BRUELHEIDE, Helge, Lubomír TICHÝ, Milan CHYTRÝ and Florian JANSEN. Implementing the formal language of the vegetation classification expert systems (ESy) in the statistical computing environment R. Applied Vegetation Science. Hoboken: Wiley, 2021, vol. 24, No 1, p. "e12562", 7 pp. ISSN 1402-2001. Available from: https://dx.doi.org/10.1111/avsc.12562.
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Basic information
Original name Implementing the formal language of the vegetation classification expert systems (ESy) in the statistical computing environment R
Authors BRUELHEIDE, Helge (276 Germany), Lubomír TICHÝ (203 Czech Republic, belonging to the institution), Milan CHYTRÝ (203 Czech Republic, guarantor, belonging to the institution) and Florian JANSEN (276 Germany).
Edition Applied Vegetation Science, Hoboken, Wiley, 2021, 1402-2001.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10611 Plant sciences, botany
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 3.431
RIV identification code RIV/00216224:14310/21:00119069
Organization unit Faculty of Science
Doi http://dx.doi.org/10.1111/avsc.12562
UT WoS 000636291500003
Keywords in English COCKTAIL method; EUNIS; Europe; expert system; R software; vegetation classification; vegetation database
Tags rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Marie Šípková, DiS., učo 437722. Changed: 11/1/2022 10:17.
Abstract
Aims The machine-readable formal language of classification expert systems has become a standard for applying plot assignment rules in vegetation classification. Here we present an efficient algorithm implementing the vegetation classification expert system in the statistical programming language R. Methods The principal idea of the R implementation is to solve the assignments to vegetation types not sequentially plot by plot but to parse the assignment rules into (nested) components that each can be evaluated by simultaneous vector-based processing of all plots in a database. Results and conclusions We demonstrate the algorithm taking the EUNIS classification expert system of European habitat types (EUNIS-ESy) as an example. The R code version of the vegetation classification expert system is particularly useful in large vegetation-plot databases because it solves all logical operations vector-wise across all plots, allowing for efficient evaluation of membership expressions and formulas. Another advantage of the R implementation is that membership formulas are not only readable but can also be produced as a machine-written result, for example as the output of classification algorithms run in R.
Links
GX19-28491X, research and development projectName: Centrum pro evropské vegetační syntézy (CEVS) (Acronym: CEVS)
Investor: Czech Science Foundation
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