PREDICTING SUGARCANE YIELDS IN KHUZESTAN USING A LARGE TIME-SERIES OF REMOTE SENSING IMAGERY REGION
PREDICTING SUGARCANE YIELDS IN KHUZESTAN USING A LARGE TIME-SERIES OF REMOTE SENSING IMAGERY REGION
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Publisher
Gottingen: Copernicus GmbH
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Language
English
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Publisher
Gottingen: Copernicus GmbH
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Contents
This study aimed to evaluate the power of various vegetation indices for sugarcane yield modelling in Shoeibeyeh area in Khuzestan province of Iran. Seven indices were extracted from satellite images and were then converted to seven days' time-series via interpolation. To eliminate noise from the time-series data, all of them were reconstructed usi...
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Full title
PREDICTING SUGARCANE YIELDS IN KHUZESTAN USING A LARGE TIME-SERIES OF REMOTE SENSING IMAGERY REGION
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TN_cdi_doaj_primary_oai_doaj_org_article_cd5b25f159b943a9b44a419c6c15084a
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_cd5b25f159b943a9b44a419c6c15084a
Other Identifiers
ISSN
2194-9034,1682-1750
E-ISSN
2194-9034
DOI
10.5194/isprs-archives-XLII-4-W18-645-2019
