Development of a GRIDRPC tool for Satellite Images Parallel Data Assimilation in Agricultural Monitoring

要旨

Recent advances in Data Assimilation of Satellite Imagery for the purpose of Agricultural Monitoring, is leading to increasing requirements of computing power. The use of evolutionary search like the Genetic Algorithm (GA) are specially indeed of large number of iterations to find the global optimum. In this context, the grouping of cluster computers into a nation wide Grid architecture enables researchers to push forward the boundary of capabilities within Agricultural Monitoring research. In this paper we explore a Grid RPC Ninf-G programming framework for data assimilation using GA. Input information is Satellite imagery, evaluation model is Soil Water Air Plant (SWAP) agro-hydrological model and output are SWP crop and water parameters.