Structure-based forest biomass from fusion of radar and hyperspectral observations

Robert N. Treuhaft, Gregory P. Asner, Beverly E. Law

Research output: Contribution to journalArticle

41 Scopus citations

Abstract

Forest biomass was estimated from the remotely sensed profiles of leaf area density. Biomass estimated from forest structure profiles may be more accurate than that determined from microwave power or optical radiance measurements. Multialtitude, airborne, C-band, radar interferometry produced relative density profiles, which were normalized by leaf area indices from airborne hyperspectral optical imagery, yielding the forest canopy leaf area density for 11 structurally diverse stands in Central Oregon. Fits of field biomass measurements to model functions of remotely sensed leaf area density produced agreement between the field and remotely sensed biomasses at the level of 25 tons/ha, or 16% of the average stand biomass. The errors in the field and remote sensing observations indicated that this level of agreement was significant with greater than 99.5% confidence. These results suggest that further demonstrations may lead to a set of model functions that enable global, structure-based biomass remote sensing.

Original languageEnglish (US)
Pages (from-to)25-1 - 25-4
JournalGeophysical Research Letters
Volume30
Issue number9
DOIs
StatePublished - May 1 2003
Externally publishedYes

ASJC Scopus subject areas

  • Geophysics
  • Earth and Planetary Sciences(all)

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