Tipping Point Analysis Using Remote Sensing to Investigate the Impacts of Green Infrastructure on Social and Environmental Benefits in Urban Areas in the United States

To comply with federal stormwater regulations, practitioners in the United States implement a mix of green and grey stormwater management infrastructure. Grey stormwater infrastructure is ubiquitous and managers have high institutional knowledge and confidence in implementing grey solutions. Practitioners generally have less institutional knowledge and confidence in green infrastructure (GI) and look for other attributes to justify uncertainty associated with GI installations. These attributes can be classified into social and environmental co-benefits, which are ancillary benefits accrued with the installation of GI. This study aims to characterize the required size and distribution of GI to achieve common social and environmental co-benefits. Using spatial data of GI installations in Austin, Denver, Philadelphia, Seattle and Washington DC we examine the extent of GI within those cities. A tipping point analysis is performed on a targeted list of 18 of the most commonly cited co-benefits generated from a literature review and validated by an expert panel. These co-benefits range from aesthetics to urban heat island mitigation. The estimated tipping points establish the scale at which GI needs to be installed to realize each co-benefit, giving practitioners more insight into the impacts on co-benefits from centralized versus distributed approaches. The tipping point analysis includes a mix of remote sensing, hydrologic modeling, and spatial mapping approaches. Remote sensing is used to assess baseline trends in city greenness and the impact of GI on city greenness trends. Greenness trends from GI are then linked to co-benefits that are positively correlated with a vegetated signal, like habitat creation. Hydrologic modeling is employed to measure co-benefits that cannot directly be associated with vegetation changes, like flood control mitigation. Spatial mapping is used in both approaches to translate results to existing conditions in each city. Results of this analysis will ultimately be linked to model outputs in a decision support tool being created for stormwater managers. Our ultimate goal is to provide a tool that allows practitioners to evaluate GI interventions through holistic analysis of current conditions.