Automated calibration pipeline for agricultural sUAS based remote sensing

Wade Pines; Ryan LaClair; Chris Willey; Baabak Mamaghani; Carl Salvaggio

doi:10.1117/12.2587495

12 April 2021 Automated calibration pipeline for agricultural sUAS based remote sensing

Wade Pines, Ryan LaClair, Chris Willey, Baabak Mamaghani, Carl Salvaggio

Proceedings Volume 11747, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VI; 117470D (2021) https://doi.org/10.1117/12.2587495
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

The vast majority of agricultural remote sensing applications that utilize multispectral imagery require several pre-processing techniques in order to provide a basis on which to accurately analyze data and provide meaningful information to the grower. This research takes these techniques and compresses them into a fully-automated data processing pipeline. This pipeline is implemented using a BeamIO TileDriver workflow, converting raw digital count to direct-georectified reflectance, ready for further processing to provide a geolocated information product for the grower.

Conference Presentation

Citation Download Citation

Wade Pines, Ryan LaClair, Chris Willey, Baabak Mamaghani, and Carl Salvaggio "Automated calibration pipeline for agricultural sUAS based remote sensing", Proc. SPIE 11747, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VI, 117470D (12 April 2021); https://doi.org/10.1117/12.2587495

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