These indexes also utilize classical statistical methods like principal component analysis or regression modeling to measure total community vulnerability, as well as the influence of certain physical and social factors on vulnerability at various jurisdictional and socio-political levels (Birkmann 2007; Cutter, Boruff, and Shirley 2003; Wood, Burton, and Cutter 2010). However, these methods neglect spatial effects or interactions occurring between indicators occurring at different scales. Society is segregated and hierarchical, making scale a crucial consideration for accounting for interactions between multiscalar variables (Cozzens and Gieryn 1990; Giddens 1984; Schelling 1971; Subramanian, Duncan, and Jones 2001). Scale and spatial processes can inhibit the reliability of certain analytical types and physical hazard models devised for specific scales, resulting in biased conclusions based on the way areal units or scale of analysis are defined (Arbia and Petrarca 2011; Burt, Barber, and Rigby
These indexes also utilize classical statistical methods like principal component analysis or regression modeling to measure total community vulnerability, as well as the influence of certain physical and social factors on vulnerability at various jurisdictional and socio-political levels (Birkmann 2007; Cutter, Boruff, and Shirley 2003; Wood, Burton, and Cutter 2010). However, these methods neglect spatial effects or interactions occurring between indicators occurring at different scales. Society is segregated and hierarchical, making scale a crucial consideration for accounting for interactions between multiscalar variables (Cozzens and Gieryn 1990; Giddens 1984; Schelling 1971; Subramanian, Duncan, and Jones 2001). Scale and spatial processes can inhibit the reliability of certain analytical types and physical hazard models devised for specific scales, resulting in biased conclusions based on the way areal units or scale of analysis are defined (Arbia and Petrarca 2011; Burt, Barber, and Rigby