Using space syntax for estimation of potential disaster indirect economic losses

The paper is aimed at estimation of indirect economic losses resulting from natural disasters. Generally, these losses are defined as interruptions in economic activities and are not related to the damaged enterprises. Even limited physical damage to property and infrastructure caused by natural disaster can produce chain reaction of losses in supply chain within a certain region. The Space Syntax Methodology is developed and used for accessing the characteristics of buildings, cities or the surrounding space in general. Although the methodology was primarily developed as urban planning method, it was also applied in the field of social and economic networks. Various studies of poverty, crime, disaster management and real estate prices are based on this methodology. The economic activities within a specific area are in a state of equilibrium before a disastrous event occurs. The disaster will change the spatial configuration (streets, buildings and infrastructure) causing negative effect on the economic networks and business opportunities. The main assumption of the research is that potential indirect losses could be estimated by comparing the Space Syntax characteristics before and after a disastrous event by measuring the deterioration of links between economic enterprises. The methodology is applied in a practical study of urban area. OpenStreetMap data is used as road-centred map of the city of York. The Historical Flood Map of the UK Environment Agency is used to setup disaster event impact. The Angular Segment Analysis implemented in DepthmapX software is used as the main method for analysis. The study of applicable network measures shows that Normalised Angular Choice can be used as criteria for selecting alternatives for minimizing indirect costs caused by road network damages. At the same time, this methodology cannot be used for monetizing indirect costs or identifying losses in different economic sectors. The study approach does not contradict the main theoretical approaches and it gives new opportunities for research on disasters recovery.