Poster
in
Workshop: NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning: Blending New and Existing Knowledge Systems
Top-down Green-ups: Satellite Sensing and Deep Models to Predict Buffelgrass Phenology
Lucas Rosenblatt · Bin Han · Erin Posthumus · Theresa Crimmins · Bill Howe
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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