Published June 25, 2026 | Version 2.1

A map of trees in New York City classified at the genus level from remote sensing

Description

Summary

This dataset is a classification of trees in New York City at the genus level, derived from remote sensing and a street tree database. A web-based visualizer of the tree map is available here: https://nyctreegenusmap.com/

Data descriptor paper in Scientific Data: Miller, D.L., Young, A.R., Ghosh, A.K., Green, A.R., Jumonville, G., Keenan, O.J., Wang, C., Xi, W., Young, S.R., Ho, G.-Y., Katz, D.S.W., 2026. Classification of trees in New York City at the genus level from PlanetScope satellite imagery and airborne lidar. Sci Data. https://doi.org/10.1038/s41597-026-08104-3

The classification is a collection of polygons for tree crowns, stored as a geopackage file (gpkg). This dataset covers all tree canopy in the city (i.e., wall-to-wall), with canopy cover current for 2021. There are classification predictions for 1,806,811 tree crowns, with additional crowns inserted from reference street tree database data (for 1,821,184 total labeled) into the source tree crown polygon dataset (2,127,625 total crowns, the difference being unclassified due to incomplete data). The overall accuracy is 82.0% (kappa = 0.794) for trees with full and complete crowns ("high-quality"), and 72.1% (kappa = 0.686) when including trees with poorer canopy condition and among other genera not included in the classifier ("expanded").
 
In the Genus_Predicted column, each crown is classified as one of 18 common, dominant deciduous tree genera present in the city, based on Nowak et al. (2018) and Treglia et al. (2021). There are many more (hundreds) of tree species in the city, and this is restricted to the genus level for the most common genera because of limitations in the separability with the XGBoost classifier.

 

Included genera are:

  • Acer (maple)
  • Ailanthus (tree of heaven)
  • Betula (birch)
  • Fraxinus (ash)
  • Ginkgo (ginkgo)
  • Gleditsia (honeylocust)
  • Liquidambar (sweetgum)
  • Liriodendron (tuliptree)
  • Malus (apple)
  • Platanus (London planetree and sycamore)
  • Prunus (cherry)
  • Pyrus (pear)
  • Quercus (oak)
  • Robinia (black locust)
  • Styphnolobium (pagoda tree)
  • Tilia (linden)
  • Ulmus (elm)
  • Zelkova (zelkova)

However, where a single valid street tree database point intersects with a tree crown object, we include this reference value in the Genus_Ref column (as well as Species_Ref, FullCultivar_Ref, and other information from the street tree database).

Where available, we merge the genus label from the street tree database into the labeled classification, superseding any predicted classification label; this is stored in the Genus_Merged column. This includes many more genera than we were able to map with the classifier.

In normal usage, we recommend using the Genus_Merged column.

 

This dataset is derived from:

  • NYC Parks & Recreation Forestry Tree Points street tree database, which are surveyed by expert staff at Parks, the Natural Areas Conservancy of NYC, and citizen scientists (and validated by expert staff). This is the reference database for types of trees as geospatial points, but is limited to trees along streets and in some parks. It includes genus, species, cultivar, diameter at breast health, tree crown and health quality flags, and additional ancillary information. This dataset is available at: https://data.cityofnewyork.us/Environment/Forestry-Tree-Points/hn5i-inap/about_data
  • Tree crown polygons for 2021 from the Nature Conservancy New York Cities Program and the University of Vermont Spatial Analysis Lab. It was made with airborne lidar and high resolution aerial imagery. This dataset is available at: https://zenodo.org/records/14053441 (The Nature Conservancy, 2024).
  • Airborne lidar collected in 2021 across all of NYC. This data was used to create the tree crown polygon data (by TNC and UVM), and it was also used to develop tree crown metrics related to tree structure. This dataset is available at: https://gis.ny.gov/lidar
  • Satellite imagery time series from PlanetScope satellite imagery (Planet Labs, San Francisco, California; https://docs.planet.com/data/imagery/planetscope/). This imagery is gridded at 3 m spatial resolution in the visible and near infrared, with observations from a constellation of satellites acquiring imagery daily or more frequently. However, actual return interval is often several days due to clouds and other data quality filtering.

 

Main geopackage file:

nyc_class_tree_genus_polygons_v2_1.gpkg

In addition to the main geopackage file, ancillary data files include:

  • Accuracy tables (confusion matrix) with separate validation tree crowns not included in the classification training. There are two csv files, one for a high-quality tree crown test set, and one for the expanded test set including poorer quality tree crowns and other genera: nyc_class_tree_genus_polygons_v2_1_accuracy_table_highquality.csv
    nyc_class_tree_genus_polygons_v2_1_accuracy_tables_expanded.csv
  • Column description file for classification attribute table. Lidar crown metrics were largely based on selection of metrics used in Alonzo et al. (2014): nyc_class_tree_genus_polygons_v2_1_attribute_description.csv

 

Geospatial projection information

New York State Plan Long Island Zone (US survey foot) coordinate reference system, EPSG 2263 (The Nature Conservancy 2024).

 

Funding information

This work is supported by the McIntire-Stennis, project award number 7005302, from the U.S. Department of Agriculture’s National Institute of Food and Agriculture, and is supported in part by the Cornell Atkinson Center for Sustainability.

 

Acknowledgments

This work utilized data made available through the NASA Commercial Satellite Data Acquisition (CSDA) Program. Includes copyrighted material of Planet Labs PBC. All rights reserved. 

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Additional details

Related works

Requires
Dataset: 10.5281/zenodo.14053441 (DOI)

Software

Repository URL
https://github.com/dlm4/nyc_tree_genus_map
Programming language
R

References

  • Alonzo, M., Bookhagen, B., & Roberts, D. A. (2014). Urban tree species mapping using hyperspectral and lidar data fusion. Remote Sensing of Environment, 148, 70–83. https://doi.org/10.1016/j.rse.2014.03.018
  • Nowak, D. J., Bodine, A. R., Hoehn, R. E., Ellis, A., Hirabayashi, S., Coville, R., Auyeung, D. S. N., Sonti, N. F., Hallett, R. A., Johnson, M. L., Stephan, E., Taggart, T., & Endreny, T. (2018). The Urban Forest of New York City (No. NRS-RB-117; p. NRS-RB-117). U.S. Department of Agriculture, Forest Service, Northern Research Station. https://doi.org/10.2737/NRS-RB-117
  • The Nature Conservancy. (2024). New York City Land Cover (2021), Tree Canopy Change (2017-2021), and Estimated Tree Location and Crown Data (2021). Developed under contract by the University of Vermont Spatial Analysis Laboratory. [Dataset]. https://doi.org/10.5281/zenodo.14053441
  • Treglia, M. L., Acosta-Morel, M., Crabtree, D., Galbo, K., Lin-Moges, T., Van Slooten, A., & Maxwell, E. N. (2021). The State of the Urban Forest in New York City. Zenodo. https://doi.org/10.5281/ZENODO.5532876