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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

  • 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

    10618 - Ecology

Result continuities

  • Project

  • 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