L. Narieswari, S. Sitorus, H. Hardjomidjojo, E. I. K. Putri
{"title":"Spatial Dynamic Model of Index-Based Disaster Resilience","authors":"L. Narieswari, S. Sitorus, H. Hardjomidjojo, E. I. K. Putri","doi":"10.5614/jpwk.2022.33.3.7","DOIUrl":null,"url":null,"abstract":"Measurement and development of resilience are essential in disaster risk reduction programs. Furthermore, efforts are needed to measure resilience baselines to track changes over time and compare areas for monitoring and evaluating resilience development. Therefore, this study identified dimensions and indicators for measuring resilience using a statistical approach and developed an index-based spatial resilience model in a web-GIS environment. This paper presents the spatial distribution of urban resilience to disasters in Semarang City at the sub-district level. Factor analysis showed that 21 selected indicators could represent five dimensions of resilience: social, economic, infrastructure, environmental, and institutional. Furthermore, the model results showed that 88% of the sub-districts were in the moderate resilience class. The spatial distribution of each dimension showed considerable heterogeneity in its coastal and plain areas (city center) as well as better resilience in the social and infrastructure dimensions than in its hilly areas. The hilly areas in the west have relatively better resilience than those in the east. These results can be used as a reference in managing resilience to disasters. The model presents a spatial distribution of resilience based on an index that quickly provides an overview of the conditions and determines priorities for increasing resilience in supporting disaster risk reduction programs.","PeriodicalId":41870,"journal":{"name":"Journal of Regional and City Planning","volume":" ","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Regional and City Planning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5614/jpwk.2022.33.3.7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REGIONAL & URBAN PLANNING","Score":null,"Total":0}
引用次数: 0
Abstract
Measurement and development of resilience are essential in disaster risk reduction programs. Furthermore, efforts are needed to measure resilience baselines to track changes over time and compare areas for monitoring and evaluating resilience development. Therefore, this study identified dimensions and indicators for measuring resilience using a statistical approach and developed an index-based spatial resilience model in a web-GIS environment. This paper presents the spatial distribution of urban resilience to disasters in Semarang City at the sub-district level. Factor analysis showed that 21 selected indicators could represent five dimensions of resilience: social, economic, infrastructure, environmental, and institutional. Furthermore, the model results showed that 88% of the sub-districts were in the moderate resilience class. The spatial distribution of each dimension showed considerable heterogeneity in its coastal and plain areas (city center) as well as better resilience in the social and infrastructure dimensions than in its hilly areas. The hilly areas in the west have relatively better resilience than those in the east. These results can be used as a reference in managing resilience to disasters. The model presents a spatial distribution of resilience based on an index that quickly provides an overview of the conditions and determines priorities for increasing resilience in supporting disaster risk reduction programs.