This research aims to assess vulnerable spaces around heritage buildings concerning their socio-spatial properties. Additionally, the research explores the predictive relationship between these properties and contextual anthropogenic hazards. The research's methodology relies on multi-methods applied to twenty-eight heritage buildings in historic Cairo, Egypt. Firstly, the research employed the Delphi technique and ICCROM-CCI-RCE method to assess the potential rates of contextual anthropogenic hazards in the study area. Afterwards, the literature review was conducted to explore a new paradigm for assessing vulnerable spaces using the space syntax-based methodology. Space syntax provides a better understanding of space, its structure, and how it affects human behaviour. Moreover, the research employed two main analytical methods of space syntax, axial graph, and visual graph analyses, which were achieved by “Depthmap 4” software to investigate the syntactic context of the study area. Furthermore, the exploratory factor analysis was employed to statistically analyse the syntactic output data to develop fewer factors of socio-spatial vulnerability. These factors served as inputs for multiple linear regression analysis as predictive models of the influence of socio-spatial vulnerability on the assessed contextual anthropogenic hazards. Finally, the resulting models highlighted the importance of investigating the socio-spatial properties around heritage buildings to predict human destructive behaviours based on quantitative analytical methods. Such results would help authorities formulate suitable and sustainable strategies for the adequate performance of heritage buildings. Also, the predictive models can potentially be used in other livable historic cities.

Historic buildings still perform their role today by being utilized either for their original purpose or a new purpose for which they are adapted. These buildings have specific requirements that inhabitants must follow. These requirements and relating uses and maintenance procedures result from adaptive reuse decisions, which may not be the most optimal scenario. The imperative is that historic buildings are used in a manner that, on the one hand, does not endanger their value related to heritage and tradition, and on the other hand, guarantees a degree of utility for their inhabitants, such as acceptable performance with regards to either air cooling or heating. The challenge is how to optimize the use of energy for either air cooling or heating, provided that adaptive reuse decisions are grounded in certain very specific and very rigid principles. The latter render is extremely difficult to meet the twin challenges of ensuring energy efficiency and thermal comfort for inhabitants while at the same time complying with the adaptive reuse principles. To address this challenge and gain an insight into ways of navigating it, a Post Occupancy Evaluation (POE) is conducted in Former Soldier’s Residence in the Cairo Citadel, Cairo, Egypt, which is now used as the National Organization for Urban Harmony’s (NOUH) administrative head office, this research can be considered as a single domain from which many other possible multi-domains can be investigated while studying the case of adaptive reuse. Other aspects such as indoor environmental quality, air quality, acoustics and lighting might act as multiple approaches appear to be widely used according to this review study, and in the future, the authors intend to test this research with the current single approach used in this research, which is the thermal comfort. POE includes both objective and subjective assessment, the POE limitation at this research to those assessment while a multi-perceptional and behavioral factors might be used as physical, contextual, personal, and others. The simulation and the survey methods were employed consecutively to assess the case study. By considering the research results, it was determined that the building consumes unnecessary energy by its current use of air conditioning system.

The key issue of this current study is related to shaping the attractiveness of heritage destinations, highlighting the significance of reuse and upgrading their historical buildings to achieve a high level of competitiveness and distinctiveness through a smart approach. Some of these cultural assets and events tend to be monotonous, and not so attractive for various categories of tourists, which negatively affects investment opportunities, tourism development, and social and economic resources. Furthermore, previous works have criticized the lack of evidence to support that the structure contains critical attributes and measurement items linked to the competitiveness of smart heritage destinations. As a result, this study aims to design and develop a composite index for evaluating these destinations and their buildings, which includes nine dimensions (attributes) and a set of key performance indicators (KPIs) of intelligent performance and competitiveness, reflecting the combination and noticing the distinct perspective between them. A mixed-methods approach was used between qualitative and quantitative methods to perform content validation on the proposed index. Furthermore, a pilot study was implemented for tourism heritage destinations to improve the quality and efficiency of the proposed index. Then, exploratory factor analysis (EFA) was used to analyze the data to develop the proposed index and measure its validity and reliability. Finally, the proposed composite index was finalized with 139 KPIs and applied to a case study (Salah El-Din Citadel). After that, we validated its utility in providing a quantitative evaluation of this heritage destination, identifying critical intervention priorities, and determining dimensions that need to be restructured. Additionally, it highlighted recommendations for future improvements to strengthen these heritage destinations to become smart heritage destinations capable of competition in the tourism sector.

The continuous cumulative worsening impact of climate change on heritage sites represents a new challenge for most of the nonrenewable resources of heritage sites and buildings in general; this is especially true with respect to coastal heritage sites, which are facing a more dangerous situation as the climate becomes more extreme in coastal areas and sea levels rise, putting heritage sites at risk. A strict adaptation plan, usually made for reducing the impact of climate change, may not be the solution, as different heritage site locations, materials, and hazard types need tailored plans. Therefore, in this research paper, a resilience approach was introduced to help adapt the most problematic sites to the impacts of climate change, i.e., coastal heritage sites. To fulfill the objective of achieving adaptation in a resilient way that can easily be developed in relation to different types of sites, mixed research methods were used. First, the literature was reviewed using the Connected Papers tool. Then, machine learning methods were used to process and analyze the input data of the resilience adaptation plan for an Egyptian coastal heritage site case study, i.e., Alexandria. Next, the data were arranged and analyzed, highlighting the main classifying algorithms responsible for identifying the resilience range, using the machine learning software packages Infra Nodus and WEKA, according to the differences in the climate change impact at the heritage sites. The final outcome of this research is a resilience approach that can be adapted to rescue plans for coastal heritage sites via machine learning.

The unstable climate causes many related risks, including heavy rainfall. In the past, Egypt experienced rainfall over time. Although Egypt is still classified as a low-precipitation country, it can experience extreme rainfall events, resulting in flash floods. Many fragile materials related to heritage building façades may be affected by the change in rainfall rates without any risk assessment plan. This research aims to confront the hazards of raindrop strikes, as the need for making a risk management plan has arisen in order to preserve heritage buildings from heavy rainfall. The research methodology uses the ABC risk assessment quantitative method in addition to experts’ multi-round assessments and tornado diagrams to analyze the magnitude of risks in order to create a risk assessment plan for a group of heritage buildings in Historic Cairo as a pilot study that can be generalized for similar cases. The final output is framed into a cause-and-effect model for rainfall risk problem solving, generated by rainfall risk causes and effects on the heritage building facades.