Gambhir Lamsal , Landon Marston

The United States is a major producer and exporter of agricultural goods, fulfilling global demands for food, fiber, and fuel while generating substantial economic benefits. Agriculture in the U.S. not only dominates land use but also ranks as the largest water-consuming sector. High-resolution cropland mapping and insights into cultivation trends are essential to enhance sustainable management of land and water resources. Existing data sources present a trade-off between temporal breadth and spatial resolution, leading to gaps in detailed geographic crop distribution. To bridge this gap, we adopted a data-fusion methodology that leverages the advantages of various data sources, including county-level data from the U.S. Department of Agriculture, along with several gridded land use datasets. This approach enabled us to create annual maps, termed HarvestGRID, of irrigated and harvested areas for 30 key crops across the U.S. from 1981 to 2019 at a resolution of 2.5 arc minutes. We assessed accuracy of HarvestGRID by comparing it with other large-scale gridded cropland databases, identifying both consistencies and discrepancies across different years, regions, and crops. This dataset is pivotal for analyzing long-term cropland use patterns and supports the advancement of more sustainable agricultural practices.