EVALUATION OF FOREST DISTURBANCES IN THE LOW TATRAS NATIONAL PARK USING TIME SERIES OF SATELLITE IMAGES

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F17%3A10364344" target="_blank" >RIV/00216208:11310/17:10364344 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.3390/ijgi8020071" target="_blank" >https://doi.org/10.3390/ijgi8020071</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/ijgi8020071" target="_blank" >10.3390/ijgi8020071</a>

Jazyk výsledku

angličtina

Název v původním jazyce

EVALUATION OF FOREST DISTURBANCES IN THE LOW TATRAS NATIONAL PARK USING TIME SERIES OF SATELLITE IMAGES

Popis výsledku v původním jazyce

The study focusses on an evaluation of the forest changes in the Low Tatras National Park. The used methods are based on the time series of the satellite Landsat images. The impacts of disturbances on the health of vegetation, particularly forest ecosystems, are investigated using time series methods. The main data source is the archive of satellite Landsat data. The selected vegetation indices are used and tested for the purposes of the detection of land cover changes and evaluation of the health of forest. From point of view data sources and methods, Landsat CDR data and calculated vegetation indices based on this data reflect very well the disturbance events, especially wind storms and biological calamities (bark beetle, in this article). The results express the high relevance of the radiometric normalizations in the time series analysis. Especially, tested methods Pseudoinvariant Features (Linear Based), Ridge (Linear Based) are useful. Time series analysis validated by in-situ data is efficient to detect the individual phases of forest disturbances and subsequent regeneration. The methods and results are very useful for the study of the changes of forest health and bring relevant information for the management of national parks.

Název v anglickém jazyce

EVALUATION OF FOREST DISTURBANCES IN THE LOW TATRAS NATIONAL PARK USING TIME SERIES OF SATELLITE IMAGES

Popis výsledku anglicky

The study focusses on an evaluation of the forest changes in the Low Tatras National Park. The used methods are based on the time series of the satellite Landsat images. The impacts of disturbances on the health of vegetation, particularly forest ecosystems, are investigated using time series methods. The main data source is the archive of satellite Landsat data. The selected vegetation indices are used and tested for the purposes of the detection of land cover changes and evaluation of the health of forest. From point of view data sources and methods, Landsat CDR data and calculated vegetation indices based on this data reflect very well the disturbance events, especially wind storms and biological calamities (bark beetle, in this article). The results express the high relevance of the radiometric normalizations in the time series analysis. Especially, tested methods Pseudoinvariant Features (Linear Based), Ridge (Linear Based) are useful. Time series analysis validated by in-situ data is efficient to detect the individual phases of forest disturbances and subsequent regeneration. The methods and results are very useful for the study of the changes of forest health and bring relevant information for the management of national parks.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10508 - Physical geography

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

SGEM2017 Conference Proceedings

ISBN

978-619-7408-03-4

ISSN

—

e-ISSN

neuvedeno

Počet stran výsledku

14

Strana od-do

87-100

Název nakladatele

SGEM

Místo vydání

Vienna, Albena

Místo konání akce

Albena, Bulgaria

Datum konání akce

29. 6. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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