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arXiv · 2310.00740

Top-down Green-ups: Satellite Sensing and Deep Models to Predict Buffelgrass Phenology

Lucas Rosenblatt·Bin Han·Erin Posthumus·Theresa Crimmins·Bill Howe
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Abstract

An invasive species of grass known as "buffelgrass" contributes to severe wildfires and biodiversity loss in the Southwest United States. We tackle the problem of predicting buffelgrass "green-ups" (i.e. readiness for herbicidal treatment). To make our predictions, we explore temporal, visual and multi-modal models that combine satellite sensing and deep learning. We find that all of our neural-based approaches improve over conventional buffelgrass green-up models, and discuss how neural model deployment promises significant resource savings.

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Lucas Rosenblatt, Bin Han, Erin Posthumus, Theresa Crimmins, Bill Howe. 2023-10-01. Top-down Green-ups: Satellite Sensing and Deep Models to Predict Buffelgrass Phenology. https://arxiv.org/abs/2310.00740

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