RealBDA: A REAL TIME BIG DATA ANALYTICS FOR REMOTE SENSING DATA BY USING MAPREDUCE PARADIGM

Enormous data generated by Satellite sensors, Storage and Processing of Remote Sensing Data is a challenging task due to its variety and volume. This paper studied on real-time Big Data Analytical architecture for remote sensing satellite application. To handle Remote Sensing Data proposed architecture comprises three main units, such as Data Pre-Processing Unit (D_PREU), Data Analysis Unit (D_AU) and Data Post-Processing Unit (D_POSTU). First, D_PREU acquires the required data from satellite sensors by using filtration, balanced distributed storage and parallel processing using Hadoop environment. Second, D_AU identifies the hidden patterns from data stored in distributed File System using Map functions followed by Reduce functions in Map-Reduce paradigm. Finally, D_POSTU is the upper layer unit of the proposed architecture, which is responsible for compiling storage of the results, and generation of decision based on the results received from D_AU.