Advancing Bird Distribution Modeling with Satellite Imagery

This chapter examines the innovative use of satellite imagery for predicting bird species encounter rates, moving beyond traditional habitat classification. It highlights the SatBIRD dataset, the integration of satellite and environmental data, and modeling techniques like ResNet18, alongside the challenges of data scarcity in regions like Kenya. The discussion underscores the necessity for collaboration between machine learning and ecology to improve conservation efforts and model effectiveness.