Cooling the land surface: Ecosystem health and water availability drive the landscape capacity to mitigate climate change
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Cooling the land surface: Ecosystem health and water availability drive the landscape capacity to mitigate climate change
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10511 - Environmental sciences (social aspects to be 5.7)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Ecological Indicators
ISSN
1470-160X
e-ISSN
1872-7034
Volume of the periodical
2025
Issue of the periodical within the volume
172
Country of publishing house
GB - UNITED KINGDOM
Number of pages
11
Pages from-to
"nestrankovano"
UT code for WoS article
001431351200001
EID of the result in the Scopus database
—