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Coupling Fused High Spatio-Temporal Resolution Remote Sensing Data and Crop Modelling to Predict Wheat Yield at the Field Scale

thesis
posted on 10.01.2022, 03:20 by YUVAL SADEH
This study aimed to improve in-season yield predictions by coupling crop modelling and satellite images with a focus on wheat in Australia. Specifically, it has developed a new approach to predict crop yield without ground-calibration data, making it broadly applicable across regions.

History

Campus location

Australia

Principal supervisor

Xuan Zhu

Additional supervisor 1

David Dunkerley

Additional supervisor 2

Jeffrey Walker

Additional supervisor 3

Karine Chenu

Year of Award

2022

Department, School or Centre

Earth, Atmosphere and Environment

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Science