Cloud enabled SDI architecture: a review

With the advancement of GIS technology since its inception in 1960’s, many educational institutions, government departments, public/ private sectors and individuals have started its use for the production and management of spatial data. Spatial Data Infrastructure (SDI) concept was introduced in the early1990’s and provides a set of technologies, standards, protocols, policies and guidelines on the whole cycle of geospatial data production and distributions, i.e., from data capture to storage and to sharing. SDI initiative at national level, termed as National Spatial Data Infrastructure (NSDI), has been taken by different countries including India. Geospatial community is facing various challenges like handling of large volumes of geospatial data, requirement of high computing resources to process geospatial data, scalability and interoperability. Therefore, need of advanced technologies in the form of SDI and cloud computing is realized to resolve the above challenges. Cloud computing has several characteristics like scalability, elasticity and self-provisioning that offers high-performance computing resources to perform geoprocessing efficiently. The main aim of the present paper is to study SDI and its components along with analysis and comparison of NSDI of various countries as well as to conceptualize and discuss service oriented architecture of cloud enabled SDI. Several challenges of the spatial data handling and processing that occurred due to the high intensity of data and lack of processing capability can be solved by adopting proposed cloud enabled SDI architecture. This research will help geospatial community and SDI developers in various perspectives including data sharing and management, interoperability, security and reliability, fault tolerance, mass market solution, upfront cost and global collaboration.