Abstract
It is difficult for young farmers to inherit technics from skilled farmers, since the population of farmers is decreasing, and their average age is increasing in Japan. Under this background, it is expected that technology for managing rice fields with little effort using sensor or robot technology. In this study, we selected drone as the platform of remote sensing since a drone is useful for precision farming. The purpose of this study is to support farmers by estimating growth stage of paddy rice by using Deep Learning (CNN) and NDVI (Normalized Difference Vegetation Index) images. In this paper, we compared growth stage classification accuracy using images taken at the different height of the drone.
Published Version
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