Using satellite data analysis to determine the effect of land cover on the physical properties of the surface

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12220%2F20%3A43901515" target="_blank" >RIV/60076658:12220/20:43901515 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.5593/sgem2020/2.2/s10.034" target="_blank" >http://dx.doi.org/10.5593/sgem2020/2.2/s10.034</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5593/sgem2020/2.2/s10.034" target="_blank" >10.5593/sgem2020/2.2/s10.034</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Using satellite data analysis to determine the effect of land cover on the physical properties of the surface

Popis výsledku v původním jazyce

In the last few years, the climate change has become more and more apparent. In this time the Central European region has experienced disruption of the precipitation layout, serious storms, heatwaves and droughts. Primarily the droughts have let people feel the need for stable and predictable environment. This problem has usually been addressed as a global effort to reduce the production of greenhouse gases, omitting the option of adjusting the environment on much smaller scale. For mitigating the effects of global warming, it is important to understand the water and energy cycles on the landscape level. Our aim was to measure and describe how different types of land covers (forest, meadow, wetlands, field with a very sparse vegetation cover) transform the solar energy input into the individual energy fluxes (LE-latent heat, H-sensible heat, G-ground heat). The studied areas lay within a watershed of Bedrichovsky creek located in Novohradske hory, small mountain range on the Czech - Austrian border. For our analysis we used multispectral and thermal images provided by USGS?s Landsat 8 satellite program as well as locally acquired meteorological data from an automatic weather station located nearby the studied area. Due to the highest amount of vegetation (NDVI = 0.83) and surface wetness (NDMI = 0.42), the forest areas were capable of investing the largest portion of solar energy into latent heat (LE = 368.9 Wm-2) compared to field?s LE = 266.9 Wm-2 with NDVI = 0.4 and NDMI = -0.04. This way the forest areas were able to cool themselves most efficiently with the lowest mean surface temperature (Ts = 23.8 °C) where mean surface temperature of the field was more than 5 °C higher (Ts = 29 °C). Thanks to the capability of the forest to retain moisture, it invested only about a third of the solar energy into sensible heat (H = 26.8 Wm-2) compared to the field (H = 83.9 Wm-2). The vegetation cooling effect was followed on meadows and wetlands as well.

Název v anglickém jazyce

Using satellite data analysis to determine the effect of land cover on the physical properties of the surface

Popis výsledku anglicky

In the last few years, the climate change has become more and more apparent. In this time the Central European region has experienced disruption of the precipitation layout, serious storms, heatwaves and droughts. Primarily the droughts have let people feel the need for stable and predictable environment. This problem has usually been addressed as a global effort to reduce the production of greenhouse gases, omitting the option of adjusting the environment on much smaller scale. For mitigating the effects of global warming, it is important to understand the water and energy cycles on the landscape level. Our aim was to measure and describe how different types of land covers (forest, meadow, wetlands, field with a very sparse vegetation cover) transform the solar energy input into the individual energy fluxes (LE-latent heat, H-sensible heat, G-ground heat). The studied areas lay within a watershed of Bedrichovsky creek located in Novohradske hory, small mountain range on the Czech - Austrian border. For our analysis we used multispectral and thermal images provided by USGS?s Landsat 8 satellite program as well as locally acquired meteorological data from an automatic weather station located nearby the studied area. Due to the highest amount of vegetation (NDVI = 0.83) and surface wetness (NDMI = 0.42), the forest areas were capable of investing the largest portion of solar energy into latent heat (LE = 368.9 Wm-2) compared to field?s LE = 266.9 Wm-2 with NDVI = 0.4 and NDMI = -0.04. This way the forest areas were able to cool themselves most efficiently with the lowest mean surface temperature (Ts = 23.8 °C) where mean surface temperature of the field was more than 5 °C higher (Ts = 29 °C). Thanks to the capability of the forest to retain moisture, it invested only about a third of the solar energy into sensible heat (H = 26.8 Wm-2) compared to the field (H = 83.9 Wm-2). The vegetation cooling effect was followed on meadows and wetlands as well.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20705 - Remote sensing

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název statě ve sborníku

20th International Multidisciplinary Scientific GeoConference SGEM 2020

ISBN

978-619-7603-07-1

ISSN

1314-2704

e-ISSN

—

Počet stran výsledku

8

Strana od-do

285-292

Název nakladatele

SGEM Scientific eLibrary

Místo vydání

Sofia

Místo konání akce

Sofia, Bulgaria

Datum konání akce

18. 8. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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