Remote sensing-based precision agriculture tools for the sugar industry : SRDC Final report DPI021
dc.contributor | Queensland Department of Agriculture, Fisheries and Forestry | |
dc.contributor | University of New England | |
dc.contributor | Precision Agriculture Research Group | |
dc.contributor | CSIRO Ecosystem Sciences | |
dc.contributor.author | Robson, A | |
dc.contributor.author | Abbott, C | |
dc.contributor.author | Bramley, R | |
dc.contributor.author | Lamb, D | |
dc.date.accessioned | 2013-09-26T01:35:32Z | |
dc.date.available | 2013-09-26T01:35:32Z | |
dc.date.issued | 2013 | |
dc.description.abstract | This project aimed to develop remote sensing applications that were both relevant and of commercial benefit to the Australian sugar industry and therefore adoptable. Such applications included the in season mapping of crop vigour so as to guide future management strategies, the identification of specific abiotic and biotic cropping constraints, and the conversion of GNDVI variability maps into yield at the block, farm and regional level. In order to achieve these applications the project team reviewed an array of remote sensing platforms, timing of imagery capture, software and analysis protocols; as well as distribution formats of derived imagery products, to a range of end users. The project developed strong collaborative linkages with all levels of the industry including mills, productivity services, agronomists, growers and researchers and increased its initial coverage from three individual farms in Bundaberg, Burdekin and the Herbert, coinciding with project CSE022, to include over 33,000 crops grown across 6 growing regions (Mulgrave, Herbert, Burdekin, Bundaberg, ISIS and Condong) during the 2011/2012 season. | |
dc.identifier.uri | http://hdl.handle.net/11079/12504 | |
dc.language.iso | en | en |
dc.relation.ispartofseries | Internal Report; 2013 DPI021 | |
dc.relation.uri | http://hdl.handle.net/11079/14315 | |
dc.subject | Precision agriculture | |
dc.subject | Imagery assessment | |
dc.subject | Optimum time of image capture | |
dc.subject | Optimal image processing and delivery protocols | |
dc.subject | Remote sensing (RS) technologies | |
dc.subject | Spatial variability | |
dc.subject | Yield prediction | |
dc.subject | Yield maps | |
dc.subject | Generic yield algorithm | |
dc.subject | Optimum time of image capture | |
dc.subject | Spatial technologies | |
dc.subject | Farming systems | |
dc.subject | Production management | |
dc.title | Remote sensing-based precision agriculture tools for the sugar industry : SRDC Final report DPI021 |
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