ABSTRACT
This chapter presents a study investigating the emerging data-driven processing related to urban design and landscape design. It also presents a research that is intended to realize the potential of streaming the abstract geospatial data into a parametric landscape. Digital modeling is increasingly implemented in computing to create digital landscapes with a high degree of complexity, such as the agent-based urban modeling by Michael Batty, parametric urbanism by Patrick Schumacher, and City Engine by Pascal Mueller. The chapter defines digital landscape into two major categories, data representation and data simulation, based on its objective and computational techniques. It describes that the scenario-based analysis process and 4D data representation have created a concept of relationship model, instability, and de-centralization of the static solution. The paradigm in the digital landscape has been conceived as an ideal solution captured as a single design scheme.
