Abstract

Recent evolution is focused on interaction with large amount of datasets and challenges to design analysis technique. To meet these challenges, Big Data Analytics concept emerged which require advance technologies to process large volume of data efficiently by using distributed and parallel file systems and in terms of GIS it is an incipient technology which allows analysis of unstructured large volume datasets to solve complex spatial decision problems. Big Data Analytics enunciated through powerful and distributed framework offered by Apache Hadoop MapReduce. Hadoop and its ecosystem of Big Data technologies offer distributed storage, large scalable data processing platform which facilitate enterprises to build emerging types of data driven applications that are at the heart of their digital strategy. In former study, Indian Biodiversity data repository generates in Geo-RDBMS environment using PostgreSQL and POSTGIS during Biodiversity characterization study. The raster data is published as WMS and WFS standard which allows online query and visualization. The developed system is taking input from users as Shape file upload, WKT as AOI to perform raster based operation using python, GDAL/OGR, JavaScript and execute raster data analysis over the web using PHP and PostGIS. Indian Biodiversity contains large volume of geo-spatial data which can be processed through Big Data Analytics very efficiently. By using spatial data (satellite based primary information, secondary geospatially derived or modelled information and geospatially referenced field sample plots) from Biodiversity Information System (http://bis.iirs.gov.in), Climatic data, Plant species dataset, Biogeography and other datasets will also give valuable input towards climate change study. This study will characterize how to process enormous amount of data into web environment which solicit WPS (Web processing service). WPS specification endues interface rules that standardize inputs and outputs for geospatial processing services on web. Geospatial Data Processing can take advantage of the OGC WPS as web interface to allow for the dynamic deployment of user processes. However, intensive computation is required for processing of large amount of geospatial problem and it can be accomplished through Big Data analytics. High performance computing cluster will be used to configure Apache Hadoop framework for large scale processing to perform intensive computation for spatial data modeling and data required by WPS will available at the server. Considering effectively, the climate change in Indian Biodiversity requires further research to overcome this dilapidation.

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Future Trends and Technologies: Big Data Analytics pro Web Processing Service

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