REN Jianqiang, CHEN Zhongxin, ZHOU Qingbo, et al. MODIS vegetation index data used for estimating corn yield in USA[J]. Journal of Remote Sensing, 2015,19(4):568-577.
REN Jianqiang, CHEN Zhongxin, ZHOU Qingbo, et al. MODIS vegetation index data used for estimating corn yield in USA[J]. Journal of Remote Sensing, 2015,19(4):568-577. DOI: 10.11834/jrs.20154146.
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.
关键词
遥感估产玉米作物分布NDVI统计数据
Keywords
remote sensingcrop yield estimationcorncrop-specific mapNDVIstatistic data