Synthesizing Forestry Images Conditioned on Plant Phenotype Using a Generative Adversarial Network

Plant phenology and phenotype prediction using remote sensing data is increasingly gaining the attention of the plant science community to improve agricultural productivity. This work aims to generate synthetic forestry images that satisfy certain phenotypic attributes, viz. canopy greenness. We harness a Generative Adversarial Network (GAN) to synthesize biologically plausible and phenotypically stable forestry images conditioned on the greenness of vegetation (a continuous attribute) over a specific region of interest (describing a particular vegetation type in a mixed forest). The …

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