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Dr. Hai Sun
Ocean University of China, collage of engineering

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0 Engineering Management
0 GIS
0 Virtual Reality
0 computer architecture

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Short Biography

Disaster-causing mechanism of major disasters in cities, and propose timely and economical disaster prevention strategies

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Journal article
Published: 17 July 2021 in Remote Sensing
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Timely acquisition of spatial flood distribution is an essential basis for flood-disaster monitoring and management. Remote-sensing data have been widely used in water-body surveys. However, due to the cloudy weather and complex geomorphic environment, the inability to receive remote-sensing images throughout the day has resulted in some data being missing and unable to provide dynamic and continuous flood inundation process data. To fully and effectively use remote-sensing data, we developed a new decision support system for integrated flood inundation management based on limited and intermittent remote-sensing data. Firstly, we established a new multi-scale water-extraction convolutional neural network named DEU-Net to extract water from remote-sensing images automatically. A specific datasets training method was created for typical region types to separate the water body from the confusing surface features more accurately. Secondly, we built a waterfront contour active tracking model to implicitly describe the flood movement interface. In this way, the flooding process was converted into the numerical solution of the partial differential equation of the boundary function. Space upwind difference format and the time Euler difference format were used to perform the numerical solution. Finally, we established seven indicators that considered regional characteristics and flood-inundation attributes to evaluate flood-disaster losses. The cloud model using the entropy weight method was introduced to account for uncertainties in various parameters. In the end, a decision support system realizing the flood losses risk visualization was developed by using the ArcGIS application programming interface (API). To verify the effectiveness of the model constructed in this paper, we conducted numerical experiments on the model’s performance through comparative experiments based on a laboratory scale and actual scale, respectively. The results were as follows: (1) The DEU-Net method had a better capability to accurately extract various water bodies, such as urban water bodies, open-air ponds, plateau lakes etc., than the other comparison methods. (2) The simulation results of the active tracking model had good temporal and spatial consistency with the image extraction results and actual statistical data compared with the synthetic observation data. (3) The application results showed that the system has high computational efficiency and noticeable visualization effects. The research results may provide a scientific basis for the emergency-response decision-making of flood disasters, especially in data-sparse regions.

ACS Style

Hai Sun; Xiaoyi Dai; Wenchi Shou; Jun Wang; Xuejing Ruan. An Efficient Decision Support System for Flood Inundation Management Using Intermittent Remote-Sensing Data. Remote Sensing 2021, 13, 2818 .

AMA Style

Hai Sun, Xiaoyi Dai, Wenchi Shou, Jun Wang, Xuejing Ruan. An Efficient Decision Support System for Flood Inundation Management Using Intermittent Remote-Sensing Data. Remote Sensing. 2021; 13 (14):2818.

Chicago/Turabian Style

Hai Sun; Xiaoyi Dai; Wenchi Shou; Jun Wang; Xuejing Ruan. 2021. "An Efficient Decision Support System for Flood Inundation Management Using Intermittent Remote-Sensing Data." Remote Sensing 13, no. 14: 2818.

Journal article
Published: 12 March 2021 in International Journal of Environmental Research and Public Health
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The accurate prediction of storm surge disasters’ direct economic losses plays a positive role in providing critical support for disaster prevention decision-making and management. Previous researches on storm surge disaster loss assessment did not pay much attention to the overfitting phenomenon caused by the data scarcity and the excessive model complexity. To solve these problems, this paper puts forward a new evaluation system for forecasting the regional direct economic loss of storm surge disasters, consisting of three parts. First of all, a comprehensive assessment index system was established by considering the storm surge disasters’ formation mechanism and the corresponding risk management theory. Secondly, a novel data augmentation technique, k-nearest neighbor-Gaussian noise (KNN-GN), was presented to overcome data scarcity. Thirdly, an ensemble learning algorithm XGBoost as a regression model was utilized to optimize the results and produce the final forecasting results. To verify the best-combined model, KNN-GN-based XGBoost, we conducted cross-contrast experiments with several data augmentation techniques and some widely-used ensemble learning models. Meanwhile, the traditional prediction models are used as baselines to the optimized forecasting system. The experimental results show that the KNN-GN-based XGBoost model provides more precise predictions than the traditional models, with a 64.1% average improvement in the mean absolute percentage error (MAPE) measurement. It could be noted that the proposed evaluation system can be extended and applied to the geography-related field as well.

ACS Style

Hai Sun; Jin Wang; Wentao Ye. A Data Augmentation-Based Evaluation System for Regional Direct Economic Losses of Storm Surge Disasters. International Journal of Environmental Research and Public Health 2021, 18, 2918 .

AMA Style

Hai Sun, Jin Wang, Wentao Ye. A Data Augmentation-Based Evaluation System for Regional Direct Economic Losses of Storm Surge Disasters. International Journal of Environmental Research and Public Health. 2021; 18 (6):2918.

Chicago/Turabian Style

Hai Sun; Jin Wang; Wentao Ye. 2021. "A Data Augmentation-Based Evaluation System for Regional Direct Economic Losses of Storm Surge Disasters." International Journal of Environmental Research and Public Health 18, no. 6: 2918.

Journal article
Published: 14 February 2021 in Sensors
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Predicting evacuation patterns is useful in emergency management situations such as an earthquake. To find out how pre-trained individuals interact with one another to achieve their own goal to reach the exit as fast as possible firstly, we investigated urban people’s evacuation behavior under earthquake disaster coditions, established crowd response rules in emergencies, and described the drill strategy and exit familiarity quantitatively through a cellular automata model. By setting different exit familiarity ratios, simulation experiments under different strategies were conducted to predict people’s reactions before an emergency. The corresponding simulation results indicated that the evacuees’ training level could affect a multi-exit zone’s evacuation pattern and clearance time. Their exit choice preferences may disrupt the exit options’ balance, leading to congestion in some of the exits. Secondly, due to people’s rejection of long distances, congestion, and unfamiliar exits, some people would hesitant about the evacuation direction during the evacuation process. This hesitation would also significantly reduce the overall evacuation efficiency. Finally, taking a community in Zhuhai City, China, as an example, put forward the best urban evacuation drill strategy. The quantitative relation between exit familiar level and evacuation efficiency was obtained. The final results showed that the optimized evacuation plan could improve evacuation’s overall efficiency through the self-organization effect. These studies may have some impact on predicting crowd behavior during evacuation and designing the evacuation plan.

ACS Style

Hai Sun; LanLing Hu; Wenchi Shou; Jun Wang. Self-Organized Crowd Dynamics: Research on Earthquake Emergency Response Patterns of Drill-Trained Individuals Based on GIS and Multi-Agent Systems Methodology. Sensors 2021, 21, 1353 .

AMA Style

Hai Sun, LanLing Hu, Wenchi Shou, Jun Wang. Self-Organized Crowd Dynamics: Research on Earthquake Emergency Response Patterns of Drill-Trained Individuals Based on GIS and Multi-Agent Systems Methodology. Sensors. 2021; 21 (4):1353.

Chicago/Turabian Style

Hai Sun; LanLing Hu; Wenchi Shou; Jun Wang. 2021. "Self-Organized Crowd Dynamics: Research on Earthquake Emergency Response Patterns of Drill-Trained Individuals Based on GIS and Multi-Agent Systems Methodology." Sensors 21, no. 4: 1353.

Journal article
Published: 22 July 2020 in Water
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The evaluation of storm surge flood risk is vital to disaster management and planning at national, regional and local levels, particularly in coastal areas that are affected more severely by storm surges. The purpose of this paper is to propose a new method that includes two modules for the simulation modeling and risk assessment of coastal flooding. One is a hydrodynamic module for simulating the process of the flood inundation coastal inundation arising from storm surge, which is based on a cellular automata (CA) model. The other is a risk assessment module for quantitatively estimating the economic loss by using the inundation data and land use data. The coastal areas of Pearl River estuary in China were taken as a case study. Simulation results are compared to experimental results from MIKE 21 and depth data from a social-media-based dataset, which demonstrates the effectiveness of the CA model. By analyzing flood risk, the flood area and the direct economic losses predicted are close to the actual case incurred, further demonstrating the computational reliability of the proposed method. Additionally, an automatic risk assessment platform is designed by integrating the two modules in a Geographic Information System (GIS) framework, facilitating a more efficient and faster simulation of coastal flooding. The platform can provide the governments as well as citizens of coastal areas with user-friendly, real-time graphics for coastal flood disaster preparation, warning, response and recovery.

ACS Style

Yazhi Zheng; Hai Sun. An Integrated Approach for the Simulation Modeling and Risk Assessment of Coastal Flooding. Water 2020, 12, 2076 .

AMA Style

Yazhi Zheng, Hai Sun. An Integrated Approach for the Simulation Modeling and Risk Assessment of Coastal Flooding. Water. 2020; 12 (8):2076.

Chicago/Turabian Style

Yazhi Zheng; Hai Sun. 2020. "An Integrated Approach for the Simulation Modeling and Risk Assessment of Coastal Flooding." Water 12, no. 8: 2076.

Conference paper
Published: 07 September 2018 in IOP Conference Series: Earth and Environmental Science
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There are many factors that influence the quality of marine water. In order to make the evaluation process more efficient and accurate, based on the normal distribution principle and Bias formula, this article establishes the seawater quality evaluation model by Bayesian method. Taking the evaluation of water quality of a sea area in Qingdao as an example, the measured data of eight water quality monitoring points are selected. The results of the evaluation are compared with the grey relational analysis. It shows that the results of the two methods are the same, which are the I type of water quality. So the Bayesian method based on normal distribution is applicable to the evaluation of marine water quality and the Bayesian method has the characteristic of more integrated, suitable for both large and small samples, simple calculation and easily to be used widely.

ACS Style

Wenchao Zhang; Huiying Gao; Hai Sun. Application and Analysis of Bayesian Method and Grey Relational Analysis in Marine Water Quality Evaluation. IOP Conference Series: Earth and Environmental Science 2018, 182, 012007 .

AMA Style

Wenchao Zhang, Huiying Gao, Hai Sun. Application and Analysis of Bayesian Method and Grey Relational Analysis in Marine Water Quality Evaluation. IOP Conference Series: Earth and Environmental Science. 2018; 182 (1):012007.

Chicago/Turabian Style

Wenchao Zhang; Huiying Gao; Hai Sun. 2018. "Application and Analysis of Bayesian Method and Grey Relational Analysis in Marine Water Quality Evaluation." IOP Conference Series: Earth and Environmental Science 182, no. 1: 012007.

Conference paper
Published: 29 November 2017 in IOP Conference Series: Materials Science and Engineering
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Previous experimental researches indicate that reinforced concrete beam-column joints play an important role in the mechanical properties of moment resisting frame structures, so as to require proper design. The aims of this paper are to predict the joint carrying capacity and cracks development theoretically. Thus, a rational model needs to be developed. Based on the former considerations, the softened strut-and-tie model is selected to be introduced and analyzed. Four adjustments including modifications of the depth of the diagonal strut, the inclination angle of diagonal compression strut, the smeared stress of mild steel bars embedded in concrete, as well as the softening coefficient are made. After that, the carrying capacity of beam-column joint and cracks development are predicted using the improved softened strut-and-tie model. Based on the test results, it is not difficult to find that the improved softened strut-and-tie model can be used to predict the joint carrying capacity and cracks development with sufficient accuracy.

ACS Style

Guoxi Fan; Debin Wang; Yuhong Diao; Huaishuai Shang; Xiaocheng Tang; Hai Sun. Improvement and Application of the Softened Strut-and-Tie Model. IOP Conference Series: Materials Science and Engineering 2017, 269, 12016 .

AMA Style

Guoxi Fan, Debin Wang, Yuhong Diao, Huaishuai Shang, Xiaocheng Tang, Hai Sun. Improvement and Application of the Softened Strut-and-Tie Model. IOP Conference Series: Materials Science and Engineering. 2017; 269 ():12016.

Chicago/Turabian Style

Guoxi Fan; Debin Wang; Yuhong Diao; Huaishuai Shang; Xiaocheng Tang; Hai Sun. 2017. "Improvement and Application of the Softened Strut-and-Tie Model." IOP Conference Series: Materials Science and Engineering 269, no. : 12016.

Conference paper
Published: 01 May 2017 in Journal of Physics: Conference Series
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The number of well-preserved ancient buildings located in Shanxi Province, enjoying the absolute maximum proportion of ancient architectures in China, is about 18418, among which, 9053 buildings have the structural style of wood frame. The value of the application of BIM (Building Information Modeling) and GIS (Geographic Information System) is gradually probed and testified in the corresponding fields of ancient architecture's spatial distribution information management, routine maintenance and special conservation & restoration, the evaluation and simulation of related disasters, such as earthquake. The research objects are ancient architectures in JIN-FEN area, which were first investigated by Sicheng LIANG and recorded in his work of "Chinese ancient architectures survey report". The research objects, i.e. the ancient architectures in Jin-Fen area include those in Sicheng LIANG's investigation, and further adjustments were made through authors' on-site investigation and literature searching & collection. During this research process, the spatial distributing Geodatabase of research objects is established utilizing GIS. The BIM components library for ancient buildings is formed combining on-site investigation data and precedent classic works, such as "Yingzao Fashi", a treatise on architectural methods in Song Dynasty, "Yongle Encyclopedia" and "Gongcheng Zuofa Zeli", case collections of engineering practice, by the Ministry of Construction of Qing Dynasty. A building of Guangsheng temple in Hongtong county is selected as an example to elaborate the BIM model construction process based on the BIM components library for ancient buildings. Based on the foregoing work results of spatial distribution data, attribute data of features, 3D graphic information and parametric building information model, the information management system for ancient architectures in Jin-Fen Area, utilizing GIS&BIM technology, could be constructed to support the further research of seismic disaster analysis and seismic performance simulation.

ACS Style

Jing Jia; Qiuhong Zheng; Huiying Gao; Hai Sun. Research of Ancient Architectures in Jin-Fen Area Based on GIS&BIM Technology. Journal of Physics: Conference Series 2017, 842, 012035 .

AMA Style

Jing Jia, Qiuhong Zheng, Huiying Gao, Hai Sun. Research of Ancient Architectures in Jin-Fen Area Based on GIS&BIM Technology. Journal of Physics: Conference Series. 2017; 842 (1):012035.

Chicago/Turabian Style

Jing Jia; Qiuhong Zheng; Huiying Gao; Hai Sun. 2017. "Research of Ancient Architectures in Jin-Fen Area Based on GIS&BIM Technology." Journal of Physics: Conference Series 842, no. 1: 012035.

Conference paper
Published: 01 September 2011 in 2011 International Conference on Electrical and Control Engineering
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The city is the highly populated areas and also the concentration of wealth.In the event of a earthquake,the damage and loss the city suffered are great. In order to grasp the spatial distribution of the earthquake,the extent of the damages,the casualties,the secondary disasters,the spot disaster information in the earthquake areas,and the trend of those disasters,a combined system of the earthquake data collection devices and the automatically triggered rapid assessment information system of the earthquake is particularly essential. Finally,the article will give out the actual operation of the earthquake early warning and command information system's interface in Fujian province.

ACS Style

Hai Sun; Ning Mei; Qimin Feng. Automatically triggered and rapid assessment information system of the earthquake disasters based on WebGIS. 2011 International Conference on Electrical and Control Engineering 2011, 4390 -4393.

AMA Style

Hai Sun, Ning Mei, Qimin Feng. Automatically triggered and rapid assessment information system of the earthquake disasters based on WebGIS. 2011 International Conference on Electrical and Control Engineering. 2011; ():4390-4393.

Chicago/Turabian Style

Hai Sun; Ning Mei; Qimin Feng. 2011. "Automatically triggered and rapid assessment information system of the earthquake disasters based on WebGIS." 2011 International Conference on Electrical and Control Engineering , no. : 4390-4393.