Identifying the Impact of Regional Meteorological Parameters on US Crop Yield at Various Spatial Scales Using Remote Sensing Data

This study investigates the influence of meteorological parameters such as temperature and precipitation on gross primary production (GPP) in continental United States (CONUS) during boreal summer using satellite-based indices GPP data at various scales (i.e., pixel, county, state levels). The strong linear relationship between is presented around central States, particularly Great Plains, where year-to-year variation very sensitive to conditions. mostly attributable semi-arid climate crop productivity are closely related. more specific information for regionality relationships across variables manifests itself higher resolutions. impact condition annual yield significant. Maize soybean yields show a correlation with both Temperature Condition Index (TCI) Precipitation (PCI) relatively TCI than PCI, which consistent compared GPP. suggests that in-depth investigations into maize required. region-dependent conditions our would guide agricultural decision making future climate.