ADOPTION OF HADOOP FOR A REMOTE SENSING REAL TIME BIG DATA ANALYSIS

Abstract

In this paper we proposed that How Real time Big data can be managed for remote sensing application using
Hadoop as a tool.Managing Big data is one of the biggest problem,its a new turn to the cost oriented companies by
managing huge volume of data, velocity and variety of information. The real-time Big data for remote sensing
application looks easy at first, but the useful data extraction in a effective manner gives the system towards a enormous
computational challenges, they are analyzing, aggregating, and storing, here information are remotely gathered.
Keeping in view that the above said points; designing such a system which calls for a both offline, as well as online
processing of data needed. That’s why, in this paper, we discuss real-time Big Data for remote sensing satellite
application using hadoop as a tool. In the Architecture it has three main blocks, they are 1) remote sensing Big Data
acquisition unit (RSDU); 2) data processing unit (DPU); 3) data analysis decision unit (DADU).Firstly, RSDU will
collect data from the satellite and transmit this data to the Base Station, where starting task process takes place. Later
DPU plays an important role in architecture for effective processing of real-time Big Data by providing filtration, load
balancing, and parallel processing. Then DADU is responsible for storage of the results, and generation of decision
based on the results received from DPU. The Design has the power of dividing, load balancing, and parallel processing
of only useful data. Thus, it results in efficiently analyzing real-time remote sensing Big Data using earth observatory
system. Finally,a detailed analysis of remotely sensed earth observatory Big Data for land and sea area are provided
using Hadoop as tool.