scholarly journals Vegetation classification of Coffea on Hawaii Island using WorldView-2 satellite imagery

2017 ◽  
Vol 11 (04) ◽  
pp. 1 ◽  
Author(s):  
Julie Gaertner
2019 ◽  
pp. 135-142
Author(s):  
K. V. Ivanova ◽  
A. M. Lapina ◽  
V. V. Neshataev

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.


2009 ◽  
pp. 27-53
Author(s):  
A. Yu. Kudryavtsev

Diversity of plant communities in the nature reserve “Privolzhskaya Forest-Steppe”, Ostrovtsovsky area, is analyzed on the basis of the large-scale vegetation mapping data from 2000. The plant community classi­fication based on the Russian ecologic-phytocoenotic approach is carried out. 12 plant formations and 21 associations are distinguished according to dominant species and a combination of ecologic-phytocoenotic groups of species. A list of vegetation classification units as well as the characteristics of theshrub and woody communities are given in this paper.


1998 ◽  
Author(s):  
Jo Ann Parikh ◽  
John S. DaPonte ◽  
Joseph N. Vitale ◽  
George Tselioudis

2013 ◽  
Vol 46 (6) ◽  
pp. 426-433 ◽  
Author(s):  
Kyung-Do Lee ◽  
Shin-Chul Baek ◽  
Suk-Young Hong ◽  
Yi-Hyun Kim ◽  
Sang-Il Na ◽  
...  

Author(s):  
D. Verma ◽  
A. Jana ◽  
K. Ramamritham

<p><strong>Abstract.</strong> The studies in the classification of the urban spatial structure have been essential in deriving insights into the land cover and the built typology which helped in the estimation of energy consumption patterns, urban density, compactness, and hierarchy of settlements. However, the analysis and comparison of the physical forms of the cities have been attempted in a piecemeal fashion where the requirement of datasets and the computation power for analysis has been a major hindrance. With the advancement in machine learning based techniques, large datasets such as satellite imagery can be studied with advanced computer vision methods. These solutions may help in studying the intricate nature of human habitats in large extents of geographical areas including various urban areas. This study utilizes smaller patches of medium resolution Sentinel-2B Imagery of ten different cities in India to explore the urban forms present in these cities. This study uses Stacked Convolutional Autoencoder (CAE) to reduce the dimensionality of satellite imagery patches and unsupervised clustering techniques such as t-SNE and K-means to study the characteristics of similar patches. On analyzing the clusters through visual exploration, similar patches are delineated and provided with corresponding labels representing urban forms. Individual clusters are then studied with respect to each city. The motive of the study is to gain insights into the different types of morphological patterns present within and among cities.</p>


2004 ◽  
Vol 30 (2) ◽  
pp. 137-149 ◽  
Author(s):  
Michael A Wulder ◽  
Steven E Franklin ◽  
Joanne C White ◽  
Morgan M Cranny ◽  
Jeff A Dechka

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