Assessing the success of forest crops using UAVs

¹ Petrozavodsk State University, 185910 Petrozavodsk, Russia
² St. Petersburg State Forest Engineering University, 1194018, St. Petersburg, Russia

^* Corresponding author: alexkabonen@mail.ru

Abstract

The article presents data on the growth and development of 22-year-old forest crops created by sowing and planting seedlings with a closed root system on the territory of the Republic of Karelia (Russia). Field surveys showed that young forests with a predominance of Pinus sylvestris were formed in all experimental plots. The share of forest plantations on the plots in terms of timber stock amounted to 38 - 44% of the total stock. The UAV data processing method made it possible to build an orthophotomap of the area and calculate the quantitative distribution of tree species: 60% (plots without tillage) -80% (plots with tillage) - Pinus sylvestris, 10% - 22% - betula pendula. These indicators are consistent with the field survey of the area (differences less than 10%). As a result of running the algorithm for automatically searching for trees using point clouds using the lidR package, it was possible to detect about 90% of trees in all areas and determine their heights. At the same time, most of the trees (85%) found by the algorithm were identified correctly. The number of false positives and the number of missing trees were quite low, and the weighted average quality score was 0.89, which indicates a high efficiency of tree search. The heights measured from the UAV data were in good agreement with the heights measured by the ground method.