This paper examines how existing data limitations and approaches to assessing street tree biodiversity and age diversity constrain our ability to plan, design, and manage equitable and resilient urban street tree systems. In response, we developed an open‑source R-Shiny data pipeline and provided recommendations to strengthen data consistency and comparability. Applying this application to street tree programs in 26 U.S. cities reveals significant variation in biodiversity outcomes and highlights the need for targeted investment. Our approach supports more strategic planting decisions, prioritizes vulnerableneighborhoods, and strengthens long‑term urban forest resilience under climate change by directing planting, maintenance, and monitoring resources to neighborhoods falling below resilience-oriented benchmarks.
| Autor / Author: | Garcia, Lara; Flohr, Travis; Albuja, Diana; Figueiredo, Caio; Heris, Mehdi |
| Institution / Institution: | Penn State University, Pennsylvania/USA; Penn State University, Pennsylvania/USA; Penn State University, Pennsylvania/USA; University of Arkansas, Arkansas/USA; Hunter College, New York/USA |
| Seitenzahl / Pages: | 17 |
| Sprache / Language: | Englisch |
| Veröffentlichung / Publication: | JoDLA – Journal of Digital Landscape Architecture, 11-2026 |
| Tagung / Conference: | Digital Landscape Architecture 2026 – Cutting Edge |
| Veranstaltungsort, -datum / Venue, Date: | University College Dublin (UCD), Ireland 28-05-26 - 29-05-26 |
| Schlüsselwörter (de): | |
| Keywords (en): | Street trees, biodiversity, equity, data science, urban forest resiliency |
| Paper review type: | Full Paper Review |
| DOI: | doi:10.14627/537770062 |
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