GIS is a data intensive in nature and it is a mature technology. It has facilitated a large amount of geospatial and non-spatial data. The size of these data with time will grow to be large enough to restrict any single organization to maintain and handle such a massive data. Also GIS applications are severe consume of computational resources such as processing, memory and storage to perform manipulative operations on such huge data. These applications generally include data acquisition and preprocessing from multiple sources which is followed by exhaustive spatial analysis . GIS functions and services are geographically and logically distributed due to the source of data, location of computing facilities and organizations. GI systems are expensive investment (HW, SW, personnel), moreover data acquisition and maintenance which are usually expensive and time consuming .
Therefore GIS always develops through governmental authorities and massive organizations which can afford such investment. Many of smaller users in different domains do not have the capability to drive GIS. Cloud computing provides resources as a service. It offers scalable infrastructure and solution to such challenges to host large volumes of data as well as powerful computing resources . With cost reduction are needed and release the upfront expensive cost, Cloud GIS help many businesses . The extensive use of GIS especially in mobile apps which becoming increasingly widespread all over the world in different types of fields, can with good opportunity be moved to the Cloud. This trend will provide on-demand services to wider range and a variety of small users.
"GIS experienced a tectonic change from stand-alone applications to a distributed environment illustrated in Spatial Data Infrastructure (SDI)" (Masser, 2005). The evolution of GIS from two-layer architecture (client and server) to the multi-layer architecture is driven by the related need of GIS applications. Open Geospatial Consortium (OGC) provides a blueprint for implementing Service Oriented Architecture (SOA) in GI science applications (Friis Christensen, 2007).
The OGC standards are technical documents that detail interfaces or encodings. These standards are implemented in products or online services. It has been the backbone of the standardization and interoperability relating to the spatial data and GI services. OGC tiered architecture shows the interaction among modular tiers in the geospatial landscape (OGC, 2011) as shown in figure 1, the interaction among modular tiers in the geospatial landscape. 
OGC facilitates the interoperability and SOA standards (OGC, 2008):
• Web Map Services (WMS) provides implementation specification for the creation and display of map like views of information.
• Web Feature Services (WFS) allows a client to retrieve and update geospatial data encoded in Geography Markup Language (GML) from multiple web feature...