Hassan Houshyar
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Hassan Houshyar has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Abdulsalam Esmailzadeh
Department of Social Planning, Faculty of Social Science, Allameh Tabataba’i University, Tehran 1485643449, Iran
1 shared publication - Amir Reza Bakhshi Lomer
Department of Geography, Birkbeck, University of London, London WC1E 7HX, UK
1 shared publication - Elias Ghabouli
Department of Urban Planning & Design, Faculty of Arts and Architecture, Tarbiat Modares University, Tehran 14115, Iran
1 shared publication - Elżbieta Macioszek
Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland
1 shared publication - Hamid Rezaei
Department of Civil and Environmental Engineering, Florida International University, Miami, FL 33199, USA
1 shared publication - Parisa Derakhshesh
Islamic Azad University
1 shared publication
Latest Publications
- Open Access
- 29 May 2023
- Published by MDPI AG in Sustainability
- Vol. 15 (11) , 8777
A Spatial Decision Support System for Modeling Urban Resilience to Natural Hazards
A major component of urban management is studying and evaluating urban resilience in order to minimize the effects of natural hazards. This is because of the increasing number of natural hazards occurring worldwide. A spatial decision support system is presented for modeling urban resilience and selecting resilient zones in response to natural hazards. This system is implemented based on 22 criteria, grouped into three categories: demographics, infrastructure, and environmental. The criteria are then standardized using minimum and maximum methods, and their importance is determined by the analytical hierarchy process (AHP). The resilience maps in various scenarios are prepared using the ordered weighted average (OWA) method. Flow accumulation (distance from fault), vulnerable population density (vulnerable population density), and distance from road network (material type) were regarded as the most important criteria for flood resilience (earthquake resilience) from environmental, demographic, and infrastructure criteria, respectively. There are different areas that are considered to have very low resilience depending on the risk attitude. According a pessimistic scenario, 1% of Tehran’s area has very low resilience, while according to an optimistic scenario, 38% has very low resilience. This system can be used by urban planners and policymakers for the purpose of improving resilience to natural hazards in low-resilience areas.
- 29 May 2023
- Published by MDPI AG in Sustainability
- Vol. 15 (11) , 8777
Open AccessA Spatial Decision Support System for Modeling Urban Resilience to Natural Hazards
A major component of urban management is studying and evaluating urban resilience in order to minimize the effects of natural hazards. This is because of the increasing number of natural hazards occurring worldwide. A spatial decision support system is presented for modeling urban resilience and selecting resilient zones in response to natural hazards. This system is implemented based on 22 criteria, grouped into three categories: demographics, infrastructure, and environmental. The criteria are then standardized using minimum and maximum methods, and their importance is determined by the analytical hierarchy process (AHP). The resilience maps in various scenarios are prepared using the ordered weighted average (OWA) method. Flow accumulation (distance from fault), vulnerable population density (vulnerable population density), and distance from road network (material type) were regarded as the most important criteria for flood resilience (earthquake resilience) from environmental, demographic, and infrastructure criteria, respectively. There are different areas that are considered to have very low resilience depending on the risk attitude. According a pessimistic scenario, 1% of Tehran’s area has very low resilience, while according to an optimistic scenario, 38% has very low resilience. This system can be used by urban planners and policymakers for the purpose of improving resilience to natural hazards in low-resilience areas.