Cooling the land surface: Ecosystem health and water availability drive the landscape capacity to mitigate climate change

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13520%2F25%3A43899071" target="_blank" >RIV/44555601:13520/25:43899071 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.ecolind.2025.113265" target="_blank" >https://doi.org/10.1016/j.ecolind.2025.113265</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ecolind.2025.113265" target="_blank" >10.1016/j.ecolind.2025.113265</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cooling the land surface: Ecosystem health and water availability drive the landscape capacity to mitigate climate change

Popis výsledku v původním jazyce

Land surface temperature (LST) is profoundly interlinked with the landscape state, settings and functioning, with the connections being very complex. Although the role of wetlands and (semi)natural habitats, in mitigating climate extremes is generally understood, the mechanisms explaining the thermal patterns in complex landscapes remain unclear. We address this knowledge gap, investigating a link between the dynamics of LST and characteristics of a diverse sandstone landscape, focusing on the role of water features and forest health in alleviating temperature extremes. For our study, we used a model example of a sandstone protected area in the north of the Czech Republic that underwent significant changes during the last decade due to a bark beetle infestation and a consequent forest die-off and wildfire. LST data were obtained from MODIS and Landsat 8 sensors in a cloud-based Google Earth Engine platform. Machine learning regression model enabled us to assess complex multivariable relationships and increase the LST spatial resolution. The results suggest the significant effect of both water availability and ecosystem health on LST, with vegetation indices, land cover and elevation being the main factors. The correlation of the satellite-based LST and in situ measured temperature depended on the canopy cover. The study indicates that in complex landscapes, LST data of high spatial and temporal resolution is necessary to disentangle local patterns and environmental drivers. Satellite data can serve as a reliable means to understand the mechanisms and prepare adaptive management measures to make the landscape more resistant to climate change related threats.

Název v anglickém jazyce

Cooling the land surface: Ecosystem health and water availability drive the landscape capacity to mitigate climate change

Popis výsledku anglicky

Land surface temperature (LST) is profoundly interlinked with the landscape state, settings and functioning, with the connections being very complex. Although the role of wetlands and (semi)natural habitats, in mitigating climate extremes is generally understood, the mechanisms explaining the thermal patterns in complex landscapes remain unclear. We address this knowledge gap, investigating a link between the dynamics of LST and characteristics of a diverse sandstone landscape, focusing on the role of water features and forest health in alleviating temperature extremes. For our study, we used a model example of a sandstone protected area in the north of the Czech Republic that underwent significant changes during the last decade due to a bark beetle infestation and a consequent forest die-off and wildfire. LST data were obtained from MODIS and Landsat 8 sensors in a cloud-based Google Earth Engine platform. Machine learning regression model enabled us to assess complex multivariable relationships and increase the LST spatial resolution. The results suggest the significant effect of both water availability and ecosystem health on LST, with vegetation indices, land cover and elevation being the main factors. The correlation of the satellite-based LST and in situ measured temperature depended on the canopy cover. The study indicates that in complex landscapes, LST data of high spatial and temporal resolution is necessary to disentangle local patterns and environmental drivers. Satellite data can serve as a reliable means to understand the mechanisms and prepare adaptive management measures to make the landscape more resistant to climate change related threats.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Ecological Indicators

ISSN

1470-160X

e-ISSN

1872-7034

Svazek periodika

2025

Číslo periodika v rámci svazku

172

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

11

Strana od-do

"nestrankovano"

Kód UT WoS článku

001431351200001

EID výsledku v databázi Scopus

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