Towards monitoring stem growth phenology from space with high resolution satellite data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F23%3A00573738" target="_blank" >RIV/86652079:_____/23:00573738 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/62156489:43410/23:43923610

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/abs/pii/S016819232300240X?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S016819232300240X?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.agrformet.2023.109549" target="_blank" >10.1016/j.agrformet.2023.109549</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Towards monitoring stem growth phenology from space with high resolution satellite data

Popis výsledku v původním jazyce

Radial stem growth is a key ecosystem process resulting in long-term carbon sequestration. Despite recognition of its importance to global carbon cycling, high uncertainties remain regarding how radial growth phenology (e.g., the onset, mid, and cessation of radial growth) will be affected by climate change. In this study, we evaluated to what extent high spatially (3 × 3 m) and temporally (up to daily) resolved satellite imagery from PlanetScope can be used to monitor stem growth phenology. For this, we made use of detailed stem growth phenological observations of six common European tree species measured by automated point dendrometers at 14 distinct sites across Switzerland between 2017 and 2021. These growth phenological observations were then linked through multiple regression modeling with metrics extracted from spectral index time series. Our results show that the remote sensing-based models enable monitoring the onset (root mean squared deviation (RMSD) ranges from 5.96 to 27.04 days) and mid-stages of stem growth (RMSD ranges from 10.20 to 36.34 days) with reasonable accuracy as opposed to the cessation of stem growth that showed low accuracy (RMSD ranges from 16.02 to 153.63 days). The accuracy of the remote sensing-based prediction models and their optimal suite of predictors varied across species. The latter has important implications for the remote sensing of stem growth phenology in mixed forests, suggesting that it is important for satellite sensors to resolve individual tree crowns. Overall, our results suggest the need for novel spectral indices that capture the spectral components of mechanistic linkages between stem growth and canopy properties that go beyond the mere detection of leaf phenology. When employing such spectral indices, remote sensing could make it possible to detect not only shifts in leaf phenology caused by climate change but also those in stem growth on a broad spatial scale.

Název v anglickém jazyce

Towards monitoring stem growth phenology from space with high resolution satellite data

Popis výsledku anglicky

Radial stem growth is a key ecosystem process resulting in long-term carbon sequestration. Despite recognition of its importance to global carbon cycling, high uncertainties remain regarding how radial growth phenology (e.g., the onset, mid, and cessation of radial growth) will be affected by climate change. In this study, we evaluated to what extent high spatially (3 × 3 m) and temporally (up to daily) resolved satellite imagery from PlanetScope can be used to monitor stem growth phenology. For this, we made use of detailed stem growth phenological observations of six common European tree species measured by automated point dendrometers at 14 distinct sites across Switzerland between 2017 and 2021. These growth phenological observations were then linked through multiple regression modeling with metrics extracted from spectral index time series. Our results show that the remote sensing-based models enable monitoring the onset (root mean squared deviation (RMSD) ranges from 5.96 to 27.04 days) and mid-stages of stem growth (RMSD ranges from 10.20 to 36.34 days) with reasonable accuracy as opposed to the cessation of stem growth that showed low accuracy (RMSD ranges from 16.02 to 153.63 days). The accuracy of the remote sensing-based prediction models and their optimal suite of predictors varied across species. The latter has important implications for the remote sensing of stem growth phenology in mixed forests, suggesting that it is important for satellite sensors to resolve individual tree crowns. Overall, our results suggest the need for novel spectral indices that capture the spectral components of mechanistic linkages between stem growth and canopy properties that go beyond the mere detection of leaf phenology. When employing such spectral indices, remote sensing could make it possible to detect not only shifts in leaf phenology caused by climate change but also those in stem growth on a broad spatial scale.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Agricultural and Forest Meteorology

ISSN

0168-1923

e-ISSN

1873-2240

Svazek periodika

339

Číslo periodika v rámci svazku

AUG

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

14

Strana od-do

109549

Kód UT WoS článku

001023571400001

EID výsledku v databázi Scopus

2-s2.0-85162106089