From local spectral species to global spectral communities: A benchmark for ecosystem diversity estimate by remote sensing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F21%3A87005" target="_blank" >RIV/60460709:41330/21:87005 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S157495412030145X" target="_blank" >https://www.sciencedirect.com/science/article/pii/S157495412030145X</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ecoinf.2020.101195" target="_blank" >10.1016/j.ecoinf.2020.101195</a>
Alternative languages
Result language
angličtina
Original language name
From local spectral species to global spectral communities: A benchmark for ecosystem diversity estimate by remote sensing
Original language description
In the light of unprecedented change in global biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential. Nevertheless, estimation of biodiversity using ecological field data can be difficult for several reasons. For instance, for very large areas, it is challenging to collect data that provide reliable information. Some of these restrictions in Earth observation can be avoided through the use of remote sensing approaches. Various studies have estimated biodiversity on the basis of the Spectral Variation Hypothesis (SVH). According to this hypothesis, spectral heterogeneity over the different pixel units of a spatial grid reflects a higher niche heterogeneity, allowing more organisms to coexist. Recently, the spectral species concept has been derived, following the consideration that spectral heterogeneity at a landscape scale corresponds to a combination of subspaces sharing a similar spectral signature. With the use of high resolution remote sen
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
Ecological Informatics
ISSN
1574-9541
e-ISSN
1878-0512
Volume of the periodical
2021
Issue of the periodical within the volume
61
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
10
Pages from-to
1-10
UT code for WoS article
000632610000003
EID of the result in the Scopus database
2-s2.0-85096649722