Comparative canopy cover estimation using RGB images from UAV and ground

Jose A. Fernandez-Gallego; Shawn C. Kefauver; Samir Kerfal; José L. Araus

doi:10.1117/12.2501531

10 October 2018 Comparative canopy cover estimation using RGB images from UAV and ground

Jose A. Fernandez-Gallego, Shawn C. Kefauver, Samir Kerfal, José L. Araus

Proceedings Volume 10783, Remote Sensing for Agriculture, Ecosystems, and Hydrology XX; 107830J (2018) https://doi.org/10.1117/12.2501531
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

Canopy cover is an important agronomical component for determining grain yield in cereals. Estimates of the canopy cover area of crops may contribute to improving the efficiency of crop management practices and breeding programs. Conventional high resolution RGB cameras can be used to acquire zenithal images taken at ground level or from a UAV (Unmanned Aerial Vehicle). Canopy-image segmentation is complicated in field conditions by numerous factors, including soil, shadows and unexpected objects. Spatial resolution is a key factor for estimating canopy cover area because low spatial resolution may introduce artifacts in the digital image. We propose a comparison of canopy cover segmentation using different spatial resolutions to test the scalability potential of these different techniques. Field trials were carried out during the 2015/2016 crop season in the Arazuri experimental station of INTIA in Navarra, Spain. Three barley genotypes, 10 different N fertilization regimens and three replicates were used in this study. This work uses zenithal RGB images taken from 1 m above the crop and images from the UAV were taken at the intervals of 2 s the during of the flight at distances of 25, 50 and 100 m. Images from the ground were taken at 1 m above the canopy. The CerealScanner plugin for FIJI (Fiji is Just ImageJ) was used to calculate the BreedPix RGB vegetation indices. The comparative results demonstrate the algorithm’s effectiveness in scaling through high correlation values between images with different spatial resolutions taken from the UAV and images taken from the ground.

Conference Presentation

Citation Download Citation

Jose A. Fernandez-Gallego, Shawn C. Kefauver, Samir Kerfal, and José L. Araus "Comparative canopy cover estimation using RGB images from UAV and ground", Proc. SPIE 10783, Remote Sensing for Agriculture, Ecosystems, and Hydrology XX, 107830J (10 October 2018); https://doi.org/10.1117/12.2501531

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