SCYM Maize Yield Maps (Low Resolution) from Deines et al. 2021, Lobell et al. 2020
<p>Annual maize yield maps for the US Corn Belt for 1999-2018, aggregated to 10 km resolution. Yield maps are produced with the SCYM methodology at 30 m resolution using Landsat satellite data. The original high resolution yield maps are aggregated to a 10 km grid resolution to preserve privacy.</p> <p>Dataset creation is described in <a href="https://doi.org/10.1016/j.rse.2020.112174">Deines et al., 2020</a> in Remote Sensing of Environment (open access). The 2008-2018 map dataset described therein was extended back to 1999 for <a href="https://doi.org/10.1038/s43016-020-00165-w">Lobell et al. 2020</a> in Nature Food (<a href="https://rdcu.be/b9cXQ">read-only accessible version</a>). Maps for 2008-2018 use the USDA's Cropland Data Layers to identify maize pixels; maps for 1999-2007 use the Corn-Soy Data Layer produced by <a href="https://www.nature.com/articles/s41597-020-00646-4">Wang et al. 2000</a> (data + manuscript are open access).</p> <p><strong>Metadata</strong></p> <p>Yield values are provided in metric tons/hectare. </p> <p>No Data value = -999 (grid cells outside of the study area + cells with <1% coverage of SCYM 30 m yield maps)</p> <p>Map projection: EPSG:5070, CONUS Albers Equal Area</p> <p> </p> <p> </p> <p>Preferred citation(s):</p> <p>Deines, J.M., R. Patel, S. Lang, W. Dado, & D.B. Lobell. 2020. A million kernels of truth: Insights in to scalable satellite maize yield mapping and yield gap analysis from an extensive ground dataset in the US Corn Belt. <em>Remote Sensing of Environment. </em><a href="https://doi.org/10.1016/j.rse.2020.112174">https://doi.org/10.1016/j.rse.2020.112174</a></p> <p>D.B. Lobell, J.M. Deines, & S. Di Tomasso. 2020. Changes in the drought sensitivity of U.S. maize yields. <em>Nature F</em><em>o</em><em>o</em><em>d</em> 1:729-735. <a href="https://doi.org/10.1038/s43016-020-00165-w">https://doi.org/10.1038/s43016-020-00165-w</a></p> <p> </p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 0
- Engagement
- 4
Topics
Dataset details
- Repository
- zenodo
- Published
- November 10, 2020
- License
- cc-by-4.0
- DOI
- 10.5281/zenodo.4267588
Scored with release 0.9.0
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