[Kuniaki Uto] Estimation of crop vitality based on Tensor decomposition and data fusion of multimodal, multitemporal leaf-scale aerial images

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Kuniaki Uto

Tokyo Institute of Technology
School of Computing
Assistant Professor

Outline

With the development of unmanned aircraft systems that enable low-altitude aerial observations, it is possible to acquire multimodal aerial images of agricultural fields with high temporal and spatial resolutions. The shading distribution of multimodal, multitemporal leaf-scale images depends on various factors, e.g., the characteristics of imagers, illumination conditions, optical characteristics of leaves, and crop structures. In this study, I aim at developing a sustainable method for evaluating the vitality of crops that is not affected by observation conditions. The vitality is evaluated based on the optical characteristics of leaves and crop structures that are precisely estimated by Tensor decomposition and data fusion of multimodal, multitemporal leaf-scale aerial images of crops.

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