Published October 27, 2025 | Version v1
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Contiguous United States 10m-resolution In-season Crop-type Data Layer 2023 June-August

Authors/Creators

  • 1. ROR icon George Mason University

Description

To address the need for high-resolution, in-season crop planting information, we developed an automated crop-type mapping workflow to produce a new data product: 10-m resolution In-season Crop-type Data Layers (ICDLs) for June, July, and August, available publicly with a delay of only 5–10 days. The workflow extracts trusted pixels from historical CDL data and incorporates Sentinel-2 and Landsat 8/9 observations to conduct supervised time-series classifications. The outputs are assembled using a multilevel mosaicking process to produce the Contiguous U.S. ICDL. Validation of the ICDL product demonstrated its high accuracy. Trusted pixel accuracies ranged from 0.825 to 0.937, while classification accuracies improved from 0.807 in June to 0.984 in August, consistently outperforming the annual CDL. Moreover, ICDL-based acreage estimates for major crops showed close agreement with official USDA National Agricultural Statistics Service (NASS) statistics. The ICDL datasets are publicly available, providing timely, high-resolution crop-type information that can directly support national-scale agricultural monitoring, management, and decision-making.

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