Social vulnerability of historic Districts: A composite measuring scale to statistically predict human-made hazards
Year: 2022
Type: article
Abstract: One of the significant challenges in heritage risk assessment is concentrating on investigating physical characteristics in assessing man-made hazards and vulnerabilities without addressing the social aspects that may affect the potential rates of man-made risks on heritage buildings and surrounding historic fabric. This article aims to investigate the predictive relationship between human-made hazards in historic districts and the socio-economic weaknesses that represent Social Vulnerability of Historic Districts (SVHD). The methodology comprises a literature review for extracting the most relevant items of SVHD. Subsequently, a content validation was performed. To enhance the quality and effectiveness of the study, a pilot study was implemented for seventy-three historic districts in historic Cairo, Egypt. Then, using IBM SPSS statistics 20, exploratory factor analysis was executed to develop fewer factors of SVHD from the extracted items and establish their validity and reliability. Finally, multiple linear regression was carried using the surveyed data of human-made hazards rates occurring in the study cases. As a result, the regression analysis developed three predictive models: (the humans model, the heritage buildings model, and the context model). These models have been succussed in predicting the potential rates of human-made hazards significantly. The resulting models highlighted the importance of investigating the social component to predict human-made hazards in historic districts using a quantitative assessment tool. This would help authorities in formulating suitable strategies for the effective performance of historic districts.
Source: Ain Shams Engineering Journal
Institutions: Zagazig University, Cairo University
Language: English
Subfield: Archeology
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $860
OpenAlex ID: W4306790729
