ABSTRACT
Urban analysis models have a long history. One of their characteristics is that they involve a large range of researchers from different disciplines, who approach the city from different perspectives, at different scales and with different objectives. However, they rarely cooperate, thus operating in distinct silos. While this may have served the community reasonably well in the past, the emergence of rich data and the speed at which transport changes nowadays, make the need for direct collaboration and interaction urgent. In this chapter, we recognise and present three of these different viewpoints, organized in three levels: (i) lower: architectural level, (ii) middle: transportation level, and (iii) top: geographical level. Particular emphasis is placed on the challenges and limitations of the integration between all levels, attempting to provide directions towards overcoming them. One such direction relates to the emergence of rich and ubiquitous data, and the proliferation of data-driven techniques, which can be a game-changer in how we think about urban analysis, and thus foster cross-sectional collaboration.
