Mapping Tree Mortality at Global Scale Using Sentinel-2
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Mapping Tree Mortality at Global Scale Using Sentinel-2. / Mosig, Clemens; Mahecha, Miguel D.; Montero, David; Cheng, Yan; Perez-Priego, Oscar; Beloiu, Mirela; Volpi, Michele; Horion, Stéphanie; Latifi, Hooman; Shafeian, Elham; Fassnacht, Fabian; Ganz, Selina; Zielewska-Büttner, Katarzyna; Laliberté, Etienne; Cloutier, Myriam; Schmehl, Marie-Therese; Frick, Annett; Müller-Landau, Helene; Cushman, KC; Hupy, Joseph; Ma, Qin; Su, Yanjun; Khatri-Chhetri, Pratima; Kruse, Stefan; Frey, Julian; Schiefer, Felix; Junttila, Samuli; Potts, Alastair; Uhl, Andreas; Rossi, Christian; Kattenborn, Teja.
2024. Abstract from EGU General Assembly 2024, Vienna, Austria.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
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TY - ABST
T1 - Mapping Tree Mortality at Global Scale Using Sentinel-2
AU - Mosig, Clemens
AU - Mahecha, Miguel D.
AU - Montero, David
AU - Cheng, Yan
AU - Perez-Priego, Oscar
AU - Beloiu, Mirela
AU - Volpi, Michele
AU - Horion, Stéphanie
AU - Latifi, Hooman
AU - Shafeian, Elham
AU - Fassnacht, Fabian
AU - Ganz, Selina
AU - Zielewska-Büttner, Katarzyna
AU - Laliberté, Etienne
AU - Cloutier, Myriam
AU - Schmehl, Marie-Therese
AU - Frick, Annett
AU - Müller-Landau, Helene
AU - Cushman, KC
AU - Hupy, Joseph
AU - Ma, Qin
AU - Su, Yanjun
AU - Khatri-Chhetri, Pratima
AU - Kruse, Stefan
AU - Frey, Julian
AU - Schiefer, Felix
AU - Junttila, Samuli
AU - Potts, Alastair
AU - Uhl, Andreas
AU - Rossi, Christian
AU - Kattenborn, Teja
PY - 2024/3/11
Y1 - 2024/3/11
N2 - Excess tree mortality in the wake of climate extremes has been observed globally. However, we still lack precise data on mortality at global scale to understand respective drivers and spatiotemporal dynamics. The Sentinel-2 satellite fleet, equipped with the MultiSpectral Instrument (MSI), covers the entire earth on average every five days at spatial resolutions ranging from 10 m to 60 m. Mapping tree mortality from Sentinel-2 globally in diverse ecosystems requires equally diverse reference data. Using globally distributed high-resolution aerial orthoimagery reference data and artificial intelligence methods, we can translate spectral signatures of remote sensing into deadwood. Specifically, in this study we show how to predict the share of standing deadwood for a 10 m pixel in a specific year. The method takes into account temporal patterns, spatial context, as well as all Sentinel-2 spectral bands. This will enable us to map tree mortality globally at a new level of precision.
AB - Excess tree mortality in the wake of climate extremes has been observed globally. However, we still lack precise data on mortality at global scale to understand respective drivers and spatiotemporal dynamics. The Sentinel-2 satellite fleet, equipped with the MultiSpectral Instrument (MSI), covers the entire earth on average every five days at spatial resolutions ranging from 10 m to 60 m. Mapping tree mortality from Sentinel-2 globally in diverse ecosystems requires equally diverse reference data. Using globally distributed high-resolution aerial orthoimagery reference data and artificial intelligence methods, we can translate spectral signatures of remote sensing into deadwood. Specifically, in this study we show how to predict the share of standing deadwood for a 10 m pixel in a specific year. The method takes into account temporal patterns, spatial context, as well as all Sentinel-2 spectral bands. This will enable us to map tree mortality globally at a new level of precision.
U2 - 10.5194/egusphere-egu24-18230
DO - 10.5194/egusphere-egu24-18230
M3 - Conference abstract for conference
T2 - EGU General Assembly 2024
Y2 - 15 April 2024 through 19 April 2024
ER -
ID: 385223040