Assessment of Machine Learning Algorithms for Modeling the Spatial Distribution of Bark Beetle Infestation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F21%3A89737" target="_blank" >RIV/60460709:41320/21:89737 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/1999-4907/12/4/395" target="_blank" >https://www.mdpi.com/1999-4907/12/4/395</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/f12040395" target="_blank" >10.3390/f12040395</a>
Alternative languages
Result language
angličtina
Original language name
Assessment of Machine Learning Algorithms for Modeling the Spatial Distribution of Bark Beetle Infestation
Original language description
Machine learning algorithms (MLAs) are used to solve complex non-linear and high-dimensional problems. The objective of this study was to identify the MLA that generates an accurate spatial distribution model of bark beetle (Ips typographus L.) infestation spots. We first evaluated the performance of 2 linear (logistic regression, linear discriminant analysis), 4 non-linear (quadratic discriminant analysis, k-nearest neighbors classifier, Gaussian naive Bayes, support vector classification), and 4 decision trees-based MLAs (decision tree classifier, random forest classifier, extra trees classifier, gradient boosting classifier) for the study area (the Horni Plana region, Czech Republic) for the period 2003-2012. Each MLA was trained and tested on all subsets of the 8 explanatory variables (distance to forest damage spots from previous year, distance to spruce forest edge, potential global solar radiation, normalized difference vegetation index, spruce forest age, percentage of spruce, volume of spruc
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
40102 - Forestry
Result continuities
Project
<a href="/en/project/QK1920433" target="_blank" >QK1920433: Influence of protective measures to populations bark beetles according on population density</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
FORESTS
ISSN
1999-4907
e-ISSN
—
Volume of the periodical
12
Issue of the periodical within the volume
4
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
19
Pages from-to
1-19
UT code for WoS article
000643043100001
EID of the result in the Scopus database
2-s2.0-85103988615