Multiscale divergence between Landsat- and lidar-based biomass mapping is related to regional variation in canopy cover and composition
2018
Background Satellite-based aboveground forest biomass maps commonly form the basis of forest biomass and carbon stock mapping and monitoring, but biomass maps likely vary in performance by region and as a function of spatial scale of aggregation. Assessing such variability is not possible with spatially-sparse vegetation plot networks. In the current study, our objective was to determine whether high-resolution lidar-based and moderate-resolution Landsat-base aboveground live forest biomass maps converged on similar predictions at stand- to landscape-levels (10 s to 100 s ha) and whether such differences depended on biophysical setting. Specifically, we examined
deviationsbetween lidar- and Landsat-based biomass mapping methods across scales and
ecoregionsusing a measure of error (normalized
root mean square deviation), a measure of the unsystematic
deviations, or noise (Pearson correlation coefficient), and two measures related to systematic
deviations, or biases (intercept and slope of a regression between the two sets of predictions).
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