Detecting and measuring fine-scale urban tree canopy loss with deep learning and remote sensing

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dc.contributor.authorPedley D
dc.contributor.authormorgenroth, justin
dc.contributor.authorPearse G
dc.date.accessioned2024-09-23T03:09:15Z
dc.date.available2024-09-23T03:09:15Z
dc.date.issued2024
dc.identifier.citationPedley D, Morgenroth J, Pearse G (2024). Detecting and measuring fine-scale urban tree canopy loss with deep learning and remote sensing. Rotorua, New Zealand: ForestSAT. 09/09/2024-13/09/2024.
dc.identifier.urihttps://hdl.handle.net/10092/107580
dc.rightsAll rights reserved unless otherwise stated
dc.rights.urihttp://hdl.handle.net/10092/17651
dc.subject.anzsrc30 - Agricultural, veterinary and food sciences::3007 - Forestry sciences::300707 - Forestry management and environment
dc.subject.anzsrc46 - Information and computing sciences::4601 - Applied computing::460106 - Spatial data and applications
dc.subject.anzsrc46 - Information and computing sciences::4611 - Machine learning::461103 - Deep learning
dc.titleDetecting and measuring fine-scale urban tree canopy loss with deep learning and remote sensing
dc.typeConference Contributions - Other
uc.collegeFaculty of Engineering
uc.departmentSchool of Forestry
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