Gautam S. Thakur, Kelly M. Sims, Chantelle Rittmaier, Joseph Bentley, Debraj De, Junchuan Fan, Tao Liu, R. Palumbo, Jesse McGaha, P. Nugent, Bryan Eaton, Jordan Burdette, Tyler Sheldon, Kevin A. Sparks
{"title":"加速评估关键基础设施,以协助自然和人为灾害期间的恢复工作","authors":"Gautam S. Thakur, Kelly M. Sims, Chantelle Rittmaier, Joseph Bentley, Debraj De, Junchuan Fan, Tao Liu, R. Palumbo, Jesse McGaha, P. Nugent, Bryan Eaton, Jordan Burdette, Tyler Sheldon, Kevin A. Sparks","doi":"10.1145/3474717.3483947","DOIUrl":null,"url":null,"abstract":"Relief and recovery from disasters (both natural and human-made) require a coordinated approach across several federal and state government agencies. In order to achieve optimal resource allocation and deployment of first responders, accurate and timely assessment of the impact and extent of destruction are the cornerstones to any recovery effort. Ideally, this knowledge should be gathered and shared within the first 0-24 hours (termed as \"Acute Phase\" by the U.S. CDC guideline) for informed decision-making. But achieving this poses significant challenges for the data collection and data harmonization processes, particularly when voluminous data are being generated from diverse and distributed sources during the disaster responses. To this end, this work developed a scalable and efficient workflow to dynamically collect and harmonize crowd-sourced geographic multi-modal data, and then assess critical infrastructure (CI) damaged during disaster events. We demonstrate the application of our framework with two real-world experiences in addressing post-disaster recovery efforts - for the Bahamas (Natural - due to Hurricane Dorian, 2019) and Beirut (Human-made - due to explosion caused by the ammonium nitrate stored in a warehouse, 2020). We have illustrated that a coordinated effort is needed for planning as well as for execution to achieve informed decision making.","PeriodicalId":340759,"journal":{"name":"Proceedings of the 29th International Conference on Advances in Geographic Information Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Accelerated Assessment of Critical Infrastructure in Aiding Recovery Efforts During Natural and Human-made Disaster\",\"authors\":\"Gautam S. Thakur, Kelly M. Sims, Chantelle Rittmaier, Joseph Bentley, Debraj De, Junchuan Fan, Tao Liu, R. Palumbo, Jesse McGaha, P. Nugent, Bryan Eaton, Jordan Burdette, Tyler Sheldon, Kevin A. Sparks\",\"doi\":\"10.1145/3474717.3483947\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Relief and recovery from disasters (both natural and human-made) require a coordinated approach across several federal and state government agencies. In order to achieve optimal resource allocation and deployment of first responders, accurate and timely assessment of the impact and extent of destruction are the cornerstones to any recovery effort. Ideally, this knowledge should be gathered and shared within the first 0-24 hours (termed as \\\"Acute Phase\\\" by the U.S. CDC guideline) for informed decision-making. But achieving this poses significant challenges for the data collection and data harmonization processes, particularly when voluminous data are being generated from diverse and distributed sources during the disaster responses. To this end, this work developed a scalable and efficient workflow to dynamically collect and harmonize crowd-sourced geographic multi-modal data, and then assess critical infrastructure (CI) damaged during disaster events. We demonstrate the application of our framework with two real-world experiences in addressing post-disaster recovery efforts - for the Bahamas (Natural - due to Hurricane Dorian, 2019) and Beirut (Human-made - due to explosion caused by the ammonium nitrate stored in a warehouse, 2020). We have illustrated that a coordinated effort is needed for planning as well as for execution to achieve informed decision making.\",\"PeriodicalId\":340759,\"journal\":{\"name\":\"Proceedings of the 29th International Conference on Advances in Geographic Information Systems\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 29th International Conference on Advances in Geographic Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3474717.3483947\",\"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 29th International Conference on Advances in Geographic Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3474717.3483947","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Accelerated Assessment of Critical Infrastructure in Aiding Recovery Efforts During Natural and Human-made Disaster
Relief and recovery from disasters (both natural and human-made) require a coordinated approach across several federal and state government agencies. In order to achieve optimal resource allocation and deployment of first responders, accurate and timely assessment of the impact and extent of destruction are the cornerstones to any recovery effort. Ideally, this knowledge should be gathered and shared within the first 0-24 hours (termed as "Acute Phase" by the U.S. CDC guideline) for informed decision-making. But achieving this poses significant challenges for the data collection and data harmonization processes, particularly when voluminous data are being generated from diverse and distributed sources during the disaster responses. To this end, this work developed a scalable and efficient workflow to dynamically collect and harmonize crowd-sourced geographic multi-modal data, and then assess critical infrastructure (CI) damaged during disaster events. We demonstrate the application of our framework with two real-world experiences in addressing post-disaster recovery efforts - for the Bahamas (Natural - due to Hurricane Dorian, 2019) and Beirut (Human-made - due to explosion caused by the ammonium nitrate stored in a warehouse, 2020). We have illustrated that a coordinated effort is needed for planning as well as for execution to achieve informed decision making.