Author: Matteo Lomaglio
The paper and presentation focus on a project that combines ecological and architectural scales and addresses the design and transformation of the environment of the Venetian Lagoon through advanced technologies. The project draws from a combined systemic and design approach and proposes a dynamic and varied attitude to landscape preservation and transformation. In so doing the project focuses on a multi-scalar approach to the ecosystem in which Venice is located. The multi-criteria analysis was undertaken based on available ecological, geological and hydrological information of the lagoon. The understanding of the complexity of this ecosystem made it necessary to investigate both current and innovative technological developments reflecting a diverse approach to ecological restoration of dynamic environments. This includes selective preservation and selective transformation in a dynamic an ongoing project for the lagoon, a proposed new botanical garden as a terrain vague, and the architectures and technologies that are key provisions in this complex process.
For this reason, it is of fundamental importance to define a complex network of relationships between the different pieces of information collected, in order to encode them together into an integrated set of generative algorithms. The aim of the thesis is the definition of complex systems of data-driven architectural strategies through computational tools. The focus is not only on the architectural scale, but the research and strategies involve the multiple scales of the lagoon, considering the concept of “scale” as determined by two main components, both the resolution (as far as spatial data is concerned) and time. The project aims to utilize the use of advanced computational methodologies in close relationship to geospatial information to inform architectural strategies at different scales. It also attempts to initiate a new approach for collaboration between disciplines such as diverse and interrelated as geography, ecology, urban planning, computer science, statistics and architecture.