Soybean yield estimation using HJ-1 CCD data in Northeast China

In this study, soybean biomass was estimated using HJ-1 CCD data, combined with a radiation use efficiency model. HJ-1 CCD data provide time-serial parameters, with which we can get the information that describe the growth process of soybean, so inputted these information into a biomass model with the real time meteorological data, and then we could get the biomass. And then a fix value of harvest index (HI) was used to calculate the soybean yield. The results were validated with ground measure data. The coefficients of determination R2 is 0.425, and the average fractional differences between estimated and observed yield of soybean is 29.73%. We concluded that estimation with remote-sensing data, such as the HJ CCD data that have a high spatial resolution and a shorter revisit cycle, can show more detail in its spatial patterns and improve the application of remote sensing on a local scale. The potential also exists for applying the approach to many other studies, including agricultural production estimation, crop growth monitoring, and agricultural ecosystem carbon cycle studies.