UAV data collection parameters impact on accuracy of Scots pine stand mensuration

Abstract

A wide range of UAV systems used for forest research requires unified approaches to data collection. The research aims to determine the optimal parameters for UAV data collection to obtain accurate information about stands, considering the cost of resources for its collection. The process of collecting remote sensing data consisted of nine combinations divided into three levels of overlap and three levels of spatial resolution (survey altitude) and changing the degree of filtering of a dense point cloud during image processing. Individual tree detectingin the stand was performed using the R programming language and the ForestTools package. The results of the assessment of the dependence of the radius of tree crowns on their height were used to set the parameters of the variable filter function for finding local maxima for Scots pine stands. Errors in the identification of treetops were estimated using the F-score. The identified heights were compared with the field data of the ground survey. The proportion of classified digital elevation model DEM in the dense point cloud was reduced from the total area of the test site using images of 4.1 cm/pix spatial resolution (150 m survey altitude). The study presents the results of assessing the impact of spatial resolution of optical images collected from UAVs and their overlap on the results of measurements of stands parameters. It is determined that a photogrammetric survey with input images with a longitudinal overlap of less than 90% is not appropriate for the study of forest areas due to the impossibility of aligning all images. The results of the assessment of tree accounting in the stand showed that it is most appropriate to use images with a spatial resolution of up to 3.3 cm/pix (120 m survey altitude), otherwise, the proportion of missed treetops increases. Reducing the spatial resolution of remote sensing data leads to an increase in errors in determining the height of individual trees, and the average heights of the experimental plots had the same trend. Given the combination of the assessed factors, it is not recommended to use images with a spatial resolution of more than 3.3 cm/pix for forestry research due to increased errors in the individual tree detection and tree height determination. The results obtained can be used to select data collection parameters for research on Scots pine stands to assess their growing stock and phytomass