Big data environment for geospatial data analysis

Geo-information system produces huge and complex geospatial data with the process of collecting real time data through sensors devices. Ground surveying, remote sensing, mobile mapping are the major applications which produces geo-spatial data. There are many other applications like geo-located sensors, geo-tagged web contents, global navigation satellite system(GNSS), volunteered geographic information(VGI) tracking and so on. However, many issues would be answered when we reuse these huge data by applying the traditional data analysis tools. Big data is usually collections of huge data sets with sizes that exceed the storage capacity. This difficulty of storage and advantage of Big data handling tools availability, the data can be captured, managed and processed easily within optimal elapsed time. The hadoop is one of the framework with rich ecosystem which provides the distributed data storage through Hadoop Distributed File System (HDFS) and parallel processing through Map Reduce mechanism.