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A tree-planting decision support tool for urban heat mitigation
Zoey R Werbin1, Leila Heidari2, Sarabeth Buckley3
1Department of Biology, Boston University, Boston, Massachusetts, United States of America.
Urban trees combat city heat, reducing health risks. A new tool, Right Place, Right Tree-Boston, guides strategic tree planting to maximize cooling benefits and improve urban resilience.
Area of Science:
- Environmental Science
- Urban Planning
- Public Health
Background:
- Urban heat island (UHI) effect exacerbates heat-related health risks in cities.
- Urban trees offer cooling and energy-saving co-benefits but face challenges in expansion due to maintenance and mortality.
- Effective urban forest expansion requires informed decision-making to maximize mitigation potential.
Purpose of the Study:
- To introduce the Right Place, Right Tree-Boston interactive web application for informed tree planting decisions.
- To identify priority areas for urban canopy expansion using a Boston-specific Heat Vulnerability Index (HVI) and land surface temperature data.
- To provide comprehensive resources supporting urban forest management and resilience.
Main Methods:
- Development of a Boston-specific Heat Vulnerability Index (HVI).
- Integration of HVI data with maps of summer daytime land surface temperatures.
- Inclusion of data on tree pests, diseases, species suitability, land ownership, and maintenance.
Main Results:
- Identification of priority regions for urban tree planting based on heat vulnerability and temperature data.
- The Right Place, Right Tree-Boston application offers a centralized platform for diverse urban forestry information.
- The tool supports decision-making for city officials and residents at multiple spatial scales.
Conclusions:
- Strategic tree planting, guided by tools like Right Place, Right Tree-Boston, is crucial for mitigating urban heat and enhancing public health.
- Addressing tree maintenance and mortality is key to successful urban canopy expansion.
- The application empowers stakeholders to make data-driven decisions for a more resilient urban forest.
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