11 October 2014 Estimation of corn and soybeans yield using remote sensing and crop yield data in the United States
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Abstract
The crop yield estimation is essential for the food security and the economic development of any nation. Particularly, the United States is the world largest grain exporter, and the total amount of corn exported from the U.S. accounted for 49.2% of the world corn trade in 2010 and 2011. Thus, accurate estimation of crop yield in U.S. is very significant for not only the U.S. crop producers but also decision makers of food importing countries. Estimating the crop yield using remote sensing data plays an important role in the Agricultural Sector, and it is actively discussed and studied in many countries. This is because remote sensing can observe the large areas repetitively. Consequently, the use of various techniques based on remote sensing data is steadily increasing to accurately estimate for crop yield. Therefore, the objective of this study is to estimate the accurate yield of corn and soybeans using climate dataset of PRISM climate group and Terra/MODIS products in the United States. We construct the crop yield estimation model for the decade (2001-2010) and perform predictions and validation for 2011 and 2012.
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Nari Kim, Yang-Won Lee, "Estimation of corn and soybeans yield using remote sensing and crop yield data in the United States", Proc. SPIE 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI, 92390Y (11 October 2014); doi: 10.1117/12.2067311; https://doi.org/10.1117/12.2067311
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