Remote sensing data for crop yield in CONUS

I) SUMMARY

This database contains harmonized time series for the study of crop yields using remote sensing data and meteorological data. We collected information on soybean, corn, and wheat yields (t/ha) over the CONUS (continuous US) from USDA-NASS for years 2015–2018 at a county level, and collocated time series for the following variables:

• Enhanced Vegetation Index (EVI) from MODIS satellite (MOD13C1 v6 product)
• Soil Moisture (SM) from SMAP satellite through MT-DCA algorithm
• Vegetation Optical Depth (VOD) from SMAP satellite through MT-DCA algorithm
• Maximum temperature (TMAX) from Daymet v3
• Precipitation (PRCP) from Daymet v3

II) CONTACT

For questions, please email Laura Martínez-Ferrer at laura.martinez-ferrer@uv.es

III) DATABASE

For each crop type, we provided CSV files containing the time series of the variables and yield described above. Furthermore, additional information for spatial and temporal identification such as a county identifier and a year are included. Lastly, country-shapefiles (.shp) are added for geospatial representation. Further details in readme.txt file.

IV) CITE

We kindly encourage to cite the following works if this database is used

L. Martínez-Ferrer, M. Piles, G. Camps-Valls, Crop Yield Estimation and Interpretability With Gaussian Processes, IEEE Geoscience and Remote Sensing Letters, 2020, vol. 18, no 12, p. 2043-2047, DOI: 10.1109/LGRS.2020.3016140 

A. Mateo-Sanchis, J. E. Adsuara, M. Piles, J. Muñoz-Marí, A. Pérez-Suay and G. Camps-Valls, "Interpretable Long-Short Term Memory Networks for Crop Yield Estimation," in IEEE Geoscience and Remote Sensing Letters, DOI: 10.1109/LGRS.2023.3244064