He, X, Jing, YS, Gu, XH, Huang, WJ (2010). A Province-Scale Maize Yield Estimation Method Based on TM and Modis Time-Series Interpolation. SENSOR LETTERS, 8(1), 2-5.
Crop yield estimation has always been important for social and government departments. This study was supported by six TM images in different growth period and a MODIS image which was stacked by eight 16-day NDVI images and covered the whole growth period of the maize in Shandong province in 2008. Through gaining the standards time-series growth curve of maize NDVI from MODIS image, we built the interpolated model which represented the maize characteristic growth, and then interpolated the TM images at different growth period into milky stage by using this model. Based on the medium-resolution data setting at milky stage and ground measured data, we built ground-medium resolution linear regression model and medium-low resolution multiple linear regression model for maize yield estimation. The results showed that the accuracy of every city yield was high, completely more than 95%; and the accuracy of entire province production is 94%. This study attempted to carry out a business running system for province-scale maize yield estimation by remote sensing.