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.

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支持云的SDI架构：评论

随着GIS技术自1960年代问世以来的发展，许多教育机构，政府部门，公共/私营部门和个人已开始将其用于空间数据的生产和管理。空间数据基础设施（SDI）概念是在1990年代初期引入的，它提供了有关地理空间数据生产和分配的整个周期（即从数据捕获到存储再到共享）的一组技术，标准，协议，策略和指南。国家级的SDI计划被称为国家空间数据基础设施（NSDI），已被包括印度在内的不同国家采用。地理空间社区面临各种挑战，例如处理大量地理空间数据，需要大量计算资源来处理地理空间数据，可伸缩性和互操作性。因此，实现了对SDI和云计算形式的先进技术的需求，以解决上述挑战。云计算具有可扩展性，弹性和自动配置等多个特性，这些特性提供了高性能的计算资源来有效地执行地理处理。本文的主要目的是研究SDI及其组件，以及对各国的NSDI进行分析和比较，并概念化和讨论面向云的SDI的面向服务的体系结构。通过采用建议的支持云的SDI体系结构，可以解决由于数据强度高和处理能力不足而引起的空间数据处理和处理的若干挑战。