Tree species identification is important for a variety of natural resource management and monitoring activities especially in forest inventory. The objective of research is to identify tree species using digital aerial photography and LIDAR data in Latvian forest conditions. The study outlines a number of tree species identification possibilities: the ability to identify conifers and deciduous trees; the ability to identify pine and spruce; the ability to identify birch, aspen and black alder. The study site is a forest in the middle part of Latvia at Jelgava district (56º39’ N, 23º47’ E). Aerial photography camera (ADS 40) and laser scanner (ALS 50 II) were used to capture the data. LIDAR resolution is 9 points m-2 (500 m altitude). The image data is RGB, NIR and PAN spectrum with 20 cm pixel resolution. During the study a modified region growing algorithm was developed to determine tree canopy and tree species identification using threshold segmentation, Fourier transform, frequency filtering and reverse Fourier transform. Tree species classification of coniferous and deciduous trees is possible in 82% of the cases; the first storey of the trees can be classified correctly in 96% of the cases, but the second storey of the trees only in 49% of the cases. Spruce identification is possible in 81.1% of the cases, for first storey trees in 89.6% of the cases and for the second storey trees in 72.9% of cases. Deciduous tree correct classification is possible in 63% of the cases, birch 75%, black alder 60% and aspen only in 41% of the cases.

This brief review of the recent birch studies is focused on different aspects, such as species distribution, growing conditions, species identification, changes due to environmental factors. All mentioned investigations were carried out in Lithuania. This analytical study summarises the results and increases knowledge dissemination to the international audience. When reviewed and summarized considerable part of relevant literature sources, we realised new problems and challenges; for example, aiming to clarify the peculiarities of the growth and crown condition of the dominant birch species (Betula pendula Roth. and B. pubescens Ehrh.) under the changing climate and anthropogenic pollution.

The aim of the study was to compare weed species diversity in organic and conventional farms in Poland. The study was carried out between 2012 and 2014 on production fields located in Lublin province, one of the easternmost regions of Poland. The results showed that diversity and abundance of weeds in spring cereals were generally higher in organic farming system than in conventional one. No significant differences between systems were found in 2013, because local flooding of fields in spring made impossible the execution of agricultural weed management treatment for some farmers. Both above-ground and soil seed bank weed communities were the mainstay of valuable weed species, which is confirmed by the presence of the species threatened with extinction, for example, summer pheasant’s-eye (Adonis aestivalis), poorman’s blue weatherglass (Anagallis foemina) and others in both tested farming systems. Dwarf everlast (Helichrysum arenarium) was the only found species that is subject to partial protection by Polish law. Both organic farms, run under CAP policy and support, and conventional extensive farms of the province of Lublin were the mainstay of biodiversity. Future rural development and CAP should be adapted and implemented regionally. Traditional extensive farms could contribute to the biodiversity and valuable plant species conservation.

One of the most challenging issues in forest inventory based on remote sensing data is identification of tree species. Hyperspectral remote sensing data provides information which considerably facilitates tree species recognition. The objective of the research is to evaluate different hyperspectral data analysis methods to classify tree species in Latvian forest conditions. The study site is a forest in the central part of Latvia, Jelgava district (56º39’ N, 23º47’ E). The area consists of a mixed coniferous and deciduous forest. During research 598 trees were analyzed in 70 sample plots. Remote sensing data are 64 hyperspectral bands in the 400 - 970 nm spectral range. Two different classification techniques: linear discriminant analysis (LDA) and artificial neural networks (ANNs) were used. In LDA species classification was done by stepwise and using principal components of hyperspectral bands. In stepwise LDA 18 hyperspectral bands were used. LDA using principal components and ANNs used all 64 hyperspectral bands. The best results show stepwise LDA where 82.4% of the data were correctly classified. Scots pine was classified 94.8%, Norway spruce 83.5%, Silver birch 77%, European aspen 71.4% and Black alder 56.3%. Classification with ANN’s best results showed for Scots pine, Norway spruce and Silver birch – respectively 81%, 84%, 86%. With LDA using principal components Scots pine’s classification showed best results with 85.1% correctly classified trees.

Only less than one percent of the territory of Latvia is occupied by broadleaved (trees having relatively wide flat leaves) forests. The aim of the research is to assess forest vegetation in the island of Upursala of Cirišs Lake. The data is collected in four forest areas of the island. Totally 12 plots, each with an area of 200 m² (20 x 20 m) have been created. In each plot, the accounting of growing trees and deadwood is carried out. The vegetation is measured in each forest area – the projective vegetation cover and cover of each plant species by tree, shrub, herb and moss layer are determined. The research founds that the average stock of growing trees on the island of Upursala is 565.8 m³ ha⁻¹. The average amount of dead wood is 108 m³ ha⁻¹, it consists mainly of fallen deadwood. Totally 45 species are listed in the vegetation plots, of which seven are determinants of European broadleaved forests. The largest number of determinant species of European broadleaved forests has been observed in stands with mixed forests (aspen – small-leaved lime – pedunculate oak, aspen – Scots pine – pedunculate oak and Scots pine – Silver birch – aspen). It can be argued that these stands will become the European broadleaved forests in the future.