Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska

Lei Ji, Bruce K. Wylie, Dana R.N. Brown, Birgit Peterson, Heather D. Alexander, Michelle C. Mack, Jennifer Rover, Mark P. Waldrop, Jack W. McFarland, Xuexia Chen, Neal J. Pastick

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composite of top-of-atmosphere reflectance for six bands as well as the brightness temperature (BT). We constructed a multiple regression model using field-observed AGB and Landsat-derived reflectance, BT, and vegetation indices. A basin-wide boreal forest AGB map at 30 m resolution was generated by applying the regression model to the Landsat composite. The fivefold cross-validation with field measurements had a mean absolute error (MAE) of 25.7 Mg ha−1 (relative MAE 47.5%) and a mean bias error (MBE) of 4.3 Mg ha−1 (relative MBE 7.9%). The boreal forest AGB product was compared with lidar-based vegetation height data; the comparison indicated that there was a significant correlation between the two data sets.

Original languageEnglish (US)
Pages (from-to)939-953
Number of pages15
JournalInternational Journal of Remote Sensing
Volume36
Issue number4
DOIs
StatePublished - Feb 16 2015
Externally publishedYes

ASJC Scopus subject areas

  • General Earth and Planetary Sciences

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