** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** SATELLITE DATA AVAILABILITY IS A KEY COMPONENT IN MODERN AGRICULTURE. HOWEVER, CURRENT ACCESS TO SATELLITE DATA AND TOOLS FOR FARMERS IS LIMITED AND UNEQUAL, AND NUMEROUS ADOPTION BARRIERS, SUCH AS THE HIGH COST OF PROCESSING SOFTWARE AND INFORMATIONAL GAPS (E.G., LIMITED KNOWLEDGE OF EFFECTIVE INTERPRETATION AND UTILIZATION OF SATELLITE DATA) PREVENT THIS PROMISING TECHNOLOGY FROM BEING INTEGRATED INTO FARMERS' DECISION-MAKING AND OPERATIONAL PROCESSES. THIS PROJECT AIMS TO PROTOTYPE THE FIRST FARM-SCALE AGRICULTURE MONITORING SYSTEM USING A SATELLITE CONSTELLATION PRODUCT THAT WILL RESULT IN A NEW WEB-BASED PORTAL (CROPVISTA) THAT TRACKS CROP GROWTH AND METEOROLOGICAL CONDITIONS TO SUPPORT U.S. FARMERS ACROSS 17 STATES. THIS RESEARCH AND DESIGN WILL USE COMPLEX DATA SCIENCE CONCEPTS TO AUTOMATE SATELLITE IMAGE PROCESSING AND DELIVER READILY INTERPRETABLE CROP CONDITION INSIGHTS, SUCH AS THE EVOLUTION OF THE GROWING SEASON AND CROP PHENOLOGY METRICS. THE PROJECT TEAM WILL: (1) IMPLEMENT A CROP FIELD BOUNDARY DETECTION FROM ENHANCED 2.5-M SENTINEL IMAGERY USING DEEP LEARNING, (2) EXTRACT FIELD-SCALE CROP PHENOLOGY TIME SERIES FROM NASA HARMONIZED LANDSAT-SENTINEL-2 IMAGES, (3) VALIDATE THE CROP PHENOLOGY AND DERIVED METRICS IN DIFFERENT CROP SYSTEMS AT MSU FARMS, (4) DERIVE DATA INSIGHTS FROM CROP PHENOLOGY AND METEOROLOGICAL VARIABILITY, AND (5) PROVIDE A NEW WEB-BASED PORTAL WITH FIELD-SCALE CROP PHENOLOGY AND METEOROLOGICAL CONDITIONS FOR AGRICULTURAL MANAGEMENT. INCREASING FARMERS' ADOPTION OF THESE RESOURCES CAN SIGNIFICANTLY STRENGTHEN U.S. AGRICULTURAL RESILIENCE USING SATELLITE OBSERVATIONS.