Applying terrestrial lidar for evaluation and calibration of airborne lidar-derived shrub biomass estimates in Arctic tundra
Monitoring of climate-driven expansion of low-stature shrubs in Arctic tundra can be improved through application of high-resolution remote sensing. However, the destructive nature of harvest sampling that is usually performed for validation of these data is resource intensive and can limit future comparisons by destroying benchmark measurements. We compared aboveground shrub biomass estimates derived from terrestrial laser scanning (TLS) and airborne laser scanning (ALS) with the goal of determining whether TLS data can be used to accurately calibrate ALS estimates of shrub biomass in Arctic tundra. We used a leave-one-out cross-validation calibration of canopy volume against harvested shrub biomass to establish predictive relationships between TLS canopy volume and harvested shrub biomass, and between ALS canopy volume and TLS-derived shrub biomass estimates. TLS produced more accurate predictions of shrub biomass (R2 = 0.78; root mean square deviation [RMSD] = 102 g) than did ALS, but the accuracy of ALS-derived shrub biomass predictions was the same whether they were calibrated directly against harvest biomass or against TLS-derived estimates of biomass (R2 = 0.62; RMSD = 140 g). Our results suggest that once the initial TLS-harvest relationship is known, TLS can provide valid ground reference data for calibration of ALS-derived estimates of shrub biomass without the need for additional destructive harvest.