• Title/Summary/Keyword: multisource data

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Feature Extraction and Multisource Image Classification

  • Amarsaikhan, D.;Sato, M.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1084-1086
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    • 2003
  • The aim of this study is to assess the integrated use of different features extracted from spaceborne interferometric synthetic aperture radar (InSAR) data and optical data for land cover classification. Special attention is given to the discriminatory characteristics of the features derived from the multisource data sets. For the evaluation of the features , the statistical maximum likelihood decision rule and neural network classification are used and the results are compared. The performance of each method was evaluated by measuring the overall accuracy. In all cases, the performance of the first method was better than the performance of the latter one. Overall, the research indicated that multisource data sets containing different information about backscattering and reflecting properties of the selected classes of objects can significantly improve the classification of land cover types.

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Application of Bayesian Statistical Analysis to Multisource Data Integration

  • Hong, Sa-Hyun;Moon, Wooil-M.
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.394-399
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    • 2002
  • In this paper, Multisource data classification methods based on Bayesian formula are considered. For this decision fusion scheme, the individual data sources are handled separately by statistical classification algorithms and then Bayesian fusion method is applied to integrate from the available data sources. This method includes the combination of each expert decisions where the weights of the individual experts represent the reliability of the sources. The reliability measure used in the statistical approach is common to all pixels in previous work. In this experiment, the weight factors have been assigned to have different value for all pixels in order to improve the integrated classification accuracies. Although most implementations of Bayesian classification approaches assume fixed a priori probabilities, we have used adaptive a priori probabilities by iteratively calculating the local a priori probabilities so as to maximize the posteriori probabilities. The effectiveness of the proposed method is at first demonstrated on simulations with artificial and evaluated in terms of real-world data sets. As a result, we have shown that Bayesian statistical fusion scheme performs well on multispectral data classification.

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Generation of Time-Series Data for Multisource Satellite Imagery through Automated Satellite Image Collection (자동 위성영상 수집을 통한 다종 위성영상의 시계열 데이터 생성)

  • Yunji Nam;Sungwoo Jung;Taejung Kim;Sooahm Rhee
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1085-1095
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    • 2023
  • Time-series data generated from satellite data are crucial resources for change detection and monitoring across various fields. Existing research in time-series data generation primarily relies on single-image analysis to maintain data uniformity, with ongoing efforts to enhance spatial and temporal resolutions by utilizing diverse image sources. Despite the emphasized significance of time-series data, there is a notable absence of automated data collection and preprocessing for research purposes. In this paper, to address this limitation, we propose a system that automates the collection of satellite information in user-specified areas to generate time-series data. This research aims to collect data from various satellite sources in a specific region and convert them into time-series data, developing an automatic satellite image collection system for this purpose. By utilizing this system, users can collect and extract data for their specific regions of interest, making the data immediately usable. Experimental results have shown the feasibility of automatically acquiring freely available Landsat and Sentinel images from the web and incorporating manually inputted high-resolution satellite images. Comparisons between automatically collected and edited images based on high-resolution satellite data demonstrated minimal discrepancies, with no significant errors in the generated output.

Neutron activation analysis: Modelling studies to improve the neutron flux of Americium-Beryllium source

  • Didi, Abdessamad;Dadouch, Ahmed;Jai, Otman;Tajmouati, Jaouad;Bekkouri, Hassane El
    • Nuclear Engineering and Technology
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    • v.49 no.4
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    • pp.787-791
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    • 2017
  • Americium-beryllium (Am-Be; n, ${\gamma}$) is a neutron emitting source used in various research fields such as chemistry, physics, geology, archaeology, medicine, and environmental monitoring, as well as in the forensic sciences. It is a mobile source of neutron activity (20 Ci), yielding a small thermal neutron flux that is water moderated. The aim of this study is to develop a model to increase the neutron thermal flux of a source such as Am-Be. This study achieved multiple advantageous results: primarily, it will help us perform neutron activation analysis. Next, it will give us the opportunity to produce radio-elements with short half-lives. Am-Be single and multisource (5 sources) experiments were performed within an irradiation facility with a paraffin moderator. The resulting models mainly increase the thermal neutron flux compared to the traditional method with water moderator.

Three-Dimensional Positional Accuracy Analysis of UAV Imagery Using Ground Control Points Acquired from Multisource Geospatial Data (다종 공간정보로부터 취득한 지상기준점을 활용한 UAV 영상의 3차원 위치 정확도 비교 분석)

  • Park, Soyeon;Choi, Yoonjo;Bae, Junsu;Hong, Seunghwan;Sohn, Hong-Gyoo
    • Korean Journal of Remote Sensing
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    • v.36 no.5_3
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    • pp.1013-1025
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    • 2020
  • Unmanned Aerial Vehicle (UAV) platform is being widely used in disaster monitoring and smart city, having the advantage of being able to quickly acquire images in small areas at a low cost. Ground Control Points (GCPs) for positioning UAV images are essential to acquire cm-level accuracy when producing UAV-based orthoimages and Digital Surface Model (DSM). However, the on-site acquisition of GCPs takes considerable manpower and time. This research aims to provide an efficient and accurate way to replace the on-site GNSS surveying with three different sources of geospatial data. The three geospatial data used in this study is as follows; 1) 25 cm aerial orthoimages, and Digital Elevation Model (DEM) based on 1:1000 digital topographic map, 2) point cloud data acquired by Mobile Mapping System (MMS), and 3) hybrid point cloud data created by merging MMS data with UAV data. For each dataset a three-dimensional positional accuracy analysis of UAV-based orthoimage and DSM was performed by comparing differences in three-dimensional coordinates of independent check point obtained with those of the RTK-GNSS survey. The result shows the third case, in which MMS data and UAV data combined, to be the most accurate, showing an RMSE accuracy of 8.9 cm in horizontal and 24.5 cm in vertical, respectively. In addition, it has been shown that the distribution of geospatial GCPs has more sensitive on the vertical accuracy than on horizontal accuracy.

Effects of Academic Stress, Somatization Symptoms, and Social Support on Coping Responses in High School Students (고등학생의 학업 스트레스, 신체화 증상, 사회적 지지가 대처유형에 미치는 영향)

  • Lee, Eun Hee;Kim, Young Im;Geun, Hyo Geun;Lee, Young Shil
    • Journal of the Korean Society of School Health
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    • v.28 no.2
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    • pp.56-66
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    • 2015
  • The purpose of this study was to investigate factors associated with coping responses in Korean public high school students. Methods: This study employed a descriptive survey research design. The sample included 263 high school students who responded to a self-report questionnaire. Variables included socio-demographic characteristics, health-related characteristics, academic stress, somatization symptoms, social support, and coping responses. Data were analyzed using descriptive statistics, t-tests, ANOVA, Pearson's correlations, and multiple regressions. Results: Participants, regarding their school life, reported moderate levels of academic stress ($M{\pm}SD=2.3{\pm}0.52$) and somatization symptoms ($M{\pm}SD=2.3{\pm}0.71$), and a relatively high level of social support ($M{\pm}SD=4.2{\pm}0.67$). All the variables were associated with the use of multiple coping responses. Active-cognitive coping ($M{\pm}SD=2.9{\pm}0.68$) was most frequently used, followed by active-behavioral coping ($M{\pm}SD=2.5{\pm}0.56$). and avoidant coping ($M{\pm}SD=2.3{\pm}0.75$). Significant relationships were found among the measured variables: positive relation between academic stress and somatization symptoms, but, negative between academic stress and both somatization symptoms and social support. Students who had higher stress and more somatization symptoms were more likely to use avoidant coping than the others. In multiple regression analysis, while factors associated with each coping response differed, gender appeared to be a significant factor in all methods. Variables included in the final model explained 27% of the variance in avoidant coping (F=11.40, p<.001). Conclusion: Based on the study results, schools should provide tailored educational programs to help high school students reduce multisource stress and somatization symptoms at school and cope with them in more active and effective ways.

Mechanisms of thermally induced deflection of a long-span cable-stayed bridge

  • Zhou, Yi;Sun, Limin;Peng, Zhijian
    • Smart Structures and Systems
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    • v.15 no.3
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    • pp.505-522
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    • 2015
  • Variation of temperature is a primary environmental factor that affects the behavior of structures. Therefore, understanding the mechanisms of normal temperature-induced variations of structural behavior would help in distinguishing them from anomalies. In this study, we used the structural health monitoring data of the Shanghai Yangtze River Bridge, a steel girder cable-stayed bridge, to investigate the mechanisms of thermally induced vertical deflection ($D_T$) at mid-span of such bridges. The $D_T$ results from a multisource combination of thermal expansion effects of the cable temperature ($T_{Cab}$), girder temperature ($T_{Gir}$), girder differential temperature ($T_{Dif}$), and tower temperature ($T_{Tow}$). It could be approximated by multiple linear superpositions under operational conditions. The sensitivities of $D_T$ of the Shanghai Yangtze River Bridge to the above temperatures were in the following order: $T_{Cab}$ > $T_{Gir}$ > $T_{Tow}$ > $T_{Dif}$. However, the direction of the effect of $T_{Cab}$ was observed to be opposite to that of the other three temperatures, and the magnitudes of the effects of $T_{Cab}$ and $T_{Gir}$ were found to be almost one order greater than those of $T_{Dif}$ and $T_{Tow}$. The mechanisms of the thermally induced vertical deflection variation at mid-span of a cable-stayed bridge as well as the analytical methodology adopted in this study could be applicable for other long-span cable-stayed bridges.

Experimental investigation of blocking mechanism for grouting in water-filled karst conduits

  • Zehua Bu;Zhenhao Xu;Dongdong Pan;Haiyan Li;Jie Liu;Zhaofeng Li
    • Geomechanics and Engineering
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    • v.34 no.2
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    • pp.155-171
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    • 2023
  • Aiming at the grouting treatment of water inflow in karst conduits, a visualized experiment system for conduit-type grouting blocking was developed. Through the improved water supply system and grouting system, and the optimized multisource information monitoring system, the real-time observation of diffusion and deposition of slurry, and the data acquisition of pressure and velocity during the whole process of grouting were realized, which breaks through the problem that the monitoring element is easy to fail due to slurry adhesion in conventional test system. Based on the grouting experiments in static and flowing water, the diffusion and deposition behavior of the quick-setting slurry under different working conditions were analyzed. The temporal and spatial variation behavior of the pressure and velocity were studied, and the blocking mechanism of the grouting were further revealed. The results showed that: (1) Under the flowing water condition, the counter-flow diffusion distance of slurry was negatively correlated with the flow water velocity and the volume ratio of cement and sodium silicate (C-S ratio), and positively correlated with the grouting volume. The slurry deposition thickness was negatively correlated with the flowing water velocity, and positively correlated with the grouting volume and C-S ratio. (2) The pressure increased slowly before blocking of the flowing water and rapidly after blocking in karst conduits. (3) With the continuous progress of grouting, the flowing water velocity decreased slowly first, then significantly, and finally tended to be stable. According to the research results, some engineering recommendations were put forward for the grouting treatment of the conduit-type water inflow disaster, which has been successfully applied in the treatment project of the China Resources Cement (Pingnan) Limestone Mine. This study provided some guidance and reference for the parameter optimization of grouting for the treatment projects of water inflow in karst conduits.