scholarly journals Woods with "Quercus petraea" (Matt.) Liebl. in Tuscany (Italy): a vegetation classification approach

2018 ◽  
Vol 39 (1) ◽  
Author(s):  
Daniele Viciani ◽  
Antonio Gabellini ◽  
Matilde Gennai ◽  
Bruno Foggi ◽  
Lorenzo Lastrucci
Keyword(s):  
Quercus Petraea ◽  
Vegetation Classification ◽  
Classification Approach

An overview of the vegetation classification approach in South Africa

2018 ◽  
Vol 48 (2) ◽  
pp. 163-170
Author(s):  
Leslie R. Brown ◽  
George J. Bredenkamp
Keyword(s):  
South Africa ◽  
Vegetation Classification ◽  
Classification Approach

The problem of the primary reduction of species in the analysis of general geobotanical tables and the elaboration of analytic programs

2001 ◽  
pp. 99-106 ◽  
Author(s):  
Yu. N. Neshatayev
Keyword(s):  
Vegetation Classification ◽  
Sample Plot ◽  
Herb Layer ◽  
Huge Amount ◽  
Species List ◽  
Community Types ◽  
Primary Reduction

If one processes a huge amount of data when es­tabli­shing the vegetation classification, it appears necessary to use the uniform algorithms of analysis. Such goals as distinguishing the reliable community types (associations or other syntaxa) involve the operational reduction of either the species list, or (more seldom) the sample plot set. This is especially useful for the analysis of multi­specific communities of meadows, steppes, or another types of markedly continuous polydominant vegetation with «fuzzy» structure of the herb layer.

Second International scientific conference «Vegetation of Eastern Europe and Northern Asia» (Bryansk, 12­–13 October 2020)

2020 ◽  
pp. 149-153
Author(s):  
V. V. Neshataev ◽  
D. D. Karsonova ◽  
A. A. Kurka
Keyword(s):  
Eastern Europe ◽  
Vegetation Classification ◽  
Scientific Conference ◽  
State University ◽  
Research Projects ◽  
Joint Research ◽  
Northern Asia ◽  
Oral Presentations ◽  
Made In ◽  
Second International

On October 12th and 13th, 2020, Bryansk State University held an international scientific online conference "Vegetation of Eastern Europe and Northern Asia". The Proceedings of abstracts includes 66 reports by 118 authors and co-authors from 5 countries, 34 localities and 51 organizations. During the meeting, 41 oral presentations were made. In conclusion, it was noted that it is necessary to promote an integration of geobotanists and florists from different regions in order to implement joint research projects. In particular, this concerns a project of making a vegetation classification in Russia.

Second international scientific conference «Present fundamental problems of vegetation classification» (Yalta, 15–20 September 2019)

2019 ◽  
pp. 135-142
Author(s):  
K. V. Ivanova ◽  
A. M. Lapina ◽  
V. V. Neshataev
Keyword(s):  
Plant Communities ◽  
National Archive ◽  
Botanical Garden ◽  
Vegetation Classification ◽  
Scientific Conference ◽  
Scientific Journals ◽  
Time Dynamics ◽  
The Past ◽  
Research Organizations

The 2nd international scientific conference «Fundamental problems of vegetation classification» took place at the Nikitskiy Botanical Garden (Yalta, Republic of Crimea, Russia) on 15–20 September 2019. There were 56 participants from 33 cities and 43 research organizations in Russia. The conference was mostly focused on reviewing the success in classification of the vegetation done by Russian scientists in the past three years. The reports covered various topics such as classification, description of new syntaxonomical units, geobotanical mapping for different territories and types of vegetation, studies of space-time dynamics of plant communities. The final discussion on the last day covered problems yet to be solved: establishment of the Russian Prodromus and the National archive of vegetation, complications of higher education in the profile of geobotany, and the issue of the data leakage to foreign scientific journals. In conclusion, it was announced that the 3rd conference in Nikitskiy Botanical Garden will be held in 2022.

DRSA: a non-hierarchical clustering algorithm using k-NN graph and its application in vegetation classification

2015 ◽  
pp. 125-138 ◽  
Author(s):  
I. V. Goncharenko
Keyword(s):  
Cluster Analysis ◽  
Clustering Algorithm ◽  
Nearest Neighbor ◽  
Clustering Algorithms ◽  
Protein Structures ◽  
Hierarchical Cluster ◽  
Vegetation Classification ◽  
K Nearest Neighbor ◽  
Neighbor Graph ◽  
Nearest Neighbor Graph

In this article we proposed a new method of non-hierarchical cluster analysis using k-nearest-neighbor graph and discussed it with respect to vegetation classification. The method of k-nearest neighbor (k-NN) classification was originally developed in 1951 (Fix, Hodges, 1951). Later a term “k-NN graph” and a few algorithms of k-NN clustering appeared (Cover, Hart, 1967; Brito et al., 1997). In biology k-NN is used in analysis of protein structures and genome sequences. Most of k-NN clustering algorithms build «excessive» graph firstly, so called hypergraph, and then truncate it to subgraphs, just partitioning and coarsening hypergraph. We developed other strategy, the “upward” clustering in forming (assembling consequentially) one cluster after the other. Until today graph-based cluster analysis has not been considered concerning classification of vegetation datasets.

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