Projects per year
Abstract
This study presents a building classification scheme for residential houses in Malawi by focusing upon informal construction, which accounts for more than 90% of housing in the country, which has the highest urbanisation rate in the world. The proposed classification is compatible with the Prompt Assessment of Global Earthquakes for Response (PAGER) method and can be used for seismic vulnerability assessments of building stock in Malawi. To obtain realistic proportions of the building classes that are prevalent in Malawi, a building survey was conducted in Central and Southern Malawi between 10th and 20th July 2017. The results from the survey are used to modify the PAGER-based proportions of main housing typologies by reflecting actual housing construction in the surveyed areas. The results clearly highlight the importance of using realistic building stock data for seismic risk assessment in Malawi; relying on global building stock information can result in significant bias of earthquake impact assessment.
Original language | English |
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Number of pages | 31 |
Journal | Journal of Housing and the Built Environment |
Early online date | 2 Aug 2019 |
DOIs | |
Publication status | E-pub ahead of print - 2 Aug 2019 |
Research Groups and Themes
- PREPARE
Keywords
- field survey
- building classification
- earthquake
- seismic vulnerability
- risk assessment
- sustainable development
Fingerprint
Dive into the research topics of 'A Building Classification Scheme of Housing Stock in Malawi for Earthquake Risk Assessment'. Together they form a unique fingerprint.Projects
- 1 Finished
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PREPARE: Enhancing PREParedness for East African Countries through Seismic Resilience Engineering
Biggs, J. J. (Principal Investigator) & Macdonald, J. H. G. (Principal Investigator)
1/05/17 → 31/03/22
Project: Research, Parent
Datasets
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Dataset_Kloukinas et al._JHBE_2019
Novelli, V. (Creator), Kafodya, I. (Creator), Ngoma, I. (Creator), Macdonald, J. (Creator), Goda, K. (Creator) & Macdonald, J. (Data Manager), University of Bristol, 29 May 2019
DOI: 10.5523/bris.14pm5de0nx8nw29az8rawx84ha, http://data.bris.ac.uk/data/dataset/14pm5de0nx8nw29az8rawx84ha
Dataset