Yield maps for everyone - scaling drone models for satellite-based decision support

Abstract

A simple model for converting known field-average yields to within-field yield maps of winter wheat (Triticum aestivum L.) was developed using data collected by a nine-band drone sensor over nine field trials in Sweden in 2019-2020. The model was deployed on Sentinel-2 satellite data, and tested on eight commercial fields. The results were compared against combine harvester yield data and the model was then implemented in a decision support system for precision agriculture. Thus, the pathway from field trial to end-user was shortened by scaling drone models using satellite data. Even if the generated surrogate yield maps can be regarded as more generalised than those that can be obtained from combine harvesters, such maps may be of interest since no special equipment or complex data handling are required.

Keywords

drone; UAV; Sentinel-2; decision support system; yield mapping

Published in

Title: Precision agriculture ’21
Publisher: Wageningen Academic Publishers

Conference

13th European Conference on Precision Agriculture, 18-22 July 2021, Budapest, Hungary

SLU Authors

• Söderström, Mats

  • Department of Soil and Environment, Swedish University of Agricultural Sciences
    

• Persson, Kristin

  • Department of Soil and Environment, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Agricultural Science

Publication identifier

• DOI: https://doi.org/10.3920/978-90-8686-916-9_109
• ISBN: 978-90-8686-363-1
• eISBN: 978-90-8686-916-9

Permanent link to this page (URI)

https://res.slu.se/id/publ/113059