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Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
Published on: October 16, 2018
A 0.6-meter resolution canopy height model for the contiguous United States.
Scott L Morford1, Brady W Allred1, Shea P Coons1
1Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA.
Biorxiv : the Preprint Server for Biology
|May 7, 2026
Summary
We created NAIP-CHM, a detailed canopy height model using aerial imagery, to map U.S. vertical structures. This cost-effective tool enhances ecosystem monitoring and land management across the contiguous United States.
Area of Science:
- Ecology
- Remote Sensing
- Geospatial Analysis
Background:
- Above-ground vertical structure is vital for ecosystem monitoring, carbon accounting, and land management.
- Airborne lidar, while accurate, is costly and has limited coverage, restricting its widespread use.
- Existing models often exclude human-made structures, providing an incomplete landscape view.
Purpose of the Study:
- To develop a high-resolution (0.6m) canopy height and structure model (CHM) for the contiguous U.S.
- To create a model, NAIP-CHM, that includes both natural vegetation and human-made features.
- To provide an accessible, cost-effective alternative to lidar for detailed vertical structure mapping.
Main Methods:
- Utilized National Agriculture Imagery Program (NAIP) aerial imagery to derive the CHM.
- Employed a U-Net convolutional neural network with attention mechanisms and environmental conditioning.
- Trained and validated the model using 22.8 million co-registered NAIP imagery and lidar-derived CHM pairs, with stratified sampling for diverse ecosystems.
Main Results:
- Achieved a pixel-wise root mean square error (RMSE) of 2.28 meters and an R-squared (r²) of 0.87 across the contiguous U.S.
- For forested sites specifically, the model yielded an R² of 0.82 and an RMSE of 3.82 meters.
- The NAIP-CHM model successfully characterized the full vertical structure, including vegetation, buildings, and infrastructure.
Conclusions:
- NAIP-CHM offers a robust and scalable solution for mapping landscape vertical structure nationwide.
- The developed dataset, code, and cloud tools facilitate broad application in ecosystem monitoring and land management.
- This approach significantly lowers the barrier to entry for detailed vertical structure analysis compared to lidar.
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