Hardening the American Landscape

How do different infill policies affect urban hardscapes? As the zoning reform movement accelerates infill development, arguments around equity and affordability contend with environmental effects. There are opportunities for synthesis between smart growth and ecological concepts by reducing vehicle miles traveled and protecting rural landscapes.

However, research on smart growth has neglected to examine the effects of infill policies on the intensification of hardships.

In "The Hardening of the American Landscape: Effects of Land Use Policy on the Evolution of Urban Surfaces" (Journal of the American Planning Association Vol. 90, No. 2) Brian Muller and Stefania Mitova introduce hardscape and stormwater policy into smart growth research. The authors tested a machine learning model that enables local leaders to assess the impacts of policy combinations on the rates of hardscape expansion during rapid infill.

Muller and Mitova's approach integrated land use change models, urban form assessments, and policy-based scenarios. Their methodology involved employing a random forest machine learning model and logistic regression techniques to simulate forthcoming patterns of hardscape alteration. By utilizing these methods, the authors could assess urban surface patterns through a case study simulation of prospective development policies in Denver.

They devised and examined six sets of land use policies and three sets of mitigation and adaptation policies, subsequently comparing the resulting hardscape outputs.

Key Findings and Implications

• Infill can be managed to minimize environmental risks.
• Local factors like hardscape connectivity greatly influence the environmental impact of infill policies.
• Current mitigation strategies face technical hurdles in adapting to rapid hardscape increases.
• Hardscape modeling aids planning across scales, including neighborhood advocacy.
• Analysts need access to diverse tools to assess environmental impacts, including considerations beyond stormwater like urban heat.

Based on an evaluation of current development processes, Muller and Mitova modeled four development scenarios:

• Dispersed growth
• Extensive corridors
• Intensive corridors
• Major centers

These scenarios encompass popular infill policies, including those promoting ADUs and small centers. Additionally, they explored landscape design, where building footprints remain unchanged while development practices shift, and high density.

Using their model to evaluate mitigation scenarios, the authors examined current adaptation policies as well as alternative low-and high-cost policies. These included tiered treatment for smaller parcels, tree plantings, bioretention on public lands, and low-impact development policies.

Table 4: Additional areas of untreated hardscape within growth scenarios.

Policy Recommendations for Mitigating Environmental Risks

Their analysis, applied in Denver, revealed the following:

• Dispersed infill policies significantly accelerate hardscape rates and environmental risk.
• Current stormwater mitigation policies are inadequate to address the majority of scenarios involving increased infill hardscape.

The dwindling availability of larger parcels impacts adaptation policy. As populations shift spatially, governments face higher administrative costs for implementing policies on smaller lots. Developers encounter obstacles and expenses in lot selection and negotiation, aiming to cut regulatory costs.

The research revealed a wide array of policy choices available to local leaders interested in reducing rates of hardscape increase during rapid infill. The authors recommend modeling hardscape and infill patterns based on local factors rather than relying on generalized policy arguments.

Regression and random forest machine learning modeling can be key tools to test and craft policy mixes to mitigate the environmental risks of rapid infill development.