Satellite-Guided Delineation of Crop Production Zones from Official Crop Statistics for Spatial Agricultural Decision Support

Spatially explicit crop-yield information is needed for regional environmental modeling, sustainability assessment, and agricultural decision support, yet official yield statistics are commonly reported only at aggregated administrative scales. This study introduces the nayd R package, a reproducible geospatial workflow for converting county-level harvested area and yield statistics into spatially explicit production units and zonal clusters while preserving consistency with official records. County-level statistics from the USDA National Agri-cultural Statistics Service were integrated with USDA Cropland Data Layer crop masks, multi-sensor NDVI products, and satellite-derived evapotranspiration from OpenET SSEBop. An NDVI-based eligibility filter refined crop masks toward reported harvested area, while normalized NDVI and evapotranspiration layers were combined into spatial weighting surfaces and aggregated into contiguous production units and graph-based clusters. Case studies for cotton and winter wheat in Texas showed that the eligibility filter removed approximately 20–40% of CDL-classified pixels while maintaining consistency with reported harvested area and preserving plausible spatial gradients associated with ir-rigated and dryland systems. Evaluation against independent Texas A&M AgriLife vari-ety-trial data yielded normalized RMSE values of approximately 11–15% for cotton and 9–12% for winter wheat. The workflow provides an open-source framework for generating statistically consistent production zones for regional crop modeling, environmental as-sessment, and sustainable agricultural planning.