Global crop growth condition monitoring and yield trend prediction with remote sensing

Remote sensing can be used for crop growth condition monitoring and yield prediction at global scale. Meteorological model and agricultural model are both deficient without adequate ground observations, but remote sensing model can give more accurate and perfect results. This paper did a case study on the method for maize growth condition monitoring and yield trend prediction in American based on SPOT-VGT data, as well as rice in India. The study suggests that SPOT-VGT/NDVI and SPOT-VGT/EVI with the spatial resolution of 1 km can both be used for operational global crop growth monitoring and yield prediction. The method for yield trend prediction can give the accuracy as high as 100%. In the most luxuriant period SPOT-VGT/EVI can give more exact information of crop growth condition than SPOT-VGT/NDVI.