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Australia-wide Machine Learning Evapotranspiration for Trees (AMLETT) model for the Lower Limestone Coast

CSIRO RDS Repository

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Title Australia-wide Machine Learning Evapotranspiration for Trees (AMLETT) model for the Lower Limestone Coast
 
Creator Tanya Doody
 
Subject Tree nutrition and physiology
Photogrammetry and remote sensing
Forestry management and environment
 
Description This dataset contains the monthly evapotranspiration (ET) data at 30 meters spatial resolution from Feb 2000 to Dec 2020 for Lower Limstone Coast, South Australia, specific to plantation forests (Pinus radiata and Eucalyptus globulous) and the extent of mapped forests in the region. The data outputs employ extensive plantation forest in-situ ET data collected by CSIRO (Benyon et al., 2006) and machine learning to create a model that estimates forest ET across the proposed timeseries. The approach used to undertake this has been developed recently in the Murray-Darling Basin by Doody et al. (2023), referred to as the AMLETT model (Australia-wide Machine Learning ET for Trees model) which is applicable to use in any location where field tree ET data is available to help train the machine learning processes.
 
Publisher CSIRO
 
Contributor Steve Gao
Richard Benyon
 
Date 2023-06-01
 
Type —
 
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Identifier csiro:56968
 
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