• Journal of the Korea Concrete Institute
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• v.13 no.1
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• pp.16-22
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• 2001

Pretensioned spun high strength concrete (PHC) pile has to be quality-controlled and provided an adequate concrete cover to assure high load carrying capacity, impact resistance, economy, and durability. During spun pre-casting, the pile section is divided into several segregated layers such as laitance, paste, mortar, and concrete layers. Greater the thickness of segregated layers, more difficult it is to guarantee the capacity and the durability of PHC pile. The experimental study was performed to investigate the effects of centrifugal condition on the segregated layers of materials and the compressive strength of concrete for PHC pile. The considering factors in the test were centrifugal time and magnitude of centrifugal force. These factors have been found to have greater influence on the segregation than the concrete strength. The moderate centrifugal condition has to be considered to maintain quality assurance in the production of PHC pile, especially to provide the adequate concrete cover over its tendons.

• Journal of Korean Society on Water Environment
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• v.25 no.1
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• pp.58-68
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• 2009

Low impact development (LID) technique is relatively new concept to reduce surface runoff and pollutant loading from land cover by attempting to match predevelopment condition with various integrated management practices (IMPs). In this study, computational model for designing and evaluating LID, named LIDMOD, was developed based on SCS-CN method and applied at Andong bus terminal to evaluate LID applicapability and design retention/detention area for volume or peak flow control. LIDMOD simulated with 21 years simulation period that yearly surface runoff by post-development without LID was significantly higher than that with LID showing about 2.8 times and LID could reduce efficiently yearly surface runoff with 75% reduction of increased runoff by conventional post development. LIDMOD designed detention area for volume/peak flow control with 20.2% of total area by hybrid design. LID can also efficiently reduce pollutant load from land cover. Pollutant loads from post-development without LID was much higher than those from pre-development with showing 37 times for BOD, 2 times for TN, and 9 times for TP. Pollutant loads from post-development with LID represented about 57% of those without LID. Increasing groundwater recharge reducing cooling and heating fee, creating green refuge at building area can be considered as additional benefits of LID. At the point of reducing runoff and pollutant load, LID might be important technique for Korean TMDL and LIDMOD can be useful tool to calculate unit load for the case of LID application.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.2 s.8
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• pp.181-193
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• 1996

A new technique for land cover classification which applies digital image pre-classified by unsupervised classification technique, clustering, to Canonical Correlation Analysis(CCA) was proposed in this paper. Compared with maximum likelihood classification, the proposed technique had a good flexibility in selecting training areas. This implies that any selected position of training areas has few effects on classification results. Land cover of each cluster designated by CCA after clustering is able to be used as prior information for maximum likelihood classification. In case that the same training areas are used, accuracy of classification using Canonical Correlation Analysis after cluster analysis is better than that of maximum likelihood classification. Therefore, a new technique proposed in this study will be able to be put to practical use. Moreover this will play an important role in the construction of GIS database

• Atmosphere
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• v.27 no.2
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• pp.235-249
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• 2017

This paper describes methodology verifying near-surface predictability of numerical weather prediction models against the surface synoptic weather station network (SYNOP) observation. As verification variables, temperature, wind, humidity-related variables, total cloud cover, and surface pressure are included in this tool. Quality controlled SYNOP observation through the pre-processing for data assimilation is used. To consider the difference of topographic height between observation and model grid points, vertical inter/extrapolation is applied for temperature, humidity, and surface pressure verification. This verification algorithm is applied for verifying medium-range forecasts by a global forecasting model developed by Korea Institute of Atmospheric Prediction Systems to measure the near-surface predictability of the model and to evaluate the capability of the developed verification tool. It is found that the verification of near-surface prediction against SYNOP observation shows consistency with verification of upper atmosphere against global radiosonde observation, suggesting reliability of those data and demonstrating importance of verification against in-situ measurement as well. Although verifying modeled total cloud cover with observation might have limitation due to the different definition between the model and observation, it is also capable to diagnose the relative bias of model predictability such as a regional reliability and diurnal evolution of the bias.

• Journal of Biosystems Engineering
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• v.41 no.2
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• pp.126-137
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• 2016

Purpose: The overall objective of this study was to evaluate the vegetation fraction of soybeans, grown under different cropping conditions using an unmanned aerial vehicle (UAV) equipped with a red, green, and blue (RGB) camera. Methods: Test plots were prepared based on different cropping treatments, i.e., soybean single-cropping, with and without herbicide application and soybean and barley-cover cropping, with and without herbicide application. The UAV flights were manually controlled using a remote flight controller on the ground, with 2.4 GHz radio frequency communication. For image pre-processing, the acquired images were pre-treated and georeferenced using a fisheye distortion removal function, and ground control points were collected using Google Maps. Tarpaulin panels of different colors were used to calibrate the multi-temporal images by converting the RGB digital number values into the RGB reflectance spectrum, utilizing a linear regression method. Excess Green (ExG) vegetation indices for each of the test plots were compared with the M-statistic method in order to quantitatively evaluate the greenness of soybean fields under different cropping systems. Results: The reflectance calibration methods used in the study showed high coefficients of determination, ranging from 0.8 to 0.9, indicating the feasibility of a linear regression fitting method for monitoring multi-temporal RGB images of soybean fields. As expected, the ExG vegetation indices changed according to different soybean growth stages, showing clear differences among the test plots with different cropping treatments in the early season of < 60 days after sowing (DAS). With the M-statistic method, the test plots under different treatments could be discriminated in the early seasons of <41 DAS, showing a value of M > 1. Conclusion: Therefore, multi-temporal images obtained with an UAV and a RGB camera could be applied for quantifying overall vegetation fractions and crop growth status, and this information could contribute to determine proper treatments for the vegetation fraction.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.179-197
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• 2020

Topographic normalization reduces the terrain effects on reflectance by adjusting the brightness values of the image pixels to be equal if the pixels cover the same land-cover. Topographic effects are induced by the imaging conditions and tend to be large in high mountainousregions. Therefore, image analysis on mountainous terrain such as estimation of wildfire damage assessment requires appropriate topographic normalization techniques to yield accurate image processing results. However, most of the previous studies focused on the evaluation of topographic normalization on satellite images with moderate-low spatial resolution. Thus, the alleviation of topographic effects on multi-temporal high-resolution images was not dealt enough. In this study, the evaluation of terrain normalization was performed for each band to select the optimal technical combinations for rapid and accurate wildfire damage assessment using PlanetScope images. PlanetScope has considerable potential in the disaster management field as it satisfies the rapid image acquisition by providing the 3 m resolution daily image with global coverage. For comparison of topographic normalization techniques, seven widely used methods were employed on both pre-fire and post-fire images. The analysis on bi-temporal images suggests the optimal combination of techniques which can be applied on images with different land-cover composition. Then, the vegetation index was calculated from the images after the topographic normalization with the proposed method. The wildfire damage detection results were obtained by thresholding the index and showed improvementsin detection accuracy for both object-based and pixel-based image analysis. In addition, the burn severity map was constructed to verify the effects oftopographic correction on a continuous distribution of brightness values.

• Spatial Information Research
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• v.19 no.5
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• pp.1-11
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• 2011

This study mainly focused on the method of accurately extracting damage information in the im agery change detection process using the constructed high resolution aerial im agery. Bongwha-gun in Gyungsangbuk-do which had been severely damaged from a localized torrential downpour at the end of July, 2008 was selected as study area. This study utilized aerial im agery having photographing scale of 30cm gray image of pre-disaster and 40cm color image of post-disaster. In order to correct errors from the differences of the image resolution of pre-/post-disaster and time series, the prelim inary phase of image processing techniques such as normalizing, contrast enhancement and equalizing were applied to reduce errors. The extent of the damage was calculated using one to one comparison of the intensity of each pixel of pre-/post-disaster im aged. In this step, threshold values which facilitate to extract the extent that damage investigator wants were applied by setting difference values of the intensity of pixel of pre-/post-disaster. The accuracy of optimal image processing and the result of threshold values were verified using the error matrix. The results of the study enabled the early exaction of the extents of the damages using the aerial imagery with identical characteristics. It was also possible to apply to various damage items for imagery change detection in case of utilizing multi-band im agery. Furthermore, more quantitative estimation of the dam ages would be possible with the use of numerous GIS layers such as land cover and cadastral maps.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1100-1108
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• 2015

A camera-based real-time hand posture and gesture recognition system is proposed for controlling various devices inside automobiles. It uses an imaging system composed of a camera with a proper filter and an infrared lighting device to acquire images of hand-motion sequences. Several steps of pre-processing algorithms are applied, followed by a background normalization process before segmenting the hand from the background. The hand posture is determined by first separating the fingers from the main body of the hand and then by finding the relative position of the fingers from the center of the hand. The beginning and ending of the hand motion from the sequence of the acquired images are detected using pre-defined motion rules to start the hand gesture recognition. A set of carefully designed features is computed and extracted from the raw sequence and is fed into a decision tree-like decision rule for determining the hand gesture. Many experiments are performed to verify the system. In this paper, we show the performance results from tests on the 550 sequences of hand motion images collected from five different individuals to cover the variations among many users of the system in a real-time environment. Among them, 539 sequences are correctly recognized, showing a recognition rate of 98%.

• Journal of Korean Association for Spatial Structures
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• v.11 no.2
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• pp.139-149
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• 2011

A cable structures have the advantage that cover a large space without column but it is very sensitive to deal with shape control because of its flexibility. Especially, location of control member and needed elongation of member are important things. Therefore, the purpose of this paper is studied on displacement control technique for pre-stressed cable structures by force method considering order of control. The layout of this paper is as follows. Firstly, in section 2, the control technique by force method for cable structures is given. Secondly, section 3 briefly introduces simple cable net in order to apply control technique considering ordering of actuator. Finally, more complex example for effective member and the conclusion are in section 4 and 5, respectively.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.8
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• pp.243-252
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• 2023

Satellite imageries are at a greatest importance for land cover examining. Numerous studies have been conducted with satellite images and uses semantic segmentation techniques to extract information which has higher altitude viewpoint. The device which is taking these images must employee wireless communication links to send them to receiving ground stations. Wireless communications from a satellite are inevitably affected due to transmission errors. Evidently images which are being transmitted are distorted because of the information loss. Current semantic segmentation techniques are not made for segmenting distorted images. Traditional image enhancement methods have their own limitations when they are used for satellite images enhancement. This paper proposes an auto-encoder based image pre-enhancing method for satellite images. As a distorted satellite images dataset, images received from a real radio transmitter were used. Training process of the proposed auto-encoder was done by letting it learn to produce a proper approximation of the source image which was sent by the image transmitter. Unlike traditional image enhancing methods, the proposed method was able to provide more applicable image to a segmentation model. Results showed that by using the proposed pre-enhancing technique, segmentation results have been greatly improved. Enhancements made to the aerial images are contributed the correct assessment of land resources.