Benchmarking and end-to-end considerations for GeoAI-enabled decision-making

Many machine learning, computer vision, artificial intelligence-inspired approaches have been developed to process and analyze voluminous, heterogeneous, and distributed remote sensing data. The success of these effective imagery analytics has the potential to enable us end-to-end applications. However, determining the most effective data and algorithms remains challenging. Therefore it is crucial to have appropriate benchmarking methods and designs to ensure the effective adaptation of GeoAI systems and to leverage the rich remote sensing data for various applications. This chapter discusses recent developments and challenges (data, metrics, protocol-related) in benchmarking for GeoAI systems. We also highlight important considerations to support and maximize the impact of GeoAI benchmarking.