Abstract

Over the course of time an organization working with geospatial data accumulates tons of data both in the form of vector and raster formats. This data is a result of co-ordinated processes within the organization and external sources such as other collaborative organizations, projects and agencies, crowd sourcing efforts, etc. The massive amount of data accumulated as a result and the recent developments in the distributed processing of geo-data have catalyzed the development of our spatio-temporal data processing model. Our model is loosely based upon GS-Hadoop and uses dataset consisting of more than 300,000 shapefiles (a vector data format), which was accumulated over a span of several years from various sources and creation of custom geo-portals for government departments. The developed model provides access to visual representation, extraction of features and related attributes from over more than 800 GB of shapefile data containing ten of billions of features. In this paper, we model a spatial data infrastructure for processing such huge amount of geo-data. Dr. Prabha Shreeraj Nair"A Spatio-Temporal Model for Massive Analysis of Shapefiles" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd6994.pdf http://www.ijtsrd.com/engineering/biological-and-bio-system-engineering/6994/a-spatio-temporal-model-for-massive-analysis-of-shapefiles/dr-prabha-shreeraj-nair

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