Estimation of Maize Yield in Yitong County Based on Multi-source Remote Sensing Data from 2007 to 2017

With the development of remote sensing technology, the utilizations of multi-spatial and multispectral resolution remote images have proved to be very important in monitoring the growth and estimating the yield of agricultural crops. The light energy utilization models using remote sensing have got the wide application because of its simple data acquisition, less parameters and capabilities for time series analysis. In this research, the yield estimation has been carried out using the net primary productivity (NPP) and the contents of soil organic matter which are obtained by Carnegie-Ames-Stanford approach (CASA) model and our proposed approach respectively. More specifically, NPP of maize in the study area from 2007 to 2017 was estimated using CASA model, and the characters of spatio-temporal variation were explored. After that, the retrieval model of the soil organic matter content was established based on the relationship analyzation between the soil organic content and NPP. The characters of spatio-temporal variation also have been explored. Then the yield of spring maize in Yitong County from 2007 to 2017 was estimated using an improved yield estimation model. Moreover, the maize harvest index and the yield of maize per unit area in the study area were obtained. Finally, the growth and development information of maize in Yitong County were comprehensively evaluated combining with these mentioned data.