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Data · dataset · 2023

Global Highly Generalized Land Evapotranspiration Dataset (HG-Land v1.0)

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The global Highly Generalized Land Evapotranspiration (ET) dataset (HG-Land v1.0) employs the state-of-the-art Deep Forest machine-learning algorithm, incorporating meteorological and vegetation variables as input data.

Description

The HG-Land dataset provides global monthly estimations, measured in W/m2, with a spatial resolution of 0.5°. It covers the period from January 1982 to December 2018.

The data is stored in a network Common Data Form (netCDF) format, conveniently within a single file. This file comprises five variables: time, longitude, latitude, ET, and ET standard deviation.

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Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.1051912 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:earth-environmentalmapping · scidb cnconnector:scidb_cn@1.0.0
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