This study addresses the use of multiple sources of auxiliary data from unmanned aerial vehicles (UAVs) and airborne laser scanning (ALS) data for inference on key biophysical parameters in small forest properties (5–300 ha). We compared the precision of the estimates using plot data alone under a design-based inference with model-based estimates that include plot data and the following four types of auxiliary data: (1) terrain-independent variables from UAV photogrammetric data (UAV-SfM); (2) variables obtained from UAV photogrammetric data normalized using external terrain data (UAV-SfMDTM); (3) UAV-LS and (4) ALS data. The inclusion of remotely sensed data increased the precision of DB estimates by factors of 1.5–2.2. The optimal data sources for top height, stem density, basal area and total stem volume were: UAV-LS, UAV-SfM, UAV-SfMDTM and UAV-SfMDTM. We conclude that the use of UAV data can increase the precision of stand-level estimates even under intensive field sampling conditions.

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