دانلود مقاله ISI انگلیسی شماره 105184
ترجمه فارسی عنوان مقاله

یک چارچوب سیستم پشتیبانی از سیستم تخلیه تلفیقی با تجزیه و تحلیل ادراک اجتماعی و تخمین جمعیت پویا

عنوان انگلیسی
An integrated evacuation decision support system framework with social perception analysis and dynamic population estimation
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
105184 2017 33 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : International Journal of Disaster Risk Reduction, Volume 25, October 2017, Pages 190-201

ترجمه کلمات کلیدی
جمعیت پویا، رسانه های اجتماعی، یکپارچه سازی داده ها، تخلیه، آتش سوزی،
کلمات کلیدی انگلیسی
Dynamic population; Social media; Data integration; Evacuation; Wildfire;
پیش نمایش مقاله
پیش نمایش مقاله  یک چارچوب سیستم پشتیبانی از سیستم تخلیه تلفیقی با تجزیه و تحلیل ادراک اجتماعی و تخمین جمعیت پویا

چکیده انگلیسی

In designing evacuation plans, it is critical for the responsive agencies to consider the dynamic change of human population within impact areas and understand social perception from local residents. Although a large number of evacuation models has been reported in the literature, many used census survey data which represent only the nighttime population distribution. To fill this research gap, this paper introduces a novel data integration framework for developing an evacuation decision support system for wildfire, Integrated Wildfire Evacuation Decision Support System (IWEDSS). IWEDSS integrates multiple data sources including social media, census survey, geographic information systems (GIS) data layers, volunteer suggestions, and remote sensing data. The integration is based on multi-disciplinary theoretical and modeling approaches including Geographic Information Science, civil and transportation engineering, computer science, social media and communication. IWEDSS includes four core modules: dynamic population estimation, stage-based robust evacuation planning, social perception analysis, and web-based geomatical analytic platform. It offers tools for evacuation planers and resource managers to make better decisions that can reduce the evacuation time and potential number of injuries and deaths. This paper also presents a case study to demonstrate the suitability of incorporating social media data to estimate the dynamic change of human population.