Pursuing Equitable Urban Tree Canopy Coverage in Vancouver, WA
Bibliographic record
Abstract
The City of Vancouver has received a recent assessment of urban tree canopy, completed in October 2021 with data from 2019 and 2020. Through regularly and thoroughly assessing tree canopy, the City of Vancouver’s Urban Forestry program can identify spaces for improvement, with equitable tree canopy coverage throughout the city as a primary goal. The benefits of a robust tree canopy range from regulatory infrastructure, like storm water management and heat mitigation, to proven psychological benefits associated with access to greenery. The data provided by the most recent tree canopy report informs where the program targets efforts and resources. Historically, Urban Forestry has focused outreach efforts on the neighborhood level. With this new project and data, the program can assess tree canopy on many scales, including the smallest geographic scales possible--census tracts and blocks. Used by the U.S. Census Bureau to track populations, these units are invaluable indicators of environmental justice, as they are directly linked with demographic and socioeconomic data. The program is utilizing resources like the Washington Environmental Health Disparities map and Tree Equity Score information in tandem with this new tree canopy assessment to concentrate new canopy growth on traditionally overburdened communities with disproportionately low canopy coverage. The recent Tree Canopy Assessment findings show current tree cover in the city of Vancouver rests at 19%, up from 16% in 2011 (this increase in canopy includes newly annexed areas), and 32% of the city remains possible planting area. Urban Forestry maintains a goal of reaching 28% urban tree cover by 2030. With 74% of possible planting area in Vancouver located on private property, Urban Forestry is concerned with removing barriers to planting, maintenance, and preservation to make tree stewardship feasible and accessible to all residents. The ambitious goal of 28% tree cover by 2030 must be a joint effort between the city, partnered organizations, and residents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".