Tree Planting Sites Identification

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Abstract

This project identifies optimal urban tree planting sites in Buffalo, NY using the Bureau of Forestry Tree Inventory dataset (133,000+ records). We applied K-Means clustering, regression models, and decision tree classification combined with geospatial visualization (heatmaps & interactive maps) to recommend zones for new plantations. Results highlight priority areas with low eco-benefits where strategic tree planting can maximize environmental impact.

Method Overview

Method Overview Diagram
Pipeline: Data cleaning → Clustering & regression → GIS visualization → Recommendations.

Interactive Maps

Explore interactive results directly below (pan, zoom, and inspect data points):

Results

Cluster Heatmap
Heatmap of eco-benefits and low-benefit clusters.
Cluster Map
K-Means clustering of tree sites across Buffalo.
Top 10 Tree Planting Sites
Recommended top 10 planting locations by benefit shortfall.
Tree Planting Map
Interactive tree planting map with cluster overlays.

Conclusion

Our data-driven framework successfully highlights urban zones where tree planting can significantly improve environmental benefits such as COâ‚‚ absorption and stormwater retention. The approach can be extended to other cities to guide smart urban forestry planning.