Testing the Height Variation Hypothesis with the R rasterdiv Package for Tree Species Diversity Estimation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F21%3A87037" target="_blank" >RIV/60460709:41330/21:87037 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2072-4292/13/18/3569" target="_blank" >https://www.mdpi.com/2072-4292/13/18/3569</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/rs13183569" target="_blank" >10.3390/rs13183569</a>
Alternative languages
Result language
angličtina
Original language name
Testing the Height Variation Hypothesis with the R rasterdiv Package for Tree Species Diversity Estimation
Original language description
Forest biodiversity is a key element to support ecosystem functions. Measuring biodiversity is a necessary step to identify critical issues and to choose interventions to be applied in order to protect it. Remote sensing provides consistent quality and standardized data, which can be used to estimate different aspects of biodiversity. The Height Variation Hypothesis (HVH) represents an indirect method for estimating species diversity in forest ecosystems from the LiDAR data, and it assumes that the higher the variation in tree height (height heterogeneity, HH), calculated through the Canopy Height Model (CHM) metric, the more complex the overall structure of the forest and the higher the tree species diversity. To date, the HVH has been tested exclusively with CHM data, assessing the HH only with a single heterogeneity index (the Raos Q index) without making use of any moving windows (MW) approach. In this study, the HVH has been tested in an alpine coniferous forest situated in the municipality of S
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10618 - Ecology
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
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
Remote Sensing
ISSN
2072-4292
e-ISSN
2072-4292
Volume of the periodical
13
Issue of the periodical within the volume
18
Country of publishing house
CH - SWITZERLAND
Number of pages
20
Pages from-to
1-20
UT code for WoS article
000701547200001
EID of the result in the Scopus database
2-s2.0-85114678535