Predicting And Mapping Of Honey Flow From Corymbia Calophylla Trees With Remote Sensing
| dc.contributor.author | Campbell, Tristan | |
| dc.contributor.supervisor | Peter Fearns | en_US |
| dc.date.accessioned | 2020-10-26T07:54:28Z | |
| dc.date.available | 2020-10-26T07:54:28Z | |
| dc.date.issued | 2020 | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/81507 | |
| dc.description.abstract |
The thesis presents research into predicting and mapping seasonal honey production from marri trees (Corymbia calophylla) in Western Australia, which produce some of the highest antimicrobial honey in the world. Through a combination of drone imagery, satellite and weather data and machine learning, a model to predict honey yields to 90% accuracy has been developed as well as several tools to map flower coverage during the honey producing season. | en_US |
| dc.publisher | Curtin University | en_US |
| dc.title | Predicting And Mapping Of Honey Flow From Corymbia Calophylla Trees With Remote Sensing | en_US |
| dc.type | Thesis | en_US |
| dcterms.educationLevel | PhD | en_US |
| curtin.department | School of Earth and Planetary Sciences | en_US |
| curtin.department | Remote Sensing and Satellite Research Group (RSSRG) | en_US |
| curtin.accessStatus | Open access | en_US |
| curtin.faculty | Science and Engineering | en_US |
| curtin.contributor.orcid | Campbell, Tristan [0000-0002-3796-9582] | en_US |