Regional Rice Yield Estimation by Integration of Spatial Technologies and Crop model

Abstract

This study investigates how spatial technologies like remote sensing and GIS (Geographic Information System) integrated with a crop growth model to estimate paddy rice yields. Two approaches were used to estimate rice yield one is from remote sensing images and another from soil, climate layers of GIS, linked to the crop model. Oryza2000 model was used as a crop model to link with these technologies. Results show that yield estimated from these two approaches were closed to the reported values from department of Agriculture, Andhra Pradesh, India and yield estimated from remote sensing is more precise than GIS layers. This underscores the potential value of remote sensing, GIS and crop model for yield estimation. The successful application of methodology used in our study to other areas will depend on number of factors including the secondary data estimates, distribution of different crops grown in that area, crop condition at the time of satellite overpass and land scene anomalies.