Phenological Patterns for Central Asia. Vegetation Dynamics by the Means of Remote Sensing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F11%3A00052802" target="_blank" >RIV/00216224:14310/11:00052802 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.earsel.org/symposia//2011-symposium-Prague/Proceedings/index.htm" target="_blank" >http://www.earsel.org/symposia//2011-symposium-Prague/Proceedings/index.htm</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Phenological Patterns for Central Asia. Vegetation Dynamics by the Means of Remote Sensing

Popis výsledku v původním jazyce

Phenology is an important indicator for climate conditions. Thus studying vegetation dynamics could lead to a better understanding of present and future climate changes. For assessing of vegetation dynamics on a regional scale remote sensing is currentlythe only method that offers at the same time the possibility for continuous monitoring over long time spans. In this study, we extracted and analyzed phenological parameters from remotely sensed time series data for Central Asia at different scales. Atregional (Central Asia) level time series of the Normalized Difference Vegetation Index (NDVI) from the Global Inventory Modeling and Mapping Studies (GIMMS) derived from imagery of the Advanced Very High Resolution Radiometer (AVHRR) instrument were utilized. These data cover a time period of 25 years (1982-2006) and have a spatial resolution of 8 km.

Název v anglickém jazyce

Phenological Patterns for Central Asia. Vegetation Dynamics by the Means of Remote Sensing

Popis výsledku anglicky

Phenology is an important indicator for climate conditions. Thus studying vegetation dynamics could lead to a better understanding of present and future climate changes. For assessing of vegetation dynamics on a regional scale remote sensing is currentlythe only method that offers at the same time the possibility for continuous monitoring over long time spans. In this study, we extracted and analyzed phenological parameters from remotely sensed time series data for Central Asia at different scales. Atregional (Central Asia) level time series of the Normalized Difference Vegetation Index (NDVI) from the Global Inventory Modeling and Mapping Studies (GIMMS) derived from imagery of the Advanced Very High Resolution Radiometer (AVHRR) instrument were utilized. These data cover a time period of 25 years (1982-2006) and have a spatial resolution of 8 km.

Druh

D - Stať ve sborníku

CEP obor

DG - Vědy o atmosféře, meteorologie

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

31st EARSeL Symposium Proceedings

ISBN

978-80-01-04868-9

ISSN

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e-ISSN

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Počet stran výsledku

9

Strana od-do

289-297

Název nakladatele

EARSeL

Místo vydání

Praha

Místo konání akce

Prag

Datum konání akce

1. 1. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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