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Description

This data set provides estimates of above-ground biomass (AGB), canopy height, and percent tree cover at 30-m spatial resolution for Sonoma County, California, USA, for the nominal year 2013. Biomass estimates, megagrams of biomass per hectare (Mg/ha) were generated using a combination of LiDAR data, field plot measurements, and random forest modeling approaches. Estimates of AGB uncertainty are also provided. Maximum canopy height and tree cover were derived from LiDAR data and high-resolution National Agriculture Imagery Program (NAIP) images.

Product Summary

Platforms
Airplane,
COMPUTERS,
MODELS
Instruments
LIDAR,
Computer
Spatial Extent
N: 38.8642 S: 38.1017 E: -122.339 W: -123.542
Coordinate System
CARTESIAN
Granule Spatial Representation
CARTESIAN
Temporal Extent
2013-09-01 to 2013-12-31
Data Partner
THE OAK RIDGE NATIONAL LABORATORY (ORNL) DISTRIBUTED ACTIVE ARCHIVE CENTER (DAAC) (ORNL_DAAC)
Concept ID
C2389082431-ORNL_CLOUD
Data State
COMPLETE
Processing Level
3
Published
Updated
Science Keywords
Biomass,
Canopy Characteristics,
Vegetation Cover

Citation

Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.

Copy Citation

Dubayah, R. O., Swatantran, A., Huang, W., Duncanson, L., Tang, H., Johnson, K., O'Neil-Dunne, J., & Hurtt, G. C. (2017). CMS: LiDAR-derived Biomass, Canopy Height and Cover, Sonoma County, California, 2013 (Version 1). ORNL Distributed Active Archive Center. https://doi.org/10.3334/ORNLDAAC/1523 Date Accessed: 2025-10-11

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Title Year Author
Multi-resolution gridded maps of vegetation structure from GEDI
Estimating forest aboveground biomass using temporal features extracted from multiple satellite data products and ensemble machine learning algorithm
Combining simulated hyperspectral EnMAP and Landsat time series for forest aboveground biomass mapping
OBJECT BASED IMAGE ANALYSIS AND TEXTURE FEATURES FOR PASTURE CLASSIFICATION IN BRAZILIAN SAVANNAH
TOWARDS INNOVATIVE PARTICIPATION-ORIENTED PLANNING OF INFRASTRUCTURE MEASURES
Fusion of Multiple Gridded Biomass Datasets for Generating a Global Forest Aboveground Biomass Map
NMSTREAM: A SCALABLE EVENT-DRIVEN ETL FRAMEWORK FOR PROCESSING HETEROGENEOUS STREAMING DATA
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