Enhancing landscape connectivity through multifunctional green infrastructure corridor modeling and design

  • February 2019
  • Peer-Reviewed Articles
  • Multiple

Zhang, Z., Meerow, S., Newell, J.P., & M. Lindquist. Enhancing landscape connectivity through multifunctional green infrastructure corridor modeling and design. Urban Forestry & Urban Greening. 38, 305-317.

ABSTRACT: Landscape connectivity is critical for ecosystem health and biodiversity conservation, yet urbanization is increasing habitat fragmentation. Green corridors that connect isolated remnant habitat patches (e.g. parks) can increase connectivity and provide ecosystem services in cities. Vacant land, especially prevalent in shrinking cities, presents a unique opportunity to reconnect these landscapes. This paper provides a practical and replicable approach for assessing landscape connectivity patterns and identifying priority locations for green corridors. The methodology integrates social and ecological factors coupled with site-scale multifunctional greenway designs and is applied to the city of Detroit as a proof of concept. First, we use FRAGSTATS to evaluate structural landscape connectivity patterns at a census tract scale. A functional connectivity assessment based on graph theory and Conefor software is used to validate the results, which indicate that habitat is highly fragmented in Detroit. To identify opportunities to reduce this fragmentation, we use a least-cost path approach to map potential green corridors linking city parks through vacant parcels, alleys, and smaller green spaces, and prioritize these corridors using a gravity model and network analysis. To make the model more concrete and useful for decision-makers, we develop site-level multifunctional corridor design typologies. This study presents a novel approach to assessing urban connectivity and a multi-scalar, systematic methodology for planning urban green infrastructure networks that connects landscape ecology with practical planning and design considerations to maximize social and ecological functions.

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