Early season crop acreage estimation is commonly conducted using crop information collected through large scale agricultural surveys to identify farmers’ planting intentions and decisions. Due to the increased frequency and impact of extreme weather events on agriculture, there is significant interest in developing remote sensing techniques for crop acreage estimation early in the growing season. This paper proposes a new method to produce early season crop acreage estimates for the State of Illinois, United States (U.S), from 2016 to 2019. A geospatial layer of early season crop classifications, known as an Early Season Cropland Data Layer (ESCDL), is created using crop rotation patterns derived from historic USDA National Agricultural Statistics Service (NASS) Cropland Data Layers and current year (March 6 – June 10) satellite imagery. The ESCDL crop specific acreage, derived through pixel counts, are combined with NASS June Area Survey data to obtain unbiased corn and soybean estimates in early June. The ESCDLs are validated using end-of-season Farm Service Agency Common Land Unit and 578 administrative data and have producer and user accuracies from 79.48% to 86.31% for corn, 74.61% to 86.21% for soybeans, and - 4 % to 6 % relative errors when compared to final NASS official estimates.