• Title/Summary/Keyword: Spatial experiment

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A Dynamic Variable Window-based Topographical Classification Method Using Aerial LiDAR Data (항공 라이다 데이터를 이용한 동적 가변 윈도우 기반 지형 분류 기법)

  • Sung, Chul-Woong;Lee, Sung-Gyu;Park, Chang-Hoo;Lee, Ho-Jun;Kim, Yoo-Sung
    • Spatial Information Research
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    • v.18 no.5
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    • pp.13-26
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    • 2010
  • In this paper, a dynamic variable window-based topographical classification method is proposed which has the changeable classification units depending on topographical properties. In the proposed scheme, to im prove the classification efficiency, the unit of topographical classification can be changeable dynamically according to the topographical properties and repeated patterns. Also, in this paper, the classification efficiency and accuracy of the proposed method are analyzed in order to find an optimal maximum decision window-size through the experiment. According to the experiment results, the proposed dynamic variable window-based topographical classification method maintains similar accuracy but remarkably reduce computing time than that of a fixed window-size based one, respectively.

SAMPLING ERROR ANALYSIS FOR SOIL MOISTURE ESTIMATION

  • Kim, Gwang-Seob;Yoo, Chul-sang
    • Water Engineering Research
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    • v.1 no.3
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    • pp.209-222
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    • 2000
  • A spectral formalism was applied to quantify the sampling errors due to spatial and/or temporal gaps in soil moisture measurements. The lack of temporal measurements of the two-dimensional soil moisture field makes it difficult to compute the spectra directly from observed records. Therefore, the space-time soil moisture spectra derived by stochastic models of rainfall and soil moisture was used in their record. Parameters for both models were tuned with Southern Great Plains Hydrology Experiment(SGP'97) data and the Oklahoma Mesonet data. The structure of soil moisture data is discrete in space and time. A design filter was developed to compute the sampling errors for discrete measurements in space and time. This filter has the advantage in its general form applicable for all kinds of sampling designs. Sampling errors of the soil moisture estimation during the SGP'97 Hydrology Experiment period were estimated. The sampling errors for various sampling designs such as satedlite over pass and point measurement ground probe were estimated under the climate condition between June and August 1997 and soil properties of the SGP'97 experimental area. The ground truth design was evaluated to 25km and 50km spatial gap and the temporal gap from zero to 5 days.

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Simmyung Laser System and Study on the X-ray Generation (신명 레이저와 X-선 발생 연구)

  • Kong, Hong-Jin;Han, Ki-Gwan;Kim, Nam-Seong;Kim, Hyun-Soo;Um, Ki-Young;Park, Jong-Rak;Lee, Jae-Youg;Shin, Yun-Sup;Han, Ki-Ho
    • Proceedings of the Optical Society of Korea Conference
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    • 1995.06a
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    • pp.185-189
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    • 1995
  • A high-power Nb:glass laser system(Simmyung I) has been contructed and tested. In this system, we used a Nb:YLF laser as a master oscillator, a 4-pass amplifier for pre-amplification, 5 stages of rod amplifiers, and spatial filtering and image reaying usits. The system has demonstrated in excess of 80J(2TW) with 40 psec(FWHM) pulse duration. Output energy, gain and spatial were measured at each amplification stage. With this laser system a preliminary X-ray generation experiment was performed. Pinhole images, X-ray diode signals and X-ray speriment were obtained for the irradiated target of copper. Detailed descriptions of the system performance and the X-tay generation experiment are presented.

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Two-stage Deep Learning Model with LSTM-based Autoencoder and CNN for Crop Classification Using Multi-temporal Remote Sensing Images

  • Kwak, Geun-Ho;Park, No-Wook
    • Korean Journal of Remote Sensing
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    • v.37 no.4
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    • pp.719-731
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    • 2021
  • This study proposes a two-stage hybrid classification model for crop classification using multi-temporal remote sensing images; the model combines feature embedding by using an autoencoder (AE) with a convolutional neural network (CNN) classifier to fully utilize features including informative temporal and spatial signatures. Long short-term memory (LSTM)-based AE (LAE) is fine-tuned using class label information to extract latent features that contain less noise and useful temporal signatures. The CNN classifier is then applied to effectively account for the spatial characteristics of the extracted latent features. A crop classification experiment with multi-temporal unmanned aerial vehicle images is conducted to illustrate the potential application of the proposed hybrid model. The classification performance of the proposed model is compared with various combinations of conventional deep learning models (CNN, LSTM, and convolutional LSTM) and different inputs (original multi-temporal images and features from stacked AE). From the crop classification experiment, the best classification accuracy was achieved by the proposed model that utilized the latent features by fine-tuned LAE as input for the CNN classifier. The latent features that contain useful temporal signatures and are less noisy could increase the class separability between crops with similar spectral signatures, thereby leading to superior classification accuracy. The experimental results demonstrate the importance of effective feature extraction and the potential of the proposed classification model for crop classification using multi-temporal remote sensing images.

Experiment and Analysis of Load-Bearing Insulations for Slabs Thermal Breaks composed by H-Shaped Stainless Steel and UHPC Blocks (H강재와 UHPC압축블록을 적용한 슬래브용 열교차단 단열구조체 실험 및 해석연구)

  • Kim, Jae Young;Lee, Ga Yoon;Yoo, Young Jong;An, Sang Hee;Lee, Kihak
    • Journal of Korean Association for Spatial Structures
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    • v.23 no.3
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    • pp.35-43
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    • 2023
  • This study aims to evaluate the structural safety of a structural thermal barrier, installed inside the structure of a building and performed the role of a load-bearing element and an insulation simultaneously, contributing to the realization of net-zero buildings. To ensure the reliability of the analysis model, the analysis results derived from LS-DYNA were compared with the experimental results. Based on the results shown through the flexural experiment, the reliability of the thermal cross-section insulation structure model for slabs was validated. In addition, the effect of the UHPC block on the load support performance and its contribution to vertical deflection was verified.

The Flexural Capacity of the U-flanged Truss Hybrid Beam considering the Tensile Force of Lattice Members (래티스재의 인장력을 고려한 U-플랜지 트러스 복합보의 휨 내력에 관한 연구)

  • Lee, Seong Min;Oh, Myoung Ho;Kim, Young Ho
    • Journal of Korean Association for Spatial Structures
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    • v.23 no.1
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    • pp.53-60
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    • 2023
  • A bending experiment was conducted to verify the structural performance of the U-flange truss hybrid bean using rebars or steel pipes to reinforce the upper compression zone. As a result of evaluating the bending strength of the truss hybrid beam according to the Structural Design Standard (KDS 14 2020: 2022) by introducing the lattice member as a tensile resistance element, the following conclusions were obtained. Considering the lattice element as a tensile resistance element, the nominal bending strength was increased by 38.57 to 47.90 kN.m. As a result of reviewing the experiment as to whether the flexural member has proper ductility, it was found that it is desirable to place appropriate rebars, steel quality plans, and lateral restraints on the upper and lower parts of the hybrid beam to have sufficient ductility ratio.

A Study on the Features of Visual-Information Acquirement Shown at Searching of Spatial Information - With the Experiment of Observing the Space of Hall in Subway Station - (공간정보의 탐색과정에 나타난 시각정보획득특성에 관한 연구 - 지하철 홀 공간의 주시실험을 대상으로 -)

  • Kim, Jong-Ha
    • Korean Institute of Interior Design Journal
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    • v.23 no.2
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    • pp.90-98
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    • 2014
  • This study has analyzed the meaning of observation time in the course of acquiring the information of subjects who observed the space of hall in subway stations to figure out the process of spatial information excluded and the features of intensive searching. The followings are the results from the analysis of searching process with the interpretation of the process for information acquirement through the interpretation of observation area and time. First, based on the general definition of observation time, the reason for analyzing the features of acquiring spatial information according to the subjects' observation time has been established. The feature of decreased analysis data reflected that of observation time in the process of perceiving and recognizing spatial information, which showed that the observation was focused on the enter of the space during the time spent in the process of observing the space and the spent time with considerable exclusion of bottom end (in particular, right bottom end). Second, while the subjects were observing the space of hall in subway stations, they focused on the top of the left center and the signs on the right exit the most, which was followed by the focus on the both side horizontally and the clock on the top. Third, the analysis of consecutive observation frequency enabled the comparison of the changes to the observation concentration by area. The difference of time by area produced the data with which the change to the contents of spatial searching in the process of searching space could be known. Fourth, as the observation frequency in the area of I changed [three times -> six times -> 9 times], the observation time included in the area increased, which showed the process for the change from perception to recognition of information with the concentration of attention through visual information. It makes it possible to understand that more time was spent on the information to be acquired with the exclusion of the unnecessary information around.

Texture Image Generation Technique Considering Storage Optimization of 3D-Spatial Data (3차원 공간자료의 저장 공간 최적화를 고려한 텍스쳐 생성기법 연구)

  • Jin, Gi-Ho;Ha, Sung-Ryong
    • Journal of Digital Contents Society
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    • v.15 no.4
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    • pp.457-464
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    • 2014
  • Recently, interests in space information data are increasing due to the initiation of spatial information open platform service by the Ministry of Land, Infrastructure and Transport. The purpose of this study is optimizing management and storing of the texture data, one kinds of 3D-spatial data. First, extract 3D-spatial data through the aerial triangulation and 3D-writing using raw image taken with the Multi-directional aerial camera and the vertical aerial camera. And develop the method to create single texture data and related technique by align and place corresponding 3D-spatial data to optimal storage space. Through experiment, the results show effect of 8 times of storage capacity reduction compared to existing single-file storage method, additionally, new method can improve file management efficiency in comparison with multiple file storage method. The results of this study can be cornerstone of three-dimensional space information management when dealing with bulk data, and utilizations will be enhanced through the further studies and algorithm improvement.

Load Balancing for Distributed Processing of Real-time Spatial Big Data Stream (실시간 공간 빅데이터 스트림 분산 처리를 위한 부하 균형화 방법)

  • Yoon, Susik;Lee, Jae-Gil
    • Journal of KIISE
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    • v.44 no.11
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    • pp.1209-1218
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    • 2017
  • A variety of sensors is widely used these days, and it has become much easier to acquire spatial big data streams from various sources. Since spatial data streams have inherently skewed and dynamically changing distributions, the system must effectively distribute the load among workers. Previous studies to solve this load imbalance problem are not directly applicable to processing spatial data. In this research, we propose Adaptive Spatial Key Grouping (ASKG). The main idea of ASKG is, by utilizing the previous distribution of the data streams, to adaptively suggest a new grouping scheme that evenly distributes the future load among workers. We evaluate the validity of the proposed algorithm in various environments, by conducting an experiment with real datasets while varying the number of workers, input rate, and processing overhead. Compared to two other alternative algorithms, ASKG improves the system performance in terms of load imbalance, throughput, and latency.

A Study on the Accuracy Verification Criteria in Underground Facilities Surveying Using GPR (지하시설물 측량에 있어서 GPR 탐사방법의 정확도 검증 기준에 관한 연구)

  • OH, Yi-Kyun
    • Journal of Cadastre & Land InformatiX
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    • v.51 no.2
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    • pp.35-49
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    • 2021
  • In order to manage the underground spatial information in systematic and effective way, production of an integration underground spatial information map is essential process. The government has been making efforts to expand manage the production of 3D underground spatial integrated map. In recent the GPR is actively used for exploring underground facilities in non-exploring area and sinkhole. For achieving the research objectives presenting the accuracy of verification standard in underground spatial information surveying using GPR, the related legislation standard, the experiment resutls and international criteria have been analyzed. From this research it is found that the accuracy standard has been made by the related academic society(USA) and association(UK) in foreign counties. It is recommended that indicate the verification standard with number and percent together considering the characteristics of GPR.