Exploring data-driven design in landscape architecture

Abstract

Currently, technology is growing exponentially, and with rapid urbanization, vast quantities of data are generated by the urban environment that is more spatial than before. Cities and ecological linkages become more complicated, and as the quality of the urban environment is determined mainly by how the data is used, the capacity to deal with data is becoming increasingly important in design processes and protocols. Therefore, this paper aims to introduce the data-driven design approach and distinguish the existing projects in landscape architecture based on their input and output types. Besides, it contributes mainly to bringing together the existing information in this field. The literature review process was applied to conduct potentially relevant literature on the research topic. Then, the existing projects were identified and reviewed. As the primary research outcome, most of the reviewed data-driven projects in landscape architecture received input data from environmental or human sources. At the same time, only 16% benefited from a mixed combination of environment and human-sourced data. Besides, only about 35% of the existing projects had adaptive or performative outputs, the most desirable characteristics towards environmental progress, while most were interactive. Although these projects are still in their early stages, this article illustrated the potentials of data-driven design to boost landscape performance in many ways. By unifying projects under a single framework, data-driven design can benefit more.