TH2.P3.4
Improved yield forecasting of individual Sugarcane crops using an evolved remote sensing and Machine Learning approach
Moshiur Rahman, Andrew Robson, University of New England, Australia
Session:
TH2.P3: Crop Health and Growth Monitoring II Oral
Track:
Land Applications
Location:
Room P3
Presentation Time:
Thursday, 7 August, 11:15 - 11:30
Presentation
Discussion
Resources
No resources available.
Session TH2.P3
TH2.P3.1: NET PRIMARY PRODUCTIVITY OF CROPLAND SIMULATED USING THE BEPS MODEL
Peng Wang, China University of Mining and Technology, China; Yong Xue, Nanjing University of Information Science & Technology, China; Zhigang Yan, Botao He, Jiahui Qin, Pei Li, China University of Mining and Technology, China
TH2.P3.2: Leaf Nutrient Retrieval Using Hyperspectral Sensing and Machine Learning
Eleni-Ioanna Koutsovili, Consiglio Nazionale delle Ricerche, Italy; Giovanni Lombardo, University of Messina, Italy; Hafsa El Horri, University of Pisa, Italy; Salvatore Maresca, Consiglio Nazionale delle Ricerche, Italy; Damiano Remorini, University of Pisa, Italy; Francesco Longo, University of Messina, Italy; Stefania Matteoli, Consiglio Nazionale delle Ricerche, Italy
TH2.P3.3: Evaluation of EMO1 Gridded Meteorological Data and its Application to Crop GPP Modelling
Rahul Raj, Bagher Bayat, Carsten Montzka, Forschungszentrum Jülich GmbH, Germany
TH2.P3.4: Improved yield forecasting of individual Sugarcane crops using an evolved remote sensing and Machine Learning approach
Moshiur Rahman, Andrew Robson, University of New England, Australia
TH2.P3.5: QUANTIFYING COTTON GROWTH RATE FROM MULTISPECTRAL UAV IMAGERY AT PLOT SCALE
Francesca Devoto, Davoud Ashourloo, Yan Zhao, Ruizhu Jiang, Rakesh Awale, Michael Bell, Tim Mclaren, Sean Reynolds-Massey-Reed, The University of Queensland, Australia; Loren Otto, AirBorn Insight Pty Ltd, Australia; Michael Bange, Cotton Seed Distributors Ltd, Australia; William Woodgate, Scott Chapman, Andries Potgieter, The University of Queensland, Australia
Resources
No resources available.