Temporal Vine Water Status Modeling Through Machine Learning Ensemble Technique and Sentinel-2 Multi...
Temporal Vine Water Status Modeling Through Machine Learning Ensemble Technique and Sentinel-2 Multispectral Images Under Semi-Arid Conditions
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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Contents
New challenges will be experienced by the agriculture sector in the near future, especially due to the effects of climate change. For example, rising temperatures could result in increased evapotranspiration demand, causing difficulties in the management of irrigation practices. Generally, an important predictor of plant water status to be taken in...
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Full title
Temporal Vine Water Status Modeling Through Machine Learning Ensemble Technique and Sentinel-2 Multispectral Images Under Semi-Arid Conditions
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TN_cdi_doaj_primary_oai_doaj_org_article_479cbca8d55a4e4fa3ad10db23748796
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_479cbca8d55a4e4fa3ad10db23748796
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ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs16244784
