Recalibrating a sugarcane crop model using thermal infrared data

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
ISBN: 978-1-4799-1114-1
Publisher: IEEE Computer Society

Conference

2013 IEEE International Geoscience & Remote Sensing Symposium

UKÄ Subject classification

Agricultural Science


Publication identifier

DOI: https://doi.org/10.1109/IGARSS.2013.6723407

Permanent link to this page (URI)

https://res.slu.se/id/publ/89030