VibrantVS Canopy Height Model (CHM)
This dataset provides a small validation sample of canopy height data for select areas across the western U.S. It includes GeoTIFF files for NAIP, LiDAR, and VibrantVS CHM.

About this dataset
This dataset provides a small validation sample of canopy height data for select locations across the western United States. Each sample includes three aligned raster layers—NAIP imagery, a LiDAR-derived canopy height model, and the VibrantVS AI canopy height model—allowing users to compare modeled and observed canopy structure under identical spatial conditions.
The NAIP imagery serves as the visual and spectral input for the VibrantVS model, while the LiDAR CHM provides benchmark measurements against which model performance can be evaluated. Together, these layers support research, model validation, and exploratory analysis of fine-scale vegetation structure in wildfire-prone landscapes.
What’s included in this dataset
How to interpret this layer
It includes three geospatial datasets in GeoTIFF format, designed for direct use in GIS applications.
1. NAIP Imagery
- Source: National Agriculture Imagery Program (NAIP)
- Format: GeoTIFF
- Bands: 4-band (Red, Green, Blue, Near-Infrared)
- Resolution: 0.5-meter
- Coverage: Selected areas across the western U.S.
- Temporal Availability: Collected every 2–3 years
2. LiDAR-Derived Canopy Height Model (CHM)
- Source: 3D Elevation Program (3DEP) LiDAR surveys (2014–2021)
- Format: GeoTIFF
- Resolution: 1-meter
- Coverage: Selected validation areas within the western U.S.
- Data Type: Digital Surface Model (DSM) representing canopy height
3. VibrantVS Canopy Height Model (CHM)
- Source: AI-generated canopy height model using a Vision Transformer (ViT) trained on NAIP imagery
- Format: GeoTIFF
- Resolution: 0.5-meter
- Coverage: Selected validation areas within the western U.S.
- Update Frequency: Approx. 3-year cycle
- Purpose: Provides scalable, high-precision canopy height estimates for wildfire mitigation, ecological monitoring, and land management

Explore the full Data Story
To dive deeper into the methods, context, and example applications behind this dataset, explore the full VPDC Data Story that accompanies it.
See the full Data Story ⭢How to get Started:
- Explore the map: Zoom and pan to locate your area of interest. The tile grid outlines the spatial boundaries of the dataset.
- Select your tiles: Click one or more tiles to highlight them. Each tile corresponds to a geographic area you can download.
- Review & adjust: Use the checkboxes in the selection list to confirm or deselect tiles.
- Download your data: Click the "Download Data" button to bundle your selected tiles into a single ZIP file.
A few things to keep in mind:
- Download limitations: For best performance, please select no more than 20 tiles per download. Larger selections may slow your browser or cause issues.
- Need more coverage? No problem—just download in smaller batches. All tiles use the same folder structure, so you can easily merge them later in your GIS software for seamless regional analysis.
- Working at larger scales? For very large areas, contact us to discuss alternative delivery options.
Tiling grid: To keep downloads efficient and analysis straightforward, the dataset is organized into a fixed tiling grid. This approach prioritizes optimal file sizes and regional coverage for analytical workflows. While the grid follows standard geospatial conventions, it is not pixel-aligned to USGS ARD or other standardized grids.
Selected Data Tiles:
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VibrantVS Canopy Height Model (CHM)
This dataset provides a small validation sample of canopy height data for select areas across the western U.S. It includes GeoTIFF files for NAIP, LiDAR, and VibrantVS CHM.
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Direct Access
Get hands-on access to this dataset using interactive notebooks. Choose between the Google Colab notebook for quick exploration in your browser or access the hosted Jupyter Notebooks via Binder or GitHub for more advanced workflows.
Direct access to the Google Collab notebook
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Click the button to the left to launch an interactive notebook directly in your browser. This pre-configured Colab notebook provides a quick and easy way to explore, visualize, and analyze the data—no setup required.
GitHub hosted Jupyter Notebooks
Flexible access for advanced workflows
Access the full collection of Jupyter Notebooks hosted on GitHub. These notebooks can be used on your local machine or via cloud platforms like Binder or Google Colaboratory, providing flexibility for more advanced customizations.
Licensing & Attribution
Licensed under Creative Commons Attribution–NonCommercial–ShareAlike 4.0 International (CC BY-NC-SA 4.0).
You may share and adapt this dataset for noncommercial purposes with attribution under the same license.
Required Attribution:
© 2025 Vibrant Planet. Distributed by Vibrant Planet Data Commons. Licensed under CC BY-NC-SA 4.0.
For commercial or special-use requests, email us at contact@vpdatacommons.org
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