Height variation hypothesis: A new approach for estimating forest species diversity with CHM LiDAR data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F20%3A82301" target="_blank" >RIV/60460709:41330/20:82301 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1470160X2030457X?dgcid=rss_sd_all" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1470160X2030457X?dgcid=rss_sd_all</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ecolind.2020.106520" target="_blank" >10.1016/j.ecolind.2020.106520</a>
Alternative languages
Result language
angličtina
Original language name
Height variation hypothesis: A new approach for estimating forest species diversity with CHM LiDAR data
Original language description
An indirect method for estimating biodiversity from Earth observations is the Spectral Variation Hypothesis SVH. SVH states that the higher the spatial variability of the spectral response of an optical remotely sensed image, the higher the number of available ecological niches and hence, the higher the diversity of tree species in the considered area. Here for the first time we apply the concept of the SVH to Light Detection and Ranging LiDAR data to understand the relationship between the height heterogeneity HH of a forest and its tree species diversity, a concept we have named the Height Variation Hypothesis HVH. We tested HVH in two different European forest types a coniferous mountain forest in the eastern Italian Alps and a mixed temperate forest in southern Germany. We used the heterogeneity index Raos Q to estimate HH using a Canopy Height ModelCHM at different resolutions derived from LiDAR data, and linear regression models and relation analysis to assess the relationships between HH and t
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
10511 - Environmental sciences (social aspects to be 5.7)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ECOLOGICAL INDICATORS
ISSN
1470-160X
e-ISSN
1872-7034
Volume of the periodical
2020
Issue of the periodical within the volume
117
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
9
Pages from-to
1-9
UT code for WoS article
000555557300010
EID of the result in the Scopus database
2-s2.0-85085268487