A Data-Driven Design Approach for Multi-scale Green Infrastructure Design: Integrating Landscape Connectivity and Phytoremediation in the Piedmont Region (IT)

Rapid urbanization, intensive agriculture, and industrial activities in Europe have led to escalating landscape fragmentation and environmental pollution, posing threats to biodiversity, and causing degradation of vital natural resources over time. In response, the imperative for sustainable green infrastructure (GI) development has intensified to effectively mitigate the adverse impacts of human activities on landscapes and enhance their capacity to support life. However, despite the recognized importance of GI in addressing environmental challenges, its design and implementation remains a complex challenge, due to the difficulty to fully grasp and assess how GI provisions link to benefits at multiple scales, and how the latter can be maximized. This paper introduces a data-driven approach for the integrated and multi-scalar design of GI, leveraging phytoremediation techniques to remediate polluted sites. By employing phytoremediation techniques at the local scale, this approach aims at enhancing local soil and water conditions while simultaneously reinforcing connectivity in regional ecological networks. The proposed approach initiates with a Morphological Spatial Pattern Analysis (MSPA) and Network Connectivity Analysis (MCA) to identify potential ecological sources and assess the impact of designed green corridors on the performance of existing regional networks. Subsequently, mapping and characterization of polluted sites are carried out in a GIS environment to identify strategic areas for the development of GI features at the local scale. This research makes use of the Novara area in the Piedmont region (IT) to test the above mentioned approach. Initial results show that quantifying and integrating landscape connectivity with the transformation of polluted sites is a viable way to optimize GI design allowing strategic design interventions on the regional and local scale. The proposed data-driven design approach offers a holistic solution to the challenges of urbanization and landscape fragmentation by providing a framework that enhances ecological resilience, optimizes resource allocation, and contributes to the creation of multifunctional landscapes.