Clean Corridors

A Data-Driven Design for Multi-Scale Green Infrastructure Design

Master thesis (2024)

Authors

M. van der Waal Architecture and the Built Environment

Contributors

D. Cannatella Urban Data Science - Architecture and the Built Environment (mentor)
F. Rizzetto Environmental Technology and Design - Architecture and the Built Environment (mentor)
Faculty
Architecture and the Built Environment
More Info
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Published Date

20-06-2024

Language

English

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Faculty

Architecture and the Built Environment

Abstract

Global trends in urbanization, industrialization, and intensive agriculture are harming our (local) environment. These activities require significant mounts of resources, energy, and transportation, whilst creating increased waste streams. Poor management of these sites has led to severe soil, water, and air contamination. Currently, Europe has 2.8 million potentially soil-contaminated sites, with around 340,000 in direct need of remediation. Additionally, these activities cause land cover changes, shrinking and fragmenting the natural landscape. The decreased ecosystem connectivity is harmful to ecological processes and biodiversity. Phytoremediation and green infrastructure (GI) planning offer robust nature-based solutions to these problems. Integrating these solutions holds the potential to utilize the same vegetation for both solutions. However, integration of these solutions is challenging due to the scalar gap between the locality of phytotechnologies and the regional scale that is used for GI planning.
This thesis presents a systematic approach to integrating small-scale phytoremediation interventions within regional-scale GI planning. Using a multi-scalar, data-driven framework, this research uses computational simulations, calculations, and assessments to identify optimal design solutions, including traditional GIS mapping, graph-theoretic networks, and neural networks. This integrated approach aims to enhance environmental remediation and ecosystem connectivity and provides a comprehensive strategy for sustainable regional planning.