114. Sensing management from space: predicting harvest dates
Author:
Affiliation:
1. Precision Agriculture Laboratory, Sydney Institute of Agriculture, School of Life and Environmental Sciences, The University of Sydney, New South Wales, Australia.
Publisher
Wageningen Academic Publishers
Link
https://www.wageningenacademic.com/doi/pdf/10.3920/978-90-8686-947-3_114
Reference11 articles.
1. Exploiting Sentinel-1 data time-series for crop classification and harvest date detection
2. Department of Agriculture, Fisheries and Forestry (DAFF). (2022, December 15). Australian crop report: December edition. https://www.agriculture.gov.au/abares/research-topics/agricultural-outlook/australiancrop-report/overview.
3. Automated Crop Harvest Detection Algorithm Based on Synergistic Use of Optical and Radar Satellite Imagery
4. Google Earth Engine: Planetary-scale geospatial analysis for everyone
5. Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening
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