{"title":"菲律宾阿尔拜马荣火山危险区资源定位智能模型概念化","authors":"A. M. Abante, Benedicto B. Balilo","doi":"10.25147/IJCSR.2017.001.1.24","DOIUrl":null,"url":null,"abstract":"Purpose – This paper presents a cloud-based GIS that aims to store, retrieve, manipulate and analyze Disaster Risk Reduction and Management (DRRM)-database human resource data for students, professional volunteers, emergency responders, social and health workers. The location-intelligence is significant in maintaining public safety and peace and order during disaster and post-disaster phases. Locating trained personnel during emergency response stage is critical in DRRM given that responders can also be exposed to disaster risks together with the evacuees during crisis. Method – The researchers tried to put into the picture how spatial integration could enhance existing Local Government Unit (LGU) information systems. Enhancing existing information systems with human resource or household locations (x, y) is critical in analyzing and validating incoming real-time data or emergency incident reports. Reliable reports and location can be quickly collected, processed and manipulated to produce crisis maps from the DRRM databases stored at the cloud GIS at real-time. Crisis maps should be produced timely for complex emergencies and response operations.The sampling covered geographic locations intersecting the outer boundary of the Mayon 6kilometer danger zone stretched up to the 10-kilometer buffering at least 2,898 families","PeriodicalId":33870,"journal":{"name":"International Journal of Computing Sciences Research","volume":"68 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Resource Location-Intelligence Model Conceptualized for Mayon Volcano Danger Zones in Albay,Philippines\",\"authors\":\"A. M. Abante, Benedicto B. Balilo\",\"doi\":\"10.25147/IJCSR.2017.001.1.24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose – This paper presents a cloud-based GIS that aims to store, retrieve, manipulate and analyze Disaster Risk Reduction and Management (DRRM)-database human resource data for students, professional volunteers, emergency responders, social and health workers. The location-intelligence is significant in maintaining public safety and peace and order during disaster and post-disaster phases. Locating trained personnel during emergency response stage is critical in DRRM given that responders can also be exposed to disaster risks together with the evacuees during crisis. Method – The researchers tried to put into the picture how spatial integration could enhance existing Local Government Unit (LGU) information systems. Enhancing existing information systems with human resource or household locations (x, y) is critical in analyzing and validating incoming real-time data or emergency incident reports. Reliable reports and location can be quickly collected, processed and manipulated to produce crisis maps from the DRRM databases stored at the cloud GIS at real-time. Crisis maps should be produced timely for complex emergencies and response operations.The sampling covered geographic locations intersecting the outer boundary of the Mayon 6kilometer danger zone stretched up to the 10-kilometer buffering at least 2,898 families\",\"PeriodicalId\":33870,\"journal\":{\"name\":\"International Journal of Computing Sciences Research\",\"volume\":\"68 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computing Sciences Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25147/IJCSR.2017.001.1.24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computing Sciences Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25147/IJCSR.2017.001.1.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Resource Location-Intelligence Model Conceptualized for Mayon Volcano Danger Zones in Albay,Philippines
Purpose – This paper presents a cloud-based GIS that aims to store, retrieve, manipulate and analyze Disaster Risk Reduction and Management (DRRM)-database human resource data for students, professional volunteers, emergency responders, social and health workers. The location-intelligence is significant in maintaining public safety and peace and order during disaster and post-disaster phases. Locating trained personnel during emergency response stage is critical in DRRM given that responders can also be exposed to disaster risks together with the evacuees during crisis. Method – The researchers tried to put into the picture how spatial integration could enhance existing Local Government Unit (LGU) information systems. Enhancing existing information systems with human resource or household locations (x, y) is critical in analyzing and validating incoming real-time data or emergency incident reports. Reliable reports and location can be quickly collected, processed and manipulated to produce crisis maps from the DRRM databases stored at the cloud GIS at real-time. Crisis maps should be produced timely for complex emergencies and response operations.The sampling covered geographic locations intersecting the outer boundary of the Mayon 6kilometer danger zone stretched up to the 10-kilometer buffering at least 2,898 families