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Integrating LIDAR and forest inventories to fill the trees outside forests data gap

Environmental Monitoring and Assessment volume 187, Article number: 623 (2015) Cite this article

Abstract

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data. An ideal approach to fill this data gap would be to integrate TOF measurements within a traditional forest inventory for a parsimonious estimate of total tree biomass. In this study, Light Detection and Ranging (LIDAR) data were used to predict biomass of TOF in all “nonforest” Forest Inventory and Analysis (FIA) plots in the state of Maryland. To validate the LIDAR-based biomass predictions, a field crew was sent to measure TOF on nonforest plots in three Maryland counties, revealing close agreement at both the plot and county scales between the two estimates. Total tree biomass in Maryland increased by 25.5 Tg, or 15.6 %, when biomass of TOF were included. In two counties (Carroll and Howard), there was a 47 % increase. In contrast, counties located further away from the interstate highway corridor showed only a modest increase in biomass when TOF were added because nonforest conditions were less common in those areas. The advantage of this approach for estimating biomass of TOF is that it is compatible with, and explicitly separates TOF biomass from, forest biomass already measured by FIA crews. By predicting biomass of TOF at actual FIA plots, this approach is directly compatible with traditionally reported FIA forest biomass, providing a framework for other states to follow, and should improve carbon reporting and modeling activities in Maryland.

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Acknowledgments

David Bruhn and Kathleen Kranich were responsible for all the field work involved in the validation component of the study and supported additional office and data entry work. Matthew Patterson and Thomas Willard provided training to the field crew. Cassandra Olson, James Blehm, and Robert Ilgenfritz provided FIA plot information and valuable guidance. Two internal reviews by Lara Roman and Grant Domke provided valuable feedback to improve the manuscript. This project was supported by NASA grant N4-CMS14-0037 (Dubayah, principal investigator).

Conflict of interest

The authors declare that they have no competing interests.

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Affiliations

  1. USDA Forest Service, Northern Research Station, 11 Campus Blvd Ste 200, Newtown Square, PA, 19073, USA

    Kristofer D. Johnson, Richard Birdsey, Jason Cole & Andrew Lister

  2. Department of Geographical Sciences, University of Maryland, 2181 LeFrak Hall, College Park, MD, 20740, USA

    Anu Swatantran & Ralph Dubayah

  3. Spatial Analysis Laboratory, University of Vermont, 205 George D. Aiken Center, Burlington, VT, 05405, USA

    Jarlath O’Neil-Dunne

Authors
  1. Kristofer D. Johnson
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  2. Richard Birdsey
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  3. Jason Cole
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  4. Anu Swatantran
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  5. Jarlath O’Neil-Dunne
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  6. Ralph Dubayah
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  7. Andrew Lister
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Correspondence to Kristofer D. Johnson.

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Johnson, K.D., Birdsey, R., Cole, J. et al. Integrating LIDAR and forest inventories to fill the trees outside forests data gap. Environ Monit Assess 187, 623 (2015). https://doi.org/10.1007/s10661-015-4839-1

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  • DOI: https://doi.org/10.1007/s10661-015-4839-1

Keywords

  • Trees outside forest
  • Carbon management
  • Nonforest biomass
  • LIDAR
  • Forest inventory