Combined use of optical and microwave remote sensing data for crop growth monitoring

In this study, optical and microwave remote sensing data were used in combination for crop growth monitoring. A simple reflectance model was used for estimating leaf area index (LAI) from optical data, and a simple backscatter model was used for estimating LAI from radar data. Subsequently, the synergistic effect of using both optical and radar data for estimating LAI was analyzed by studying different data acquisition scenarios. Finally, the remote sensing models were inverted to obtain LAI estimates during the growing season for use in calibrating the crop growth model to actual growing conditions. This concept for crop growth monitoring is elucidated and illustrated with examples using ground-based and airborne data obtained during the MAC Europe 1991 campaign. Results showed that simultaneous optical and radar observations did not improve estimates of LAI over optical data alone. However, for operational applications the assumption of nonsimultaneous observations is more realistic. Results for sugar beet indicated that when periodic (about every ten days) optical recordings are available throughout most of the growing season, LAI can be monitored well and a good estimate of sugar beet yield at the end of the season is possible by using a calibrated crop growth model. When only a few recording dates with an optical sensor are available, radar recordings at L-band HH polarization or C-band W polarization gave a slight improvement of the results of crop monitoring and yield estimation compared with the optical data alone. In the absence of optical remote sensing data, radar data yielded a significant improvement in yield estimation compared with the case of no remotely observed information. This confirmed that the main advantage of radar lies in acquiring information on crop growth when other techniques (in particular optical techniques) fail.