A remote-sensing assessment of oak forest recovery after postfire restoration - Dataset

A remote-sensing assessment of oak forest recovery after postfire restoration - Dataset

The analysis is based on a dataset of post-fire restoration interventions conducted on deciduous oak forests in Portugal between 2017 and 2018. The dataset includes data on 1314 restored sites and on 1699 control sites. We used a Generalized Additive Mixed Model (GAMM) to analyse how vegetation indi...

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Hauptverfasser: Lopes, Luis Filipe, Dias, Filipe S., M. Fernandes, Paulo, Acácio, Vanda
Format: Dataset
Sprache:eng
Schlagworte:
Fire ecology
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Beschreibung
Zusammenfassung:The analysis is based on a dataset of post-fire restoration interventions conducted on deciduous oak forests in Portugal between 2017 and 2018. The dataset includes data on 1314 restored sites and on 1699 control sites. We used a Generalized Additive Mixed Model (GAMM) to analyse how vegetation indices such as NDVI and MSAVI changed over time as a function of post-fire restoration and topography and climate variables.
DOI:10.6084/m9.figshare.22012688