Abstract
The objective of this study was to assess the use of unmanned aerial vehicle (UAV) data for modelling tree density and canopy height in young boreal forests stands. The use of UAV data for such tasks can be beneficial thanks to the high resolution and reduction of the time spent in the field. This study included 29 forest stands, within which 580 clustered plots were measured in the field. An area-based approach was adopted to which random forest models were fitted using the plot data and the corresponding UAV data and then applied and validated at plot and stand level. The results were compared to those of models based on airborne laser scanning (ALS) data and those from a traditional field-assessment. The models based on UAV data showed the smallest stand-level R M S E values for mean height (0.56 m) and tree density (1175 trees ha−1). The R M S E of the tree density using UAV data was 50% smaller than what was obtained using ALS data (2355 trees ha−1). Overall, this study highlighted that the use of UAVs for the inventory of forest stands under regeneration can be beneficial both because of the high accuracy of the derived data analytics and the time saving compared to traditional field assessments.
Highlights
The digital surface model (DSM) variables were more important for N and Nc while the normalized point cloud-variables proved to be more important in modelling Hm and height of crop trees (Hc)
The objective of this study was to assess whether unmanned aerial vehicle (UAV) data can be used to model relevant biophysical forest variables in stands under regeneration
This study demonstrated that the use of UAV data provided more accurate predictions than an airborne laser scanning (ALS) data or field assessments, with a reduction in the relative root mean square error (RMSE) of 50% for stem density compared to ALS data
Summary
A key aspect in modern precision forestry practices is to ensure updated and reliable information. This is especially true when the forest structure is changing rapidly because of rapid growth such as in the young stages of stand development. Within the context of this study we refer to forest stands under regeneration as stands that have been harvested and where the tree generation is regenerated either through planting or through natural seed dispersal, and where the dominant trees have not yet reached merchantable size (i.e., stands in maturity class II sensu ; Antón-Fernández and Astrup [1]). Current operational FMI methods do not sufficiently capture reliable information on biophysical forest properties in stands under regeneration. The use of unmanned aerial vehicles (UAVs) in forest inventory has proven to produce accurate results both for small-scale forest management inventories [3,4,5,6,7] as well as for large-scale forest inventories [8,9]
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