Pantropical modelling of canopy functional traits using Sentinel-2 remote sensing data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43410%2F21%3A43918420" target="_blank" >RIV/62156489:43410/21:43918420 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1016/j.rse.2020.112122" target="_blank" >https://doi.org/10.1016/j.rse.2020.112122</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.rse.2020.112122" target="_blank" >10.1016/j.rse.2020.112122</a>
Alternative languages
Result language
angličtina
Original language name
Pantropical modelling of canopy functional traits using Sentinel-2 remote sensing data
Original language description
Tropical forest ecosystems are undergoing rapid transformation as a result of changing environmental conditions and direct human impacts. However, we cannot adequately understand, monitor or simulate tropical ecosystem responses to environmental changes without capturing the high diversity of plant functional characteristics in the species-rich tropics. Failure to do so can oversimplify our understanding of ecosystems responses to environmental disturbances. Innovative methods and data products are needed to track changes in functional trait composition in tropical forest ecosystems through time and space. This study aimed to track key functional traits by coupling Sentinel-2 derived variables with a unique data set of precisely located in-situ measurements of canopy functional traits collected from 2434 individual trees across the tropics using a standardised methodology. The functional traits and vegetation censuses were collected from 47 field plots in the countries of Australia, Brazil, Peru, Gabon, Ghana, and Malaysia, which span the four tropical continents. The spatial positions of individual trees above 10 cm diameter at breast height (DBH) were mapped and their canopy size and shape recorded. Using geo-located tree canopy size and shape data, community-level trait values were estimated at the same spatial resolution as Sentinel-2 imagery (i.e. 10 m pixels). We then used the Geographic Random Forest (GRF) to model and predict functional traits across our plots. We demonstrate that key plant functional traits can be accurately predicted across the tropicsusing the high spatial and spectral resolution of Sentinel-2 imagery in conjunction with climatic and soil information. Image textural parameters were found to be key components of remote sensing information for predicting functional traits across tropical forests and woody savannas. Leaf thickness (R2 = 0.52) obtained the highest prediction accuracy among the morphological and structural traits and leaf carbon content (R2 = 0.70) and maximum rates of photosynthesis (R2 = 0.67) obtained the highest prediction accuracy for leaf chemistry and photosynthesis related traits, respectively. Overall, the highest prediction accuracy was obtained for leaf chemistry and photosynthetic traits in comparison to morphological and structural traits. Our approach offers new opportunities for mapping, monitoring and understanding biodiversity and ecosystem change in the most species-rich ecosystems on Earth.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10511 - Environmental sciences (social aspects to be 5.7)
Result continuities
Project
<a href="/en/project/LTT19018" target="_blank" >LTT19018: Participation of the Czech Republic in the GEM network</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Remote Sensing of Environment
ISSN
0034-4257
e-ISSN
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Volume of the periodical
252
Issue of the periodical within the volume
January
Country of publishing house
US - UNITED STATES
Number of pages
18
Pages from-to
112122
UT code for WoS article
000596508800003
EID of the result in the Scopus database
2-s2.0-85092472356