Data

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

University of New England, Australia
Robson, Andrew ; Brinkhoff, James ; Sinha, Priyakant ; Rahman, Muhammad ; Torgbor, Adjah
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25952/52x6-gr48&rft.title=Integrating Remote Sensing and Weather Variables for Yield Forecasting of Horticultural Tree Crops – A Case Study of Mango in Ghana and Australia - Dataset&rft.identifier=10.25952/52x6-gr48&rft.publisher=University of New England&rft.description=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.&rft.creator=Robson, Andrew &rft.creator=Brinkhoff, James &rft.creator=Sinha, Priyakant &rft.creator=Rahman, Muhammad &rft.creator=Torgbor, Adjah &rft.date=2023&rft_rights=Rights holder: AARSC, UNE&rft_subject=Photogrammetry and remote sensing&rft_subject=Geomatic engineering&rft_subject=ENGINEERING&rft_subject=Expanding knowledge in the agricultural, food and veterinary sciences&rft_subject=Expanding knowledge&rft_subject=EXPANDING KNOWLEDGE&rft.type=dataset&rft.language=English Access the data
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Rights holder: AARSC, UNE

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mrahma37@une.edu.au

Full description

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.

Notes

Funding Source
Australian Government Department of Agriculture and Water Resources Horticulture Innovations Australia Ltd. Remote Sensing Scholarship from AARSC, UNE

Issued: 2023

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Subjects
Engineering | Expanding Knowledge | Expanding Knowledge | Expanding Knowledge in the Agricultural, Food and Veterinary Sciences | Geomatic Engineering | Photogrammetry and Remote Sensing |

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handle : https://hdl.handle.net/1959.11/60293

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