Efficacy of rain barrels and rain gardens to reduce urban pluvial flooding in densely built-up residential areas: a case study on Miyahara-Cho in Saitama City, Japan
Authors (first, second and last of 4)
Collection
Computational Sustainability and Design
Computational Sustainability and Design caters for computational designers, architects, urban designers, planners, scholars and policy-makers interested in sustainability and sustainable futures.This section publishes high-quality research on advanced design approaches, data-driven methods and algorithmic models that contribute to the global effort on climate change and sustainable future cities. The collection is mapped to the UN Sustainable Development Goal 11: to “Make cities and human settlements inclusive, safe, resilient and sustainable”.
Computational Sustainability and Design aims at the advancement of current knowledge on analysis, design and management of cities and urban communities, tacking global challenges and targets, including Race to Zero, Zero Carbon buildings, intelligent and sustainable future cities, and resilient communities.
CSD welcomes contributions from a range of design and related fields, including architecture, planning, urban design, computer science, engineering, data science, urban and human geography, and urban studies. In particular, the collection is intended as a platform for presentation and debate around impactful case studies, projects, analyses and critical studies emerging as the collaboration of transnational and multidisciplinary research and design teams.
Examples of topics relevant to CSD include, but are not limited to:- Innovative algorithmic approaches to sustainable aspects of design - Data-driven models applied to cities and communities - Computational methods applied to urban contexts - Generative design for sustainability - Analytical work on cities and predictive models for future cities - Data science models applied to more inclusive communities and urban developments
Editors
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Silvio Carta
Dr Silvio Carta is an architect (ARB/RIBA), Chartered Building Engineer (MCABE) and Associate Professor at the University of Hertfordshire (UK), where he is Head of Design and Director of the Professional Doctorates in Design (DDES). Silvio’s research includes Artificial Intelligence and Machine Learning design methods applied to the built environment, urban data science, data-driven approaches and computational design. He is currently a member of the technical committee: Data Sensing & Analysis (DSA) of the European Council on Computing in Construction (EC3).
