{"title":"灾害风险模型的元模型","authors":"W. H. Nur, F. N. Azizah, Saiful Akbar","doi":"10.1109/ICODSE.2015.7436964","DOIUrl":null,"url":null,"abstract":"As the world faces an increasing number of both natural and social disasters, attempts to support disaster risk reduction are also increasing. Although there is a general rule to calculate the disaster risk on an area based on the components of hazard, vulnerability, and capacity, disaster risk studies result in a number of disaster risk models which present different characteristics in terms of the number of components involved, indicators, and the calculations. This poses a difficulty for disaster analysts to choose the most appropriate model to calculate the disaster risk of an area. Moreover, they often need to adapt the existing models or even to create new models in order to provide the most suitable way of calculating the disaster risks. Therefore, a mechanism that enables the use of different kinds of disaster risk model and the creation of new models is required. This paper presents a metamodel of disaster risk based on a study on a number of disaster risk models used in Indonesia: the BNPB (Badan Nasional Penanggulangan Bencana) disaster risk model, the volcanic disaster risk model using SMART (Simple Multi Attribute Rating Technique) method, and the tidal flooding disaster risk model using fuzzy method. The metamodel is presented in an entity-relationship model. It is basically a spatial data model since the components and indicators for the calculation of disaster risks are always associated to the space on earth. The metamodel is implemented on top of ArcGIS software. Using Phyton Add-in, the software is adapted by adding new functionalities to calculate the disaster risk of an area and to create new disaster risk models.","PeriodicalId":374006,"journal":{"name":"2015 International Conference on Data and Software Engineering (ICoDSE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A metamodel for disaster risk models\",\"authors\":\"W. H. Nur, F. N. Azizah, Saiful Akbar\",\"doi\":\"10.1109/ICODSE.2015.7436964\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the world faces an increasing number of both natural and social disasters, attempts to support disaster risk reduction are also increasing. Although there is a general rule to calculate the disaster risk on an area based on the components of hazard, vulnerability, and capacity, disaster risk studies result in a number of disaster risk models which present different characteristics in terms of the number of components involved, indicators, and the calculations. This poses a difficulty for disaster analysts to choose the most appropriate model to calculate the disaster risk of an area. Moreover, they often need to adapt the existing models or even to create new models in order to provide the most suitable way of calculating the disaster risks. Therefore, a mechanism that enables the use of different kinds of disaster risk model and the creation of new models is required. This paper presents a metamodel of disaster risk based on a study on a number of disaster risk models used in Indonesia: the BNPB (Badan Nasional Penanggulangan Bencana) disaster risk model, the volcanic disaster risk model using SMART (Simple Multi Attribute Rating Technique) method, and the tidal flooding disaster risk model using fuzzy method. The metamodel is presented in an entity-relationship model. It is basically a spatial data model since the components and indicators for the calculation of disaster risks are always associated to the space on earth. The metamodel is implemented on top of ArcGIS software. Using Phyton Add-in, the software is adapted by adding new functionalities to calculate the disaster risk of an area and to create new disaster risk models.\",\"PeriodicalId\":374006,\"journal\":{\"name\":\"2015 International Conference on Data and Software Engineering (ICoDSE)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Data and Software Engineering (ICoDSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICODSE.2015.7436964\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Data and Software Engineering (ICoDSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICODSE.2015.7436964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
随着世界面临越来越多的自然灾害和社会灾害,支持减少灾害风险的努力也在增加。虽然一般规则是根据危害、脆弱性和能力的组成部分来计算一个地区的灾害风险,但灾害风险研究产生了许多灾害风险模型,这些模型在涉及的组成部分的数量、指标和计算方面呈现出不同的特征。这给灾害分析人员选择最合适的模型来计算一个地区的灾害风险带来了困难。此外,他们经常需要调整现有的模型,甚至创建新的模型,以便提供最合适的计算灾害风险的方法。因此,需要一种能够使用不同类型的灾害风险模型和创建新模型的机制。本文在对印度尼西亚使用的几种灾害风险模型(BNPB (Badan Nasional Penanggulangan ben卡纳)灾害风险模型、采用SMART (Simple Multi Attribute Rating Technique)方法的火山灾害风险模型和采用模糊方法的潮汐洪水灾害风险模型)进行研究的基础上,提出了灾害风险的元模型。元模型以实体-关系模型的形式表示。它基本上是一个空间数据模型,因为计算灾害风险的成分和指标总是与地球上的空间相关联。该元模型是在ArcGIS软件上实现的。使用Phyton Add-in,该软件通过添加新的功能来计算一个地区的灾害风险并创建新的灾害风险模型。
As the world faces an increasing number of both natural and social disasters, attempts to support disaster risk reduction are also increasing. Although there is a general rule to calculate the disaster risk on an area based on the components of hazard, vulnerability, and capacity, disaster risk studies result in a number of disaster risk models which present different characteristics in terms of the number of components involved, indicators, and the calculations. This poses a difficulty for disaster analysts to choose the most appropriate model to calculate the disaster risk of an area. Moreover, they often need to adapt the existing models or even to create new models in order to provide the most suitable way of calculating the disaster risks. Therefore, a mechanism that enables the use of different kinds of disaster risk model and the creation of new models is required. This paper presents a metamodel of disaster risk based on a study on a number of disaster risk models used in Indonesia: the BNPB (Badan Nasional Penanggulangan Bencana) disaster risk model, the volcanic disaster risk model using SMART (Simple Multi Attribute Rating Technique) method, and the tidal flooding disaster risk model using fuzzy method. The metamodel is presented in an entity-relationship model. It is basically a spatial data model since the components and indicators for the calculation of disaster risks are always associated to the space on earth. The metamodel is implemented on top of ArcGIS software. Using Phyton Add-in, the software is adapted by adding new functionalities to calculate the disaster risk of an area and to create new disaster risk models.