{"title":"优先考虑道路网络连接信息以应对灾害","authors":"Yingjie Hu, K. Janowicz","doi":"10.1145/2835596.2835613","DOIUrl":null,"url":null,"abstract":"Information plays an important role in disaster response. In the past, there has been a lack of up-to-date information following major disasters due to the limited means of communication. This situation has changed substantially in recent years. With the ubiquity of mobile devices, people experiencing emergency events may still be able to share information via social media and peer-to-peer networks. Meanwhile, volunteers throughout the world are remotely convened by humanitarian organizations to digitize satellite images for the impacted area. These processes produce rich information which presents a new challenge for decision makers who have to interpret large amount of heterogeneous information within limited time. This short paper discusses this problem and outlines a potential solution to prioritizing information in emergency situations. Specifically, we focus on information about road network connectivity, i.e., whether a road segment is still accessible after a disaster. We propose to integrate information value theory with graph theory, and prioritize information items based on their contributions to the successes of potential rescue tasks and to the more accurate estimation of road network connectivity. Finally, we point out directions for future work.","PeriodicalId":323570,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Prioritizing road network connectivity information for disaster response\",\"authors\":\"Yingjie Hu, K. Janowicz\",\"doi\":\"10.1145/2835596.2835613\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Information plays an important role in disaster response. In the past, there has been a lack of up-to-date information following major disasters due to the limited means of communication. This situation has changed substantially in recent years. With the ubiquity of mobile devices, people experiencing emergency events may still be able to share information via social media and peer-to-peer networks. Meanwhile, volunteers throughout the world are remotely convened by humanitarian organizations to digitize satellite images for the impacted area. These processes produce rich information which presents a new challenge for decision makers who have to interpret large amount of heterogeneous information within limited time. This short paper discusses this problem and outlines a potential solution to prioritizing information in emergency situations. Specifically, we focus on information about road network connectivity, i.e., whether a road segment is still accessible after a disaster. We propose to integrate information value theory with graph theory, and prioritize information items based on their contributions to the successes of potential rescue tasks and to the more accurate estimation of road network connectivity. Finally, we point out directions for future work.\",\"PeriodicalId\":323570,\"journal\":{\"name\":\"Proceedings of the 1st ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2835596.2835613\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2835596.2835613","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prioritizing road network connectivity information for disaster response
Information plays an important role in disaster response. In the past, there has been a lack of up-to-date information following major disasters due to the limited means of communication. This situation has changed substantially in recent years. With the ubiquity of mobile devices, people experiencing emergency events may still be able to share information via social media and peer-to-peer networks. Meanwhile, volunteers throughout the world are remotely convened by humanitarian organizations to digitize satellite images for the impacted area. These processes produce rich information which presents a new challenge for decision makers who have to interpret large amount of heterogeneous information within limited time. This short paper discusses this problem and outlines a potential solution to prioritizing information in emergency situations. Specifically, we focus on information about road network connectivity, i.e., whether a road segment is still accessible after a disaster. We propose to integrate information value theory with graph theory, and prioritize information items based on their contributions to the successes of potential rescue tasks and to the more accurate estimation of road network connectivity. Finally, we point out directions for future work.