Identification of the Leaves of Ulmus pumila L., Tilia cordata Mill. and Acer campestre L. Using Vegetation Indices

Abstract

The aim of the research was to evaluate a group of vegetation indices (VIs) for identifying the leaves of some species including Ulmus pumila L., Tilia cordata Mill. and Acer campestre L. Hyperspectral imaging (HSI) was carried out under artificial lighting in laboratory conditions using a Cubert UHD-185 hyperspectral camera. A technique was developed for the automated selection of pure spectral profiles from hyperspectral images by setting a double barrier specified by intervals of PSSR and NDVI VIs. A total of 80 VIs was calculated. A statistical analysis of the data was carried out to determine their representativeness. The VIs that were most dependent on the species characteristics of the trees were determined using analysis of variance (ANOVA) and principal component analysis (PCA) methods. Research has shown that the PCA method is effective and sufficient to identify the group of VIs characterized by the highest dispersion related to tree species. The PCA carried out for pairs of tree species made it possible to identify a group of vegetation indices, the value of which to the greatest extent depends on species characteristics. These VIs are Carter2, CI2, CRI4, GMI2, mSR2, NDVI2, OSAVI2, SR1, Carter4, Datt2, SR6, Datt, DD, Maccioni, MTC.