Integrating Remote Sensing and Weather Variables for Yield Forecasting of Horticultural Tree Crops – A Case Study of Mango in Ghana and Australia - Dataset

Title
Integrating Remote Sensing and Weather Variables for Yield Forecasting of Horticultural Tree Crops – A Case Study of Mango in Ghana and Australia - Dataset
Publication Date
2023
Author(s)
Robson, Andrew
( supervisor )
OrcID: https://orcid.org/0000-0001-5762-8980
Email: arobson7@une.edu.au
UNE Id une-id:arobson7
Brinkhoff, James
( supervisor )
OrcID: https://orcid.org/0000-0002-0721-2458
Email: jbrinkho@une.edu.au
UNE Id une-id:jbrinkho
Sinha, Priyakant
( supervisor )
OrcID: https://orcid.org/0000-0002-0278-6866
Email: psinha2@une.edu.au
UNE Id une-id:psinha2
Rahman, Muhammad
( supervisor )
OrcID: https://orcid.org/0000-0001-6430-0588
Email: mrahma37@une.edu.au
UNE Id une-id:mrahma37
Torgbor, Adjah Benjamin
Type of document
Dataset
Language
en
Entity Type
Publication
Publisher
University of New England
Place of publication
Armidale, Australia
DOI
10.25952/52x6-gr48
UNE publication id
une:1959.11/62791
Abstract
Extracted time series satellite remote sensing (RS) data in an excel table with column names describing the content of the observations in rows. It also include figures and results tables from the analysis conducted in the research. The data excludes the actual yield data obtained from mango growers in the study locations of which sharing is not permitted. The satellite RS data was used in relation with the actual yield data to develop the time series yield models.
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