Joint analysis of field and remote data in assessing the structure and composition of forests for the western part of Moscow regionстатья
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Дата последнего поиска статьи во внешних источниках: 11 ноября 2020 г.
Аннотация:For the test area in the central part of the Russian Plain (the western sector of Moscow re-gion), the results of a joint analysis of field research data, multispectral remote sensing data (MRSD) and a digital elevation model (DEM) are presented. An assessment of the organi-zation and coenotic diversity of the forest cover of the territory has been carried out. A total of 38 syntaxons with the rank of association groups were identified based on relevés, using the ecological-phytocoenotic approach. The overall quality of discrimination of the selected units according to the relevés and species cover was 84.5 %. The relief characteristics were considered one of the main factors of the natural differentiation of forest cover. The source of information about the altitudes of the territory was the SRTM v.3 data, for which the relief characteristics (slopes, curvatures, illuminances) of various levels of hierarchical organization were calculated. The quality of discrimination of syntaxons based on the relief characteristics was 49.6 %. Landsat 5 and 8 images, as well as indices calculated based on spectral bands, were used as remote sensing data. The quality of the discriminant analysis in this case was 49.8 %. The quality of discrimination carried out in a joint analysis of the characteristics of relief and MRSD amounted to 64.6 % of the originally defined syntaxons. Thus, the sharing of informa-tion about the relief and MRSD improved the separation of the selected classes by 15 %. The map of typological diversity of the vegetation cover for the studied territory was calculated, which characterizes the spatial structure and composition of the forest cover of the studied region. The main characteristics of the relief, which together define the conditions of habitat and, largely, differentiate the considered groups of associations in space, are highlighted. Keywords: MRSD, DEM, discriminant analysis, ground-based research, classification, typolo-gy of forests, mapping, forest cover, Moscow region.