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Updated: Jun 7, 2026
09:44
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 Allred2, Shea P Coons2
1Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA. scott.morford@umontana.edu.
Scientific Data
|June 5, 2026
Summary
We created NAIP-CHM, a detailed 3D model of U.S. landscapes using aerial imagery. This tool accurately maps vertical structures like trees and buildings, aiding ecosystem monitoring and land management.
Area of Science:
- Geospatial science
- Remote sensing
- Ecology
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, limiting comprehensive landscape analysis.
Purpose of the Study:
- To develop a high-resolution (0.6m) canopy height and structure model (CHM) for the contiguous U.S. using publicly available aerial imagery.
- To create a model that characterizes the full vertical structure of landscapes, including vegetation, buildings, and infrastructure.
- To provide accessible tools and data for broad application in land management and ecosystem monitoring.
Main Methods:
- Utilized the National Agriculture Imagery Program (NAIP) aerial imagery to derive the NAIP-CHM.
- Employed a U-Net convolutional neural network with attention mechanisms and environmental conditioning.
- Trained and validated the model using a large dataset of 22.8 million co-registered NAIP imagery and lidar-derived CHM pairs, with stratified sampling for diverse ecosystems.
Main Results:
- The NAIP-CHM model achieved a pixel-wise root mean square error (RMSE) of 2.28 meters and an 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 developed model successfully characterizes both natural and human-made vertical structures.
Conclusions:
- NAIP-CHM offers a cost-effective and comprehensive solution for mapping landscape vertical structure across the U.S.
- The model's accuracy and broad coverage support improved ecosystem monitoring, carbon accounting, and land management.
- The provision of dataset, source code, and cloud tools facilitates widespread adoption and application without specialized computational needs.
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