TreeMap: A tree-level model of United States forests
Researchers used machine learning to pair forest plot data with biophysical characteristics of the landscape to produce a seamless tree-level forest map.
The TreeMap dataset is a spatial model of the trees in forests of the United States. It provides detailed spatial information on forest characteristics including a list of trees for each pixel (with tree species, DBH, height, and live or dead status), and summary information for each pixel including forest type, number of live and dead trees, biomass, and carbon. TreeMap covers the entire forested extent of the conterminous United States at 30 x 30 meter resolution, enabling analyses at fine scales. Inputs to TreeMap include detailed forest plot data measured by Forest Inventory and Analysis (FIA), national gridded maps of forest cover, height, and vegetation type provided by the LANDFIRE project, and climatic variables from Daymet. TreeMap includes disturbance as a response variable, resulting in increased accuracy in mapping disturbed areas.
Using random forests (a type of machine learning algorithm) we match the forest plot data to the gridded vegetation maps, producing a seamless model of the trees of the forests of the U.S. Specifically, the result is a map of plot ID numbers, which identify the best-matching forest plot for each 30x30 pixel in the map. The map of plot ID numbers can be linked back to the FIA databases to generate maps of any number of forest characteristics, ranging from basal area to biomass to species types.
Some current uses of the dataset include estimation of:
- Forest carbon
- Wildfire risk to forest carbon
- Volume of harvestable wood generated by fuel treatments
- Hydrologic effects of fuel treatments
Principal Investigator: Karin Riley
Read more about TreeMap and how to use it, or explore and download the data at the following links:
TreeMap Fact Sheet TreeMap Explorer
TreeMap 2016 Download TreeMap 2020 Download TreeMap 2022 Download
Top Image: Plot identifiers for a subset of the Mogollon Rim of Arizona. Each unique color corresponds to a different plot. Bottom Image: Live tree carbon for the same subset of the Mogollon Rim.
Online Resources
Multimedia
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Webinarshttps://research.fs.usda.gov/firelab/products/multimedia/webinars/mapping-live-and-dead-trees-fire-responder-hazard-carbon-and
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Webinarshttps://research.fs.usda.gov/firelab/products/multimedia/webinars/treemap-and-fuelmap
TreeMap Fact Sheet
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Fact Sheet
https://research.fs.usda.gov/rmrs/understory/treemap-glance
Publications
- Karin Riley, Isaac C. Grenfell, Mark A. Finney, Jason M. Wiener. 2021. TreeMap, a tree-level model of conterminous US forests circa 2014 produced by imputation of FIA plot data
- Karin Riley, Isaac C. Grenfell, Mark A. Finney, Nicholas L. Crookston. 2014. Utilizing random forests imputation of forest plot data for landscape-level wildfire analyses
- Karin Riley, Isaac C. Grenfell, Mark A. Finney. 2016. Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots
- Karin Riley, Isaac C. Grenfell, John D. Shaw, Mark A. Finney. 2022. TreeMap 2016 dataset generates CONUS-wide maps of forest characteristics including live basal area, aboveground carbon, and number of trees per acre
- Karin Riley, Christopher D. O'Connor, Christopher J. Dunn, Jessica R. Haas, Richard D. Stratton, Benjamin Gannon. 2022. A national map of snag hazard to reduce risk to wildland fire responders
Related Datasets and Tools
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Model
https://research.fs.usda.gov/rmrs/products/dataandtools/national-snag-hazard-map -
Tool
https://research.fs.usda.gov/products/dataandtools/fia-datamart
Principal Investigators
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Person
Karin Riley, PhD
Research Ecologisthttps://research.fs.usda.gov/about/people/karin.l.riley -
Person
Mark A. Finney, PhD
Research Foresterhttps://research.fs.usda.gov/about/people/mark.finney -
Person
John D. Shaw, PhD
Biological Scientisthttps://research.fs.usda.gov/about/people/john.d.shaw -
Person
Isaac C. Grenfell
Mathematical Statisticianhttps://research.fs.usda.gov/about/people/isaac.c.grenfell -
Forest Service
Rachel Houtman
Biological Scientistmailto: Rachel.Houtman@usda.gov -
Person
Scott Zimmer
Biological Scientisthttps://research.fs.usda.gov/about/people/scott.zimmer -
RedCastle Resources, Inc.
Lila Leatherman
Geospatial Data Scientisthttps://www.redcastleresources.com/
Research Collaborators
Jason Wiener, University of Montana
Related Programs
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Program
https://research.fs.usda.gov/programs/fia
Previous Versions of TreeMap
Riley, Karin L., Isaac C. Grenfell, Mark A. Finney, Jason M. Wiener, and Rachel M. Houtman. 2019. Fire Lab tree list: A tree-level model of the conterminous United States landscape circa 2014. Fort Collins, CO: Forest Service Research Data Archive.
Karin L. Riley, Isaac C. Grenfell, Mark A. Finney, Jason M. Wiener. 2018. Fire Lab tree list: A tree-level model of the western US circa 2009 v1. Fort Collins, CO: Forest Service Research Data Archive.
Conference Presentations
Riley, Karin L., Isaac C. Grenfell, John D. Shaw, and Mark A. Finney. 2021. TreeMap lays foundation for analysis of risk to terrestrial carbon from wildland fire and fuel treatment. Association for Fire Ecology, 9th International Fire Ecology and Management Congress: November 30 - December 3, 2021, Virtual.
Riley, Karin L., Isaac C. Grenfell, Mark A. Finney. 2018. Mapping forest vegetation and biomass for the continental United States using modified random forests imputation of FIA forest plots. Society for Ecological Restoration and Society of Wetland Scientists, Restoring Resilient Communities in Changing Landscapes: October 15-18, 2018, Spokane, Washington.
Riley, Karin L., Isaac C. Grenfell, Mark A. Finney, and Nicholas L. Crookston. 2014. Utilizing random forests imputation of forest plot data for landscape-level wildfire analyses. VII International Conference on Forest Fire Research. Associacao para o Desenvolvimento da Aerodinamica Industrial. November 17-20, 2014, Coimbra, Portugal.
Riley, Karin L., Isaac Grenfell, and Nicholas Crookston. 2014. Random forests imputation of forest plot data for landscape-level analyses. 2014 Society of American Foresters National Convention. Society of American Foresters. October 9-11, 2014, Salt Lake City, Utah.
Riley, Karin L., Isaac C. Grenfell, Mark A. Finney, Alan A. Ager, and Nicholas L. Crookston. 2012. Random Forests imputation of forest plot data for landscape-level wildfire analyses. Association for Fire Ecology 5th Fire Ecology Congress: Uniting Research, Education, and Management. December 3-7, 2012, Portland, Oregon.