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From flows to workflows: integrating spatially explicit urban metabolism assessment techniques into the urban landscape infrastructure planning process
Journal article   Open access   Peer reviewed

From flows to workflows: integrating spatially explicit urban metabolism assessment techniques into the urban landscape infrastructure planning process

Luciano Brina and Lynette Cheah
Journal of Industrial Ecology, Vol.Advanced access
13-May-2026
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s44498-026-00056-61.39 MBDownloadView
Published Version (Advanced Access) Open Access CC BY V4.0

Abstract

industrial ecology landscape architecture urban planning geographic information science landscape socio-economic metabolism urban metabolism
The operational convergence between urban metabolism (UM) and urban landscape infrastructure planning (ULIP) can contribute to the informed visualization, spatialization, implementation, evaluation and maintenance of nature-based solutions, circular and climate-sensitive designs, and virtuous urban food-water-carbon nexuses. However, such integration remains underdeveloped and unstructured due to dissonances regarding spatial scales of analysis and intervention, unclear operational entry points of each party along the planning process, and divergent standpoints concerning the role of quali-quantitative landscape metabolism data. To bridge these gaps, we present a comprehensive yet open-ended workflow aiming to overcome critical shortcomings of UM and ULIP: lack of common data visualization cultures; arbitrariness implementing UM data into resource-aware planning decisions; and deficient sociometabolic scenario building capabilities. It does so by identifying shared interpretations of space, spatiality and spatialization ; suitable spatial scales of interdisciplinary collaboration; and UM concepts, frameworks, models and instruments applicable to each stage of said process, emphasizing [geo]spatial and visually explicit, geographic information science-reliant approaches. This paper uses 52 records retrieved through a bias-aware, iterative bibliometric analysis using the Web of Science Core Collection (years 2015 to 2025), in accordance with the PRISMA Statement 2020.

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