Estimating tree species diversity from space in an alpine conifer forest: The Rao's Q diversity index meets the spectral variation hypothesis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F19%3A79752" target="_blank" >RIV/60460709:41330/19:79752 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1574954119300561?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1574954119300561?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ecoinf.2019.04.001" target="_blank" >10.1016/j.ecoinf.2019.04.001</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Estimating tree species diversity from space in an alpine conifer forest: The Rao's Q diversity index meets the spectral variation hypothesis

Popis výsledku v původním jazyce

Forests cover about 30 of the Earth surface, they are among the most biodiverse terrestrial ecosystems and represent the bulk of many ecological processes and services. The assessment of biodiversity is an important and essential goal to achieve but it can results difficult, time consuming and expensive when based on field data. Remote sensing covers large areas and provides consistent quality and standardized data, which can be used to estimate species diversity. One method to estimate species diversity from remote sensing data is based on the Spectral Variation Hypothesis (SVH), which assumes that the higher the spectral variation of an image, the higher the environmental heterogeneity and the species diversity of the considered area. SVH has been tested using different spectral heterogeneity (SH) indices and measures, recently the Raos Q index has been proposed as a new spectral variation measure to be applied to remote sensing data. In this paper, we tested the SVH in an alpine coniferous forest

Název v anglickém jazyce

Estimating tree species diversity from space in an alpine conifer forest: The Rao's Q diversity index meets the spectral variation hypothesis

Popis výsledku anglicky

Forests cover about 30 of the Earth surface, they are among the most biodiverse terrestrial ecosystems and represent the bulk of many ecological processes and services. The assessment of biodiversity is an important and essential goal to achieve but it can results difficult, time consuming and expensive when based on field data. Remote sensing covers large areas and provides consistent quality and standardized data, which can be used to estimate species diversity. One method to estimate species diversity from remote sensing data is based on the Spectral Variation Hypothesis (SVH), which assumes that the higher the spectral variation of an image, the higher the environmental heterogeneity and the species diversity of the considered area. SVH has been tested using different spectral heterogeneity (SH) indices and measures, recently the Raos Q index has been proposed as a new spectral variation measure to be applied to remote sensing data. In this paper, we tested the SVH in an alpine coniferous forest

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10618 - Ecology

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Ecological Informatics

ISSN

1574-9541

e-ISSN

1878-0512

Svazek periodika

2019

Číslo periodika v rámci svazku

52

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

9

Strana od-do

26-34

Kód UT WoS článku

000472984800004

EID výsledku v databázi Scopus

2-s2.0-85065048906