A CNN-LSTM-based method for crop yield estimation at the county level
A crop and county-level technology, applied in the field of CNN-LSTM-based crop yield estimation at the county level, can solve problems such as little attention to yield prediction, and achieve the effect of improving the accuracy of yield estimation
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[0035] In order to make the purpose, technical solution and advantages of the present invention clearer, the embodiments of the present invention will be further described below in conjunction with the accompanying drawings.
[0036]In the invention, the 15 states in the middle of the United States are taken as the case area, based on the remote sensing data and historical production data from 2003 to 2015 as the data source, the soybean production in the area from 2011 to 2015 is estimated, and the estimated results are compared with the real ones. Compare with official figures.
[0037] Selection of production areas to be estimated: According to the soybean planting distribution announced by the United States Department of Agriculture (USDA), soybeans are grown in 31 states. In this case, 15 states are selected as examples, including North Dakota, South Dakota, Nebraska California, Minnesota, Iowa, Kansas, Missouri, Arkansas, Mississippi, Tennessee, Illinois, Indiana, Ohio, ...
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