Estimating safety factor against root lodging using Sentinel-1 data

S. Chauhan, R. Darvishzadeh*, Mirco Boschetti, Sander H. van Delden, A.D. Nelson

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

Lodging in wheat is one of the main constraints limiting yield and grain quality. Accurate information about crop lodging susceptibility during the growing season is critical for improving yield estimates and for targeting the expenditure on lodging control. In this context, this study aims to estimate safety factor against root lodging (SFA) as a measure of lodging susceptibility by exploiting Sentinel-1 data using Extreme Gradient Boosting Regression. Through extensive field experiments during a crop season, several crop variables were collected from several plots in multiple visits, and the corresponding metrics were extracted from the Sentinel-1 images. Our results show that the field measured SFA correlated well with the field lodging and the cross-validated regression model could estimate SFA with an R2cv = 0.73 and RMSEcv = 0.59. Thus, the SFA measure constitutes a state-of-the-art approach in the remote sensing community for the assessment of root lodging susceptibility.
Original languageEnglish
Pages1-3
Number of pages3
Publication statusPublished - 12 Jul 2021
EventIEEE- International Geoscience and Remote Sensing Symposium- IGARSS 2021 - Brussels
Duration: 12 Jul 202116 Jul 2021
https://igarss2021.com

Conference

ConferenceIEEE- International Geoscience and Remote Sensing Symposium- IGARSS 2021
Period12/07/2116/07/21
Internet address

Fingerprint

Dive into the research topics of 'Estimating safety factor against root lodging using Sentinel-1 data'. Together they form a unique fingerprint.

Cite this