scholarly journals Classification of trees and tree species in Obrenovac “Mali park” by the elements of growth, vitality and ornamentalness

2010 ◽  
Vol 62 (4) ◽  
pp. 1119-1124 ◽  
Author(s):  
N. Stavretovic ◽  
M. Vuckovic ◽  
B. Stajic
Keyword(s):  
Tree Species ◽  
Juglans Regia ◽  
Platanus Acerifolia ◽  
Homogeneous Groups ◽  
Tree Vitality ◽  
Direct Measurements ◽  
Betula Verrucosa ◽  
The Town ◽  
Celtis Australis

The study was performed in Mali Park, in the town of Obrenovac. Our findings are based on the data obtained after direct measurements of elements of growth and the derived indicators of tree vitality and ornamentalness. Cluster analysis was applied to determine the relatively homogeneous groups of tree species. The results show that the group with the best functional characteristics includes Platanus acerifolia, Tilia grandifolia and Fraxinus ornus, and the group of species with inferior characteristics includes Betula verrucosa, Juglans regia, Celtis australis, Acer platanoides, Cedrus atlantica and Acer negundo.

scholarly journals Geometric and Topological Bases of a New Classification of Wood Vascular Tissues Part 1: Shape and Arrangement Classifications of Vessels

2021 ◽  
Vol 13 (14) ◽  
pp. 7545
Author(s):  
Nikolai Bardarov ◽  
Vladislav Todorov ◽  
Nicole Christoff
Keyword(s):  
Computer Vision ◽  
Detailed Analysis ◽  
Tree Species ◽  
Complete Solution ◽  
New Classification ◽  
Topological Characteristics ◽  
Definition Of ◽  
Wood Science ◽  
Quantitative Indicators

The need to identify wood by its anatomical features requires a detailed analysis of all the elements that make it up. This is a significant problem of structural wood science, the most general and complete solution of which is yet to be sought. In recent years, increasing attention has been paid to the use of computer vision methods to automate processes such as the detection, identification, and classification of different tissues and different tree species. The more successful use of these methods in wood anatomy requires a more precise and comprehensive definition of the anatomical elements, according to their geometric and topological characteristics. In this article, we conduct a detailed analysis of the limits of variation of the location and grouping of vessels in the observed microscopic samples. The present development offers criteria and quantitative indicators for defining the terms shape, location, and group of wood tissues. It is proposed to differentiate the quantitative indicators of the vessels depending on their geometric and topological characteristics. Thus, with the help of computer vision technics, it will be possible to establish topological characteristics of wood vessels, the extraction of which would be used to develop an algorithm for the automatic classification of tree species.

Impact of atmospheric correction and image filtering on hyperspectral classification of tree species using support vector machine

2015 ◽  
Vol 9 (1) ◽  
pp. 095990 ◽  
Author(s):  
Morteza Shahriari Nia ◽  
Daisy Zhe Wang ◽  
Stephanie Ann Bohlman ◽  
Paul Gader ◽  
Sarah J. Graves ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Tree Species ◽  
Atmospheric Correction ◽  
Image Filtering ◽  
Support Vector ◽  
Hyperspectral Classification

Kraepelin revisited: a reassessment and statistical analysis of dementia praecox and manic-depressive insanity in 1908

1993 ◽  
Vol 23 (4) ◽  
pp. 843-858 ◽  
Author(s):  
A. Jablensky ◽  
H. Hugler ◽  
M. Von Cranach ◽  
K. Kalinov
Keyword(s):  
Meta Analysis ◽  
Original Data ◽  
Dementia Praecox ◽  
Schizoaffective Disorders ◽  
Homogeneous Groups ◽  
Manic Depressive ◽  
Original Case ◽  
State Examination ◽  
Dichotomous Classification

SynopsisA meta-analysis was carried out on 53 cases of dementia praecox (DP) and 134 cases of manic-depressive insanity (MDI) originally diagnosed by Kraepelin or his collaborators in Munich in 1908. The original case material was coded in terms of Present State Examination syndromes and analysed statistically for internal consistency and discrimination between the two diagnostic entities. Kraepelin's DP and MDI were found to define homogeneous groups of disorders which could be clearly distinguished from one another. A CATEGO re-classification of the cases revealed an 80·2% concordance rate between Kraepelin's diagnoses and ICD-9. Cluster analysis of the original data reproduced closely Kraepelin's dichotomous classification of the psychoses but suggested that DP was a narrower concept than schizophrenia today, while MDI was a composite group including both ‘typical’ manic-depressive illnesses and schizoaffective disorders.

scholarly journals The mystery of Anser neglectus Sushkin, 1897. Victim of the Tunguska disaster? A Hungarian story

2019 ◽  
Vol 27 (2) ◽  
pp. 20-58
Author(s):  
Jacques Van Impe
Keyword(s):  
Distinct Species ◽  
Genetic Mutations ◽  
Zoological Garden ◽  
Large Numbers ◽  
Bean Goose ◽  
Field Identification ◽  
Breeding Grounds ◽  
The Republic ◽  
The Town

Abstract The well-known Russian ornithologist Prof. Peter Sushkin described it as a distinct species from Bashkortostan (Bashkiria) in 1897, a highly acclaimed discovery. However, its breeding grounds never been discovered. Since then, there has been a long-standing debate over the taxonomic position of Anser neglectus. Taxonomists have argued that Anser neglectus belongs to the group of A. fabalis Lath. because of its close resemblance with A. f. fabalis. At the beginning of the 20th century, large numbers of the Sushkin’s goose were observed in three winter quarters: on two lakes in the Republic of Bachkortostan, in the surroundings of the town of Tashkent in the Republic Uzbekistan, and in the puszta Hortobágy in eastern Hungary. It is a pity that taxonomists did not thoroughly compare the Russian and Hungarian ornithological papers concerning the former presence of Anser neglectus in these areas, because these rich sources refer to characteristics that would cast serious doubt on the classification of Anser neglectus as a subspecies, an individual variation or mutation of A. f. fabalis. Sushkin’s goose, though a typical Taiga Bean Goose, distinguished itself from other taxa of the Bean Goose by its plumage, its field identification, by its specific “Gé-gé” call, the size of its bill, and by its preference for warm and dry winter haunts. A. neglectus should therefore be considered a separate, fully distinct species, sensu Stegmann (1935) and Stegmann in Schenk (1931/34), if we follow the established criteria in bird systematics of Tobias et al. (2010). Between 1908 and 1911, an estimation of up to 150.000 individuals of A. neglectus wintered in the Hortobágy puszta. Approximate counts for both other winter quarters are not available. The last living birds were seen in the zoological garden of Budapest in 1934. Since then, A. f. fabalis and A. s. rossicus “Type neglectus” (i.e. A. f. fabalis and A. s. rossicus with a color of the bill and the legs, similar to the former A. neglectus) have been observed sporadically on the breeding grounds and in the winter quarters of both taxa. However, the true A. neglectus seems to be extinct. Its sudden disappearance may be related to the Tunguska event, the catastrophe in 1908 that may have caused genetic mutations. This hypothesis is considered to be the most likely, among other available hypotheses about its extinction.

scholarly journals Machine Learning for Tree Species Classification Using Sentinel-2 Spectral Information, Crown Texture, and Environmental Variables

2020 ◽  
Vol 12 (12) ◽  
pp. 2049
Author(s):  
Joongbin Lim ◽  
Kyoung-Min Kim ◽  
Eun-Hee Kim ◽  
Ri Jin
Keyword(s):  
Machine Learning ◽  
South Korea ◽  
Tree Species ◽  
North Korea ◽  
Forest Type ◽  
Forest Area ◽  
Training Data ◽  
Machine Learning Techniques ◽  
Forest Types

The most recent forest-type map of the Korean Peninsula was produced in 1910. That of South Korea alone was produced since 1972; however, the forest type information of North Korea, which is an inaccessible region, is not known due to the separation after the Korean War. In this study, we developed a model to classify the five dominant tree species in North Korea (Korean red pine, Korean pine, Japanese larch, needle fir, and Oak) using satellite data and machine-learning techniques. The model was applied to the Gwangneung Forest area in South Korea; the Mt. Baekdu area of China, which borders North Korea; and to Goseong-gun, at the border of South Korea and North Korea, to evaluate the model’s applicability to North Korea. Eighty-three percent accuracy was achieved in the classification of the Gwangneung Forest area. In classifying forest types in the Mt. Baekdu area and Goseong-gun, even higher accuracies of 91% and 90% were achieved, respectively. These results confirm the model’s regional applicability. To expand the model for application to North Korea, a new model was developed by integrating training data from the three study areas. The integrated model’s classification of forest types in Goseong-gun (South Korea) was relatively accurate (80%); thus, the model was utilized to produce a map of the predicted dominant tree species in Goseong-gun (North Korea).

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