 Remote sensing, R.S., data and advanced machine learning algorithms such as deep learning, DL, have become powerful tools for crop mapping and yield prediction. Recent research has demonstrated the potential of DL-based solutions for accurate crop mapping and yield prediction, but there remain several challenges to be addressed. These include the lack of large-scale training datasets, the need for more efficient and transparent models, and the difficulty of developing generalizable solutions for diverse locations and crops. This article was authored by Abhashya Joshi, Bisbhaji Pradhan, Shilpa Jeet, and others.