Remote sensing (RS) has revolutionized modern agriculture by delivering timely, accurate, and scalable data to enhance decision-making in crop production and land management. In this chapter, we provide a comprehensive overview of the applications of remote sensing in modern agriculture structured into four core domains: crop monitoring, precision agriculture, crop health assessment, land use and land management. Initially, we summarized the fundamental knowledge of remote sensing including types of sensors, platforms and principle followed by applications. In crop monitoring, we covered how unmanned air vehicles (UAVs) based sensors facilitate the tracking of crops growth stages, yield forecasting and spatiotemporal variability analysis. RS has enabled the precision agriculture to site specific interventions like variable rate input application, irrigation scheduling, and soil nutrient mapping. Research focused on enhanced field boundary detection, land cover classification, and sustainable resource planning has helped in land use and natural resource management. Crop health management harnesses RS in early disease outbreak detection, weed management, pest and disease surveillance. Additionally, we have discussed how RS coupled with approaches and technologies like artificial intelligence (AI), machine learning (ML), big data, mobile apps and ground-based sensors enhances data utility. The chapter also addresses the limitations, future opportunities and policy recommendations. This chapter provides a broader overview of the applications of RS in modern agriculture, offering recommendations to support farmers and policy makers to promote sustainable agricultural management.