An open observatory from the Better Places Lab. Explore Auckland’s trees, investigate our estimates and help test what the models get right or wrong.
ALTO brings Auckland’s tree records, aerial laser surveys and imagery together. For each tree, it estimates size, form, roots and environmental benefits, and links earlier canopy records where available. Open a profile to see the source data, compare estimates and find observations that could improve them.
Service totals exclude nominal crownless-tree scenarios.
Select a tree to explore its source records, dimensions, root estimates, environmental benefits and canopy history. You can download that tree’s complete record as JSON from its profile.
The methods explain how ALTO finds trees, estimates their dimensions and benefits, links surveys through time, and tests its predictions. They include the assumptions, test results and gaps still to resolve. Model code and documentation.
V5 combines the 2024 laser survey with aerial NDVI to redraw the canopy. Fewer or different crowns reflect the new segmentation. Earlier detections, dimensions and field observations remain in each tree’s full record.
Unverified Council notable-tree positions stay separate from automatic crown matches. Crown boundaries can still split one tree or join several trees. Read the v5 release notes.
Trees found only in the 2024 laser survey are labelled by how strong the evidence is: very likely, probably or possibly a tree. A possible tree may be a hedge or a large shrub. The “Possible & unverified trees” switch in Layers hides them.
The current map covers metropolitan Auckland. Earlier canopy records depend on historic survey coverage and successful matching. Records outside the v5 footprint retain earlier measurements. Unmatched records remain available for review. Trunk diameter and roots are estimated; field measurements would improve both. Species names come from source inventories, while the classifier estimates four broad tree types.
Developed by the Better Places Lab (Dr Timothy F. Welch), Waipapa Taumata Rau | University of Auckland. Built on Auckland Council open data, LINZ LiDAR and imagery, and i-Tree species references.