Laboratory measurement of forest-vegetation reflectance spectra in the European part of the Russian Federation for the 1–2.4 µm range

Subject of study. The reflectance spectra of leaves and needles from woody vegetation were measured and analyzed within the spectral range of 1–2.4 µm. Aim of study. The study aims to explore the potential of hyperspectral measurements of forest-vegetation reflectance spectra (1–2.4 µm) for forestry applications in the Russian Federation. Method. Laboratory measurements were conducted on the reflectance spectra of leaves and needles from woody vegetation representative of the European part of the Russian Federation. The experimental setup included a spectrometer for capturing reflectance spectra within the 1–2.4 µm range. Specimens comprised green spruce, pine, birch, oak, maple, aspen, and linden, representing coniferous and deciduous vegetation. Measurements took place in summer (August) at a Bauman Moscow State Technical University branch in the Dmitrov district of Moscow. Main results. The results reveal that the reflectance spectra in the 1–2.4 µm range facilitate the differentiation between coniferous and deciduous tree species and the classification of forest vegetation. Reliable spectral separation between coniferous and deciduous species was observed in the ranges of 1.5–1.8 µm and 2.1–2.4 µm. Reflectance spectra in the range of 1–2.4 µm with a 10 nm resolution enabled effective classification of birch, oak, maple, linden, aspen, spruce, and pine, with at least 88% accuracy for each species. Practical significance. This research lays the groundwork for developing a spectral-reflectivity database of woody vegetation typical of forested regions in the Russian Federation. Hyperspectral data in the 1–2.4 µm range can support tree species identification, assess tree health, detect disease, monitor drying processes, and enhance remote forest inventory methods.