Introduction
Bing Maps was developed by Microsoft in response to the business threat posed by Google who also offers Google Earth Pro, for the visualization and mapping of much of the world using satellite imaging from low- and medium-Earth orbit satellites (LEO’s and MEO’s). The main competitor to Google Earth is Bing Maps which was created by a collaboration between Yahoo and Microsoft and launched in December 2005. It uses a number of Microsoft technologies such as Microsoft MapPoint, Silverlight, and Photosynth. Silverlight is similar to Adobe Flash and allows a user to get directions to specified locations, and views of urban landscapes. Street maps and photographs of almost all of North America and western Europe are available online with 3-D visualization being possible for many of the larger cities and towns. Photosynth supports 3-D modeling of objects on the ground and allows the user to take virtual tours of buildings, sports stadia etc. Since its release, Bing Map’s data and features have been constantly updated. To maintain its market share, Google is working to improve its own product, Google Earth. In June 2009 Google was still the dominant player in this market with some 72% of market share as against Bing Map’s 9% but by January 2010 these figures had changed to 65.5% and 11.5% respectively. (Physorg 2010)
How does it fit into the larger ecosystem of computing, especially GIS?
The “computing ecosystem” is a new term to describe the new virtual reality of increasingly inter-related networked systems and the devices which use them. The GIS technologies of returning images of the Earth from satellites link into satellite navigation devices, mobile telephone technology and land-based Internet connections.
What are its underlying concepts?
Bing Maps uses modern Internet technology and infrastructure. The system processes very large data sets of GIS data in visual form with text data for coordinate and geographic placing. Because of the size of the database, which is constantly being updated as data arrives from the satellites, it is distributed on numerous mirrored clustered servers – so-called “commodity” servers. The data is partitioned between these clusters which are connected via a high-bandwidth dedicated link. To process the client query, Microsoft uses a neural net system to rank the incoming query and direct it to the appropriate cluster(s). Neural networks are also used to process the back-end of the problem i.e. the aggregation of multiple results.
Many languages have been suggested for the parallel processing of distributed databases but one used by Microsoft itself is called “SCOPE” – Structured Computations Optimized for Parallel Execution”. (Chaiken et al 2009) This is a language based on SQL with extensions to allow for simultaneous processing in different server locations. Its authors state that is based upon standard relational database technology, it will perform like a normal sequential query language, but the extensions allow it also to work equally well in distributed mode.
Numerous algorithms for optimizing Bing Maps performance are also in existence. For example, one of its features is the use of “pushpins” – map markers in the shape of a thumbtack to pinpoint a particular location. Large numbers of these in a single map will reduce the performance. A lot of work is currently being undertaken to develop algorithms for client-side pre-processing by, for example, amalgamating large numbers of pushpin clusters for faster processing and better legibility.
Who should use the application?
Internet users who are looking for the geographical features of a targeted area should use this application. Users will be able to find and query web maps to use them practically. It will find, as does Google Earth now, applications in transportation, logistics, town planning, new infrastructure development, driving directions, traffic management, architectural design, civil engineering, pipe- and cable-laying, surveying, land registration, property management, property taxation, environmental monitoring, the proximity analysis of critical projects, geography teaching, geological mapping and mineral prospecting, air and sea navigation and many more. Undoubtedly, however, very many people will use it as an extension to the many rapidly-developing social computing networks. It is already part of the real-time content of Twitter and Facebook.
Reference List
Chaiken, Ronnie, Jenkins, Bob, Larsen, Per-Åke, Ramsey, Bill, Shakib, Darren, Weaver, Simon, Zhou. Jingren. 2009. SCOPE: Easy and Efficient Parallel Processing of Massive Data Sets , Microsoft Corporation , .
Physorg.net, 2010 Physorg.net Bing gains US search market share for ninth straight month” , Web.