Skip to Main Content
U.S. Forest Service
Caring for the land and serving people

United States Department of Agriculture

Home > Search > Publication Information

  1. Share via EmailShare on FacebookShare on LinkedInShare on Twitter
    Dislike this pubLike this pub
    Author(s): Robert Kennedy; Janet Ohmann; Matt Gregory; Heather Roberts; Zhiqiang Yang; David Bell; Van Kane; M Joseph Hughes; Warren Cohen; Scott Powell; Neeti Neeti; Tara Larrue; Sam Hooper; Jonathan Kane; David Miller; James Perkins; Justin Braaten; Rupert Seidl
    Date: 2018
    Source: Environmental Research Letters. 13(2): 025004-.
    Publication Series: Scientific Journal (JRNL)
    Station: Pacific Northwest Research Station
    PDF: Download Publication  (2.0 MB)


    The fate of live forest biomass is largely controlled by growth and disturbance processes, both natural and anthropogenic. Thus, biomass monitoring strategies must characterize both the biomass of the forests at a given point in time and the dynamic processes that change it. Here, we describe and test an empirical monitoring system designed to meet those needs. Our system uses a mix of field data, statistical modeling, remotely-sensed time-series imagery, and small-footprint lidar data to build and evaluate maps of forest biomass. It ascribes biomass change to specific change agents, and attempts to capture the impact of uncertainty in methodology. We find that:
    • A common image framework for biomass estimation and for change detection allows for consistent comparison of both state and change processes controlling biomass dynamics.
    • Regional estimates of total biomass agree well with those from plot data alone.
    • The system tracks biomass densities up to 450–500 Mg ha −1 with little bias, but begins underestimating true biomass as densities increase further.
    • Scale considerations are important. Estimates at the 30 m grain size are noisy, but agreement at broad scales is good. Further investigation to determine the appropriate scales is underway.
    • Uncertainty from methodological choices is evident, but much smaller than uncertainty based on choice of allometric equation used to estimate biomass from tree data.
    • In this forest-dominated study area, growth and loss processes largely balance in most years, with loss processes dominated by human removal through harvest. In years with substantial fire activity, however, overall biomass loss greatly outpaces growth. Taken together, our methods represent a unique combination of elements foundational to an operational landscape-scale forest biomass monitoring program.

    Publication Notes

    • Visit PNW's Publication Request Page to request a hard copy of this publication.
    • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.


    Kennedy, Robert E.; Ohmann, Janet; Gregory, Matt; Roberts, Heather; Yang, Zhiqiang; Bell, David M.; Kane, Van; Hughes, M Joseph; Cohen, Warren B.; Powell, Scott; Neeti, Neeti; Larrue, Tara; Hooper, Sam; Kane, Jonathan; Miller, David L.; Perkins, James; Braaten, Justin; Seidl, Rupert. 2018. An empirical, integrated forest biomass monitoring system. Environmental Research Letters. 13(2): 025004-.


    Google Scholar


    Forest biomass, Landsat, forest inventory, lidar, monitoring, disturbance.

    Related Search

    XML: View XML
Show More
Show Fewer
Jump to Top of Page