ArborLayer turns open source geospatial data into a practical view of individual tree locations, heights and canopy sizes in the form of exact canopy polygons and radius crowns. Explore the results as an interactive layer, inspect individual features and add editable, labelled trees to your planning drawings or GIS workflow.
How ArborLayer is built: We built a custom mapping pipeline that analyses open LiDAR point clouds for height, vegetation structure, point density and laser-return patterns. Our algorithms and machine-learning models combine those signals with LiDAR surface and terrain models, derived vegetation objects, satellite imagery and building footprints to separate likely trees from buildings and other above-ground features.
Human-reviewed samples help us spot false positives and improve the models over time. Each mapped feature includes its source date, giving planning and property professionals useful early-stage context while making the age of the underlying data clear.
ArborLayer is in its pilot data phase. We are continually striving to improve the quality and accuracy of locations, heights and canopies where individual tree identification is challenging, and individual trees can be missed, merged or incorrectly identified. Use ArborLayer to inform early decisions, prior to full and formal tree surveys being commissioned.