Combined Use of Polar Orbiting and Geo-stationary Satellites to Improve Time Interpolation in Dynamic Crop Models for Food Security Assessment

Use of satellite data in crop growth monitoring could provide great value for regional food security assessments. By using the difference between remotely sensed crop canopy temperature and the corresponding ambient temperature at the time of the satellite overpass the daily actual rate of transpiration can be inferred. This relationship allows adjustment of the actual rate of assimilation and hence of actual crop growth. Although promising results were obtained using methods based on this premise, the sensitivity of these methods to temporal variability outside the time-window of the satellite overpass is a concern. Based on our findings we show that temporal aspects are indeed not negligible and an improvement in the accuracy of crop productivity assessments can be achieved if data from satellites with different temporal and spatial resolutions are combined. In this study, data from the Advanced Very High Resolution Radiometers (AVHRR) instrument aboard the polar orbiting satellite National Oceanic and Atmospheric Administration #14 (NOAA-14) and data from the Visible Infrared Spin Scan Radiometer (VISSR) instrument onboard the Geostationary Meteorological Satellite #5 (GMS-5) are integrated in a dynamic crop growth simulation procedure. The existing estimation method we used to evaluate our results against solely dependents on data from polar orbiting satellites, which observe the earth surface too infrequently to yield sufficient clear-sky observations (only 24 out of 100 days of the crop cycle were cloud-free). More observations of temperature differences between the crop canopy and ambient air can be obtained when coupled with geo-stationary satellite measurements that represent the diurnal cycle. The linear interpolation procedure applied to obtain proxies for missing days improved accordingly. The results indicate that Storage Organ Mass (SOM) values can be determined from the new method with a higher degree of certainty as compared to the existing method. When evaluated against SOM values as observed at Quzhou, P.R. of China, experimental maize fields, the estimates are within an accuracy of about 150 kg ha1, a relative error of less than 1,8%. This also confirms our hypothesis that observations from geo-stationary satellites as an additional data source, which are more frequently made than measurements from polar orbiting satellites, can be useful to explain temporal dynamics of crop stress to better estimate regional crop productivity. * Corresponding author.