 ASOSs operated by the Korea Meteorological Administration. Based on the data observed at the ASOSs in August during the recent ten years, we established the initial and boundary conditions of the CFD model. We analyzed the temperature observation environment by comparing the temperature change ratios in the case considering the actual land-cover types with those assuming all land-cover types as grassland. The land-cover types around the ASOSs significantly affected the air temperature observation environment. The temperature change ratios were large at the ASOSs around which buildings and roads were dense. On the other hand, when all land covers were assumed as grassland, the temperature change ratios were small. Wind speeds and directions at the ASOSs were also significantly influenced by topography and buildings when their heights were higher or similar to the observation heights. Obstacles even located at a long distance affected the wind observation environments. The results in this study would be utilized for evaluating ASOS observation environments in the relocating or newly organizing steps.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.43-54
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• 2022

The settlement at the railroad foundation is often the leading cause of track irregularity and potential derailment. The control of such deformation is considered necessary in track maintenance practice. Nevertheless, the monitoring process performed by in situ surveying requires an excessive amount of manpower and cost. The InSAR, a remote sensing technique by RADAR satellite, is used to overcome such a burden. The PS-InSAR technique is preferred for a long-term precise monitoring method. However, this study aims to obtain relatively brief analysis results from only two satellite images using the D-InSAR technique, while a minimum of 25 images are required for PS-InSAR. This study verifies the precision of D-InSAR within a few millimeters by inspecting railroad facilities and land settlements in Korea Railroad Research Institute's test track with images from TerraSAR-X Satellite. Multiple corner reflectors were adopted and installed on an embankment and the building roof to raise the surface reflectivity. Those reflectors were slightly adjusted periodically to verify the detecting performance. The results revealed the optimum distance between corner reflectors. Further, the deformation of railway tracks, slopes, and concrete structures was analyzed successively. In conclusion, this study indicates that the D-InSAR technique effectively monitors the short-term deformation of a broad area such as railway structures.

• Research in Plant Disease
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• v.28 no.1
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• pp.1-18
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• 2022

Volatiles exist ubiquitously in nature. Volatile compounds produced by plants and microorganisms confer inter-kingdom and intra-kingdom communications. Autoinducer signaling molecules from contact-based chemical communication, such as bacterial quorum sensing, are relayed through short distances. By contrast, biogenic volatiles derived from plant-microbe interactions generate long-distance (>20 cm) alarm signals for sensing harmful microorganisms. In this review, we discuss prior work on volatile compound-mediated diagnosis of plant diseases, and the use of volatile packaging and dispensing approaches for the biological control of fungi, bacteria, and viruses. In this regard, recent developments on technologies to analyze and detect microbial volatile compounds are introduced. Furthermore, we survey the chemical encapsulation, slow-release, and bio-nano techniques for volatile formulation and delivery that are expected to overcome limitations in the application of biogenic volatiles to modern agriculture. Collectively, technological advances in volatile compound detection, packaging, and delivery provide great potential for the implementation of ecologically-sound plant disease management strategies. We hope that this review will help farmers and young scientists understand the nature of microbial volatile compounds, and shift paradigms on disease diagnosis and management to aromatic (volatile-based) agriculture.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.467-479
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• 2023

Satellite altimeters have continuously observed sea surface height (SSH) in the global ocean for the past 30 years, providing clear evidence of the rise in global mean sea level based on observational data. Accurate altimeter-observed SSH is essential to study the spatial and temporal variability of SSH in regional seas. In this study, we used measurements from the Ieodo Ocean Research Station (IORS) and validate SSHs observed by satellite altimeters (Envisat, Jason-1, Jason-2, SARAL, Jason-3, and Sentinel-3A/B). Bias and root mean square error of SSH for each satellite ranged from 1.58 to 4.69 cm and 6.33 to 9.67 cm, respectively. As the matchup distance between satellite ground tracks and the IORS increased, the error of satellite SSHs significantly amplified. In order to validate the correction of the tide and atmospheric effect of the satellite data, the tide was estimated using harmonic analysis, and inverse barometer effect was calculated using atmospheric pressure data at the IORS. To achieve accurate tidal corrections for satellite SSH data in the seas around the Korean Peninsula, it was confirmed that improving the accuracy of tide data used in satellites is necessary.

• 대한공업교육학회지
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• v.34 no.2
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• pp.346-362
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• 2009

The purpose of this study was to develop the handy non-contact measurement device of the surface roughness by using the optical fiber sensor. The advantages of fiber optic sensors are high-speed responsibility, non-effect of the magnetic, convenience of the product and high precision. The measurement theory for surface roughness of optical fiber sensor is one to one correspondence between the reflected light intensity based on the surface roughness of the object and the measurement value of previously known for surface roughness. The reflected light intensity was determined using the distance to the surface from the sensor probe and the limit reflection angle based on the surface roughness. Therefore, in this study, the sensor probe was produced for determining the value of surface roughness only using the limit reflection angle based on the surface roughness with the fixed distance from the surface. A prototype measurement system was composed of a transmitting part, a receiving part and a signal processing circuit. The materials of standard measurement which was used in this experiment were SM45C, STS303 and Al60. According to the results of this study, approximation surface roughness formulas which was deduced from the correlation of between the standard surface roughness and the sensing output were verified that they were effect against the surface roughness measurement value of the option sample. And handy optical fiber surface roughness measurement device which was produced by an order was verified that it was effect for measuring of the precision surface roughness.

• Journal of the Korean association of regional geographers
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• v.9 no.4
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• pp.519-533
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• 2003

The U.S. Conservation Reserve Program (CRP) resulted in the conversion of approximately 14.8 million ha(36.5 million acres) of cropland to grassland, woodland, and other conservation uses throughout the U.S. between 1986 and 1992. One of the major results of CRP has been the addition of millions of hectares of potential wildlife habitat. primarily as grassland. In this study, we examined regional changes in landscape structure caused by the introduction of CRP. Utilizing multi-seasonal Landsat Thematic Mapper imagery, we produced maps of cropland and grassland for the pre- and post- CRP enrollment periods for a six-county region in southwest Kansas. We then applied post-classification differencing to identify regions of cropland that had been converted to CRP. Using the FRAGSTATS spatial pattern analysis program, we calculated a variety of spatial statistics to analyze changes in landscape structure due to CRP. The major impact of CRP in the six-county study area has been the reversal of an overall trend of grassland habitat fragmentation. From the standpoint of potential wildlife habitat, the introduction of CRP has greatly increased the number of patches, mean patch size, and the interior or core area of grassland patches. In addition, CRP has increased connectivity and aggregation between grassland patches, potentially important factors for species of conservation interest, particularly those that require larger expanses of unbroken habitat. Finally, the distance between neighboring patches of grassland has decreased, reducing travel distance between patches. Clearly, the introduction of CRP has substantially modified the spatial structure of the southwest Kansas landscape, with important implications for wildlife habitat.

• Journal of Korean Society of Rural Planning
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• v.21 no.3
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• pp.171-179
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• 2015

The objectives of this research have been focussed on 1) developing prediction techniques for the flash flood and landslide based on rainfall prediction data in agricultural area and 2) developing an integrated forecasting system for the abrupt disasters using USN based real-time disaster sensing techniques. This study contains following steps to achieve the objective; 1) selecting rainfall prediction data, 2) constructing prediction techniques for flash flood and landslide, 3) developing USN and communication network protocol for detecting the abrupt disaster suitable for rural area, & 4) developing mobile application and SMS based early warning service system for local resident and tourist. Local prediction model (LDAPS, UM1.5km) supported by Korean meteorological administration was used for the rainfall prediction by considering spatial and temporal resolution. NRCS TR-20 and infinite slope stability analysis model were used to predict flash flood and landslide. There are limitations in terms of communication distance and cost using Zigbee and CDMA which have been used for existing disaster sensors. Rural suitable sensor-network module for water level and tilting gauge and gateway based on proprietary RF network were developed by consideration of low-cost, low-power, and long-distance for communication suitable for rural condition. SMS & mobile application forecasting & alarming system for local resident and tourist was set up for minimizing damage on the critical regions for abrupt disaster. The developed H/W & S/W for integrated abrupt disaster forecasting & alarming system was verified by field application.