Advances in crop health monitoring would help farmers use resources more efficiently and accurately. Higher-quality spatiotemporal information on changes in crop characteristics will enable more precise and timely management of crop health, by providing early indication of crop disease outbreaks and enabling site-specific disease management. This chapter explores how current advances in remote sensing can contribute to improve the monitoring of plant health in response to stresses such as disease. A case study demonstrates how very high-resolution remote sensing data from drones, combined with deep learning models, can be used to evaluate stripe rust in the field. The chapter discusses current limitations of remote sensing to provide accurate and specific data on plant health and disease and how these might be addressed.