Investigating the potential of satellite imagery for high-throughput field phenotyping applications

Sindhuja Sankaran; Chongyuan Zhang; J. Preston Hurst; Afef Marzougui; Arun Narenthiran Veeranampalayam-Sivakumar; Jiating Li; James Schnable; Yeyin Shi

doi:10.1117/12.2558729

13 May 2020 Investigating the potential of satellite imagery for high-throughput field phenotyping applications

Sindhuja Sankaran, Chongyuan Zhang, J. Preston Hurst, Afef Marzougui, Arun Narenthiran Veeranampalayam-Sivakumar, Jiating Li, James Schnable, Yeyin Shi

Author Affiliations +

Proceedings Volume 11414, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V; 1141402 (2020) https://doi.org/10.1117/12.2558729
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

High throughput phenotyping, including remote sensing, is enabling new approaches to both breeding and precision farming techniques that improve agricultural efficiency. Unmanned aerial vehicles (UAVs) are being widely employed to collect remote sensing data for high throughput phenotyping. This approach provides high image resolution and rapid data acquisition. However, using UAVs to collect remote sensing is a labor-intensive process as a pilot is needed for each flight. As a result, UAV based approaches face challenges in scaling data collection to large field experiments conducted across multiple geographically remote field sites. Remote sensing data collected from satellites has continually to improve with current datasets providing sub-meter spatial resolution and re-visit time as frequent as once per day. Here, we evaluate the feasibility of employing high resolution satellite imagery for phenotyping small-plot plant breeding and agronomic trials. Vegetation indices derived from satellite imagery were compared to those extracted from an UAV-based multispectral camera and the yield in a small-plot (approx. 8 sq. m) maize trial. The preliminary result indicates that there is a strong and significant correlation between data derived from satellite and UAV imagery. Satellite based phenotyping of yield trial plots would enable evaluation of new crop varieties across larger numbers of geographically distinct locations, assisting in the development of more resilient and broadly adapted crops.

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Sindhuja Sankaran, Chongyuan Zhang, J. Preston Hurst, Afef Marzougui, Arun Narenthiran Veeranampalayam-Sivakumar, Jiating Li, James Schnable, and Yeyin Shi "Investigating the potential of satellite imagery for high-throughput field phenotyping applications", Proc. SPIE 11414, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V, 1141402 (13 May 2020); https://doi.org/10.1117/12.2558729

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