Morel, Julien
- French Agricultural Research Centre for International Development (Cirad)
Abstract
Coupling remotely sensed data with crop model is known to improve the estimation of crop variables by the model. The recalibration coupling approach tends to reduce the differences between observation and simulation by optimizing the value of one of the model's parameter. In this study, we used this approach with a sugarcane model and Crop Water Stress Index calculated using remotely sensed thermal infrared data in order to optimize the value of the root depth parameter thanks to measured and simulated AET/MET ratio. The effect of the root depth recalibration has also been assessed on the yield estimation, which showed good trends with a significant enhancement of the estimated yield.
Keywords
thermal infrared; recalibration; crop model; sugarcane; yield
Published in
IEEE International Geoscience and Remote Sensing Symposium proceedings
2013, pages: 2806-2809
Title: 2013 IEEE International Geoscience & Remote Sensing Symposium : proceedings : July 21-26, 2013, Melbourne, Australia
Publisher: IEEE Computer Society
Conference
2013 IEEE International Geoscience & Remote Sensing Symposium
SLU Authors
UKÄ Subject classification
Agricultural Science
Publication identifier
- DOI: https://doi.org/10.1109/IGARSS.2013.6723407
- ISBN: 978-1-4799-1114-1
Permanent link to this page (URI)
https://res.slu.se/id/publ/89030