Implementing the formal language of the vegetation
classification expert systems (ESy) in the statistical
computing environment R

J 2021

Implementing the formal language of the vegetation classification expert systems (ESy) in the statistical computing environment R

BRUELHEIDE, Helge; Lubomír TICHÝ; Milan CHYTRÝ a Florian JANSEN

Základní údaje

Originální název

Implementing the formal language of the vegetation classification expert systems (ESy) in the statistical computing environment R

Autoři

BRUELHEIDE, Helge; Lubomír TICHÝ; Milan CHYTRÝ a Florian JANSEN

Vydání

Applied Vegetation Science, Hoboken, Wiley, 2021, 1402-2001

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10611 Plant sciences, botany

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 3.431

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14310/21:00119069

Organizační jednotka

Přírodovědecká fakulta

Klíčová slova anglicky

COCKTAIL method; EUNIS; Europe; expert system; R software; vegetation classification; vegetation database

Štítky

14314020, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 11. 1. 2022 10:17, Mgr. Marie Novosadová Šípková, DiS.

Anotace

V originále

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.

Návaznosti

GX19-28491X, projekt VaV

Název: Centrum pro evropské vegetační syntézy (CEVS) (Akronym: CEVS)

Investor: Grantová agentura ČR, Centrum pro evropské vegetační syntézy (CEVS)

Citovat

BRUELHEIDE, Helge; Lubomír TICHÝ; Milan CHYTRÝ a 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, roč. 24, č. 1, s. "e12562", 7 s. ISSN 1402-2001. Dostupné z: https://doi.org/10.1111/avsc.12562.

@article{1782178,
   author = {Bruelheide, Helge and Tichý, Lubomír and Chytrý, Milan and Jansen, Florian},
   article_location = {Hoboken},
   article_number = {1},
   doi = {https://doi.org/10.1111/avsc.12562},
   keywords = {COCKTAIL method; EUNIS; Europe; expert system; R software; vegetation classification; vegetation database},
   language = {eng},
   issn = {1402-2001},
   journal = {Applied Vegetation Science},
   title = {Implementing the formal language of the vegetation classification expert systems (ESy) in the statistical computing environment R},
   url = {https://doi.org/10.1111/avsc.12562},
   volume = {24},
   year = {2021}
}

TY  - JOUR
ID  - 1782178
AU  - Bruelheide, Helge - Tichý, Lubomír - Chytrý, Milan - Jansen, Florian
PY  - 2021
TI  - Implementing the formal language of the vegetation classification expert systems (ESy) in the statistical computing environment R
JF  - Applied Vegetation Science
VL  - 24
IS  - 1
SP  - "e12562"
EP  - "e12562"
PB  - Wiley
SN  - 14022001
KW  - COCKTAIL method
KW  - EUNIS
KW  - Europe
KW  - expert system
KW  - R software
KW  - vegetation classification
KW  - vegetation database
UR  - https://doi.org/10.1111/avsc.12562
N2  - 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.
ER  -

BRUELHEIDE, Helge; Lubomír TICHÝ; Milan CHYTRÝ a Florian JANSEN. Implementing the formal language of the vegetation classification expert systems (ESy) in the statistical computing environment R. \textit{Applied Vegetation Science}. Hoboken: Wiley, 2021, roč.~24, č.~1, s.~''e12562'', 7 s. ISSN~1402-2001. Dostupné z: https://doi.org/10.1111/avsc.12562.

Přehled o publikaci