Integration of field sampling and LiDAR data in forest inventories: comparison of area-based approach and (lognormal) universal kriging

We compared (lognormal) universal kriging with the area-based approach for estimation of forest inventory variables using LiDAR data as auxiliary information and showed that could be an accurate alternative when there is spatial autocorrelation. Forest inventories supported by geospatial technologies are essential to achieve a spatially informed assessment structure. technology supplies comprehensive explicit enabling wide-scale variables. To compare stem density, basal area, quadratic mean diameter information. used from 202 plots, distributed in four Management Units differences structure management, 6-points/m2 resolution dataset Pinus sylvestris L. Spain test accuracy approaches. In those where analyzed autocorrelation, better results than terms RMSE Pearson coefficient between observed estimated values, although lognormal provided slightly biased estimations (up 2%). Universal method variable exhibiting