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Using remote sensing to quantify the additional climate benefits of California forest carbon offset projects

Cite this dataset

Coffield, Shane (2022). Using remote sensing to quantify the additional climate benefits of California forest carbon offset projects [Dataset]. Dryad.


Nature-based climate solutions are a vital component of many climate mitigation strategies, including California’s, which aims to achieve carbon neutrality by 2045. Most carbon offsets in California’s cap-and-trade program come from improved forest management projects (IFMs). Since 2012, various landowners have set up IFMs following the California Air Resources Board’s IFM protocol. As many of these projects approach their tenth year, we now have the opportunity to assess their effectiveness, identify best practices, and suggest improvements toward future protocol revisions. In this study, we used remote sensing-based datasets to evaluate the carbon trends and harvest histories of 37 IFMs in California. Despite some current limitations and biases, these datasets can be used to quantify carbon accumulation and harvest rates in offset project lands relative to nearby similar “control” lands before and after the projects began. Five lines of evidence suggest that the carbon accumulated in offset projects to date has generally not been additional to what might have otherwise occurred: (1) most forests in northwestern California have been accumulating carbon since at least the mid-1980s and continue to accumulate carbon, whether enrolled in offset projects or not; (2) harvest rates were high in large timber company project lands before IFM initiation, suggesting they are earning carbon credits for forests in recovery; (3) projects are often located on lands with higher densities of low-timber-value species; (4) carbon accumulation rates have not yet increased on lands that enroll as offset projects, relative to their pre-enrollment levels; and (5) harvest rates have not decreased on most project lands since offset project initiation. These patterns suggest that the current protocol should be improved to robustly measure and reward additionality. In general, our framework of geospatial analyses offers an important and independent means to evaluate the effectiveness of the carbon offsets program, especially as these data products continue improving and as offsets receive attention as a climate mitigation strategy.


Data are compiled from a variety of sources in the public domain, detailed in the readme.docx. We assemble geospatial datasets for remote-sensing-estimated carbon and harvest in Google Earth Engine, extract for regions of interest (California offset projects and control regions), and generate figures comparing these datasets in Python. See "Methods" section of paper for details. 

Usage notes

Google Earth Engine

Python v3

Code also available on GitHub:


National Science Foundation, Award: DGE-1839285

National Science Foundation, Award: 2044937

National Science Foundation, Award: 1802880

National Science Foundation, Award: 2003017

David and Lucile Packard Foundation

UCOP National Laboratory Fees Research Program, Award: LFR-18-542511

U.S. Department of Agriculture, Award: NIFA AFRI 2018‐67019‐27850

California Strategic Growth Council's Climate Change Research Program