Paddy Rice Mapping using Deep ResU-Net CNN Segmentation

DOI:10.4121/21764192.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/21764192

Datacite citation style

Onojeghuo, Alex (2022): Paddy Rice Mapping using Deep ResU-Net CNN Segmentation. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21764192.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Usage statistics

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171
downloads

Geolocation

Alberta, Canada

Licence

CC0

Interoperability

The main objective of this study was to develop a workflow for paddy rice field mapping using a combination of high spatial and temporal optical and radar satellite data in a deep-learning residual CNN model.

History

  • 2022-12-28 first online, published, posted

Publisher

4TU.ResearchData

Format

Acrobat pdf

Organizations

Jolexy Environmental Services Limited

DATA

Files (2)