###### Abstract  
Winter wheat is a main cereal crop grown in the United States of America (USA), and the USA is the third largest wheat exporter globally. Timely and reliable in-season forecast and year-end estimation of winter wheat grain production in the USA are needed for regional and global food security. In this study, we assessed the consistency between the agricultural statistical reports and satellite-based data for winter wheat over the contiguous US (CONUS) at both the county and national scales. First, we compared the planted area estimates from the National Agricultural Statistics Service (NASS) and the Cropland Data Layer (CDL) from 2008-2018. Second, we investigated the relationship between gross primary production (GPP) estimated by the vegetation photosynthesis model (VPM) and grain production from the NASS. Lastly, we explored the in-season utility of GPPVPM in monitoring seasonal production. Strong spatiotemporal consistency of planted areas was found between the NASS and CDL datasets. However, in the Southern Great Plains, both the CDL and NASS planted acreage were noticeable larger (\(>\)20%) than the NASS harvested area, where some winter wheat fields were used as forage for cattle grazing. County-level GPPVPM was linearly related with grain production of winter wheat, with an R\({}^{2}\) value of 0.68 across the CONUS. The relationships between grain production and GPPVPM in those counties without a substantial difference (\(<\)20%) between planted and harvested area were much stronger and their harvest index (HI\({}_{\text{CPP}}\)) values ranged from 0.2-0.3. GPPVPM in May could explain about 70-90% of the variance of winter wheat grain production. Our findings highlight the potential of GPPVPM in winter wheat monitoring, especially for those high harvested/planted ratio, which could provide useful data to guide planning and marketing for decision makers, stakeholders, and the public. winter wheat; crop production; harvested area; planted area; gross primary production; vegetation photosynthesis model +
Footnote †: journal: Remote Sensing  
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[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Spatiotemporal Changes of Winter Wheat Planted and Harvested Areas, Photosynthesis and Grain Production in the Contiguous United States from 2008-2018. _Remote Sens._**2021**, _13_, _1735_. [[https://doi.org/10.3300/rs13091735](https://doi.org/10.3300/rs13091735)]([https://doi.org/10.3300/rs13091735](https://doi.org/10.3300/rs13091735))
on the international wheat trade and global food security. Therefore, timely, reliable, and spatially explicit information on winter wheat planted and harvested areas, grain yield, and production are critical for regional and global food security as well as international food trade. The agricultural surveys and statistical reports by governmental agencies have been the major data sources for crop acreages (including planted and harvested area), grain yield, and grain production for each year from county to national scales [4; 5; 6; 7]. The U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) leads the effort for in-season forecast and year-end estimation of grain production of most crops grown in the USA. Each year, the NASS conducts several surveys and extensive field observations to collect a variety of data needed to fulfill this task [6; 7]. Spatially, an efficient sample design is usually required for agricultural surveys to provide crop estimates over regions. However, the sampling fields only covers part of the intended region. Temporally, it takes time for the government to gather and process the survey data and, for information confidentiality, the agricultural survey data usually have a scheduled release. There are no reports or data available between the scheduled releases. Thus, agricultural surveys are usually time consuming, expensive, and have spatial and temporal gaps [8].