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Probabilistic key for identifying vegetation types in the field: A new method and Android application
Author(s) -
Tichý Lubomír,
Chytrý Milan
Publication year - 2019
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.1111/jvs.12799
Subject(s) - vegetation classification , vegetation (pathology) , probabilistic logic , computer science , vegetation types , field (mathematics) , vegetation type , remote sensing , a priori and a posteriori , data mining , ecology , geography , artificial intelligence , habitat , mathematics , biology , medicine , philosophy , epistemology , pathology , grassland , pure mathematics
Quick identification of vegetation types in the field, based on species composition but not requiring time‐consuming plot sampling, is often needed for vegetation mapping, conservation assessment, teaching and other applications of vegetation classification. Here, we propose a new method that identifies the probability of belonging to the units of an established vegetation classification for vegetation stands encountered in the field. The method is based on calculating the probability that a few species observed in the field would co‐occur in a priori defined vegetation types, using the existing information on species occurrence frequency in these types. The method has been implemented in a freely available Android application called Probabilistic Vegetation Key, which makes it possible to employ it in the field using smartphones or tablets, even in the absence of internet access.