Green Infrastructure Spatial Planning Model

Green infrastructure (parks, greenways, green roofs, bioswales, etc.) is an increasingly popular strategy for cities to enhance resilience and ecosystem services, from improved public health to stormwater management. It is commonly promoted on the basis of its multifunctionality, but in practice green infrastructure plans and studies tend to focus on one or a few benefits, such as stormwater management, and rarely assess potential synergies and tradeoffs between other desired functions. As a result, green infrastructure may not be strategically sited to maximize social and environmental benefits. The Green Infrastructure Spatial Planning (GISP) model provides a stakeholder-driven methodology for identifying green infrastructure tradeoffs, synergies, and ‘hotspots’. The model is designed to facilitate spatial planning at a citywide scale, to be followed by detailed suitability assessments at smaller spatial scales.

The GISP model is made up of six GIS layers corresponding to planning priorities (stormwater management, social vulnerability, access to green space, air quality, the urban heat island effect, and landscape connectivity). Individual criteria are mapped and spatial tradeoffs and synergies assessed. For the Detroit model, the six criteria are weighted based on local stakeholders' priorities. For New York City, Los Angeles, and Manila, a more interactive online app allows the user to set the criteria weights based on their own priorities and visualize the weighted and combined results. To read a more detailed description of the model and Detroit results see the published article in Landscape and Urban Planning.

To access the models, click the city name below. The sites may take a minute to load. For Los Angeles, New York, and Manila when you click one of the city links it takes you to the R Shiny App where you have to adjust the weights on the "generate criteria combination" tab and hit the "click here to generate criteria combination" button. Note that the combined and weighted map may take a few minutes to load.