The coarse resolution arable land and crop yield statistics at state level or country level were often used in most of former research of crop yield estimation for other overseas countries and regions with remote sensing in China. In view of this above research status,taken corn yield estimation with remote sensing in USA as an example,the method of crop yield estimation based on higher resolution crop-specific maps,county-level statistic data and MODIS NDVI time series data was explored in this paper in order to further improve the accuracy and refinement level of crop yield estimation research results. Firstly,corn maps with higher spatial resolution of multiple years were acquired from Cropland Data Layer（ CDL） produced annually by the National Agricultural Statistics Service（ NASS） of United States Department of Agriculture（ USDA）. Taken the above crop-specific maps as mask image respectively,mean NDVI value of corn in each main growth stage of every year was calculated in each county. Then,taken each state as a corn yield estimation region respectively,relationship between mean NDVI of corn in each critical growth stage and statistic county-level crop yield data was built up in each state. Thirdly,according to the fitting degree between NDVI and crop yield in each growth stage of corn,the best time and best model of corn yield estimation in each state was selected out. Finally,corn yield of each state was calculated depending on the best crop yield estimation model and the mean NDVI of corn in each county and corn yield at national level was gotten through aggregating the corn yield of each state. Accuracy validation of each state and whole country were carried out. Among them,data in the year from 2007 to 2010 were used to build the models and data of the year of 2011 was used as validation data. It was shown that Relative Error（ RE） of corn yield estimation in each state in the year of 2011 was between- 4. 16% and 4. 92% and that Root Mean Square Error（ RMSE） was between 148. 75 kg / ha and 820. 93 kg / ha and that the RE of the corn yield estimation at national level was only 2. 12% and RMSE was only 285. 57 kg / ha. We could draw the conclusion that method of crop yield estimation based on crop-specific maps,county-level statistic data and MODIS NDVI time series data was reasonable and feasible and could estimate crop yield more accurately in larger overseas region.

remote sensing;crop yield estimation;corn;crop-specific map;NDVI;statistic data