The title of this article was borrowed from a recent posting in Directions Magazine on Key Resources on Geospatial Cloud Computing. This phrase seems an appropriate title because, after some years of hype about cloud computing in general, we are seeing the emergence of a variety of very interesting cloud-based geospatial products and services. I will review the landscape of “the geospatial cloud” to provide you with a sense of the current state of the art.
Let us begin by quickly reviewing the elements of cloud computing. A very useful reference is The NIST Definition of Cloud Computing by the U.S. Department of Commerce
National Institute of Standards and Technology. NIST established five essential characteristics of the cloud model:
- On-demand self service. A consumer can request resources to be allocated automatically as needed.
- Broad network access. Clearly “the Internet is the computer.”
- Resource pooling. The provider resources are pooled to serve multiple customers.
- Rapid elasticity. The ability to rapidly scale by requesting additional resources
- Measured Service. Resource usage is monitored and customers often “pay-per-use.”
As we look at the various offerings in the geospatial technology sector, it will be useful to keep in mind these essential characteristics.
In the past several years we have seen the growth of a large ecosystem of IT providers in the cloud computing arena, as defined by the NIST essential characteristics. Where do geospatial companies stand in this space? In the traditional computing model, we have: (1) hardware resources such as storage, processor or memory; (2) platform, i.e., operating system, tools, databases, etc.; (3) application software. In the cloud computing paradigm, these translate into infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS) and software-as-a-service (SaaS). Geospatial software companies (or other application software companies) that wish to embrace cloud computing can offer their products on a cloud computing platform (IaaS/PaaS) or they can create new offerings in the cloud (SaaS).
The option of running a geospatial product in a cloud computing platform (IaaS/PaaS) such as Amazon EC2 or Windows Azure is relatively straightforward. Such cloud platforms provide a virtual machine with an operating system to install the application software. Depending on the application, there might be some issues - for example, firewall configuration, ports usage, licensing, etc. An end user might not be able to solve these problems on his or her own, however, they should be relatively minor complications for the software vendor. Thus from a vendor perspective, supporting a cloud platform is a matter of testing, making changes as needed, and certifying the software in such an environment. Software vendors might elect to go a step further and integrate with the cloud platform. In that case, the application software is packaged and configured to integrate with the cloud vendor management interface. As part of this integration, the geospatial software may adopt the cloud vendor payment system. ArcGIS for Server on Amazon EC2 is packaged for rapid deployment in Amazon EC2. The Open Geo Suite integrates with Skygone (theGISmarketplace) and Amazon EC2. Skygone hosts cloud versions of a variety of geospatial products, including MapServer and ERDAS Apollo, among others. In summary, supporting a cloud platform is not a radical move since it basically implies running the same traditional applications on a “rented” system outside the premises rather than on an in-house, company-owned system. The application software itself may be licensed on a pay-per-use basis rather than on permanent licenses. This may have significant financial implications that have been discussed in detail by Editor in Chief Joe Francica in an earlier Directions Magazine article: The Cloud’s Disruptive Value Play.
Even more interesting is an examination of the new SaaS geospatial offerings. For this purpose, we will categorize offerings into three groups:
- Basic mapping services
- Value added geoprocessing services
- Specialty applications
Basic mapping services are largely commoditized and many such services are available at low cost. For a discussion about the commoditization aspect, see the Directions Magazine article: Is Geospatial Cloud Computing a Commodity? Basic mapping services generally offer online content that can be used as a backdrop for users to add their own data. Users can upload data from a variety of formats to be mapped and symbolized against a selected base. Offerings include Esri’s ArcGIS Online and Google Earth Fusion Tables, which use their own image and vector content, and other services which are generally based on the widely used OpenStreetMap data. Examples of the latter include MapBox, GeoCommoms, CartoDB and Cloudmade. Basic mapping services commonly offer a free entry level option and fee options based on resource utilization or value added services. ArcGIS Online entry level users can upgrade to subscription-based services which include a rich set of added capabilities. Google Earth Fusion Tables users can migrate to other geoservices offered by Google (more on this later on). MapBox fees are based on the number of “map views,” storage utilization, support options, ability to remove the logo from maps, and analytics support. CartoDB fees are based on the number of tables, storage utilization, support options and the ability to remove the brand. GeoCommons can upgrade to the parent company, GeoIQ, for enterprise level services. Cloudmade users can upgrade by purchasing subscriptions to a large variety of point-of-interest databases.
Value added geoprocessing services are available in various forms from the geospatial cloud vendors. The full version of ArcGIS Online essentially exposes the full set of Esri ArcGIS capabilities to a cloud-hosted environment. ArcGIS for desktop acts as an authoring tool which provides the ability to create and publish geoprocessing services into ArcGIS Online. Google announced Google Earth Builder in April 2011. Recently, the name of Google Earth Builder was changed to Google Maps Engine. Google Maps Engine is a cloud-based platform for geospatial data management and collaborations. Data visualization is done seamlessly in Google Maps. Earlier, in December 2010, Goggle Labs announced Google Maps Engine ( formerly Google Earth Engine), a platform for distributed processing of satellite images. In addition to offerings from the giants, Esri and Google, the companies mentioned in the previous paragraph offer a variety of value added services:
- MapBox complements superior styling capabilities, offering advanced map analytics.
- GeoIQ, the parent company of GeoCommons, offers connectivity to enterprise databases and sophisticated geospatial analysis.
- CartoDB offers data join capability and spatial queries. Cloudmade focuses on consumer applications, offering geocoding, driving directions and a data market place with extensive point-of-interest datasets.
- eSpatial supplies a robust geoprocessing functionality via its product, OnDemand GIS. This is a full-featured SaaS GIS covering the entire gamut of capabilities for data capture and editing, data management, view, analysis and reporting.
In the specialty application category, there are a variety of SaaS applications designed to perform specific tasks. I will mention just a few examples. In this category is Socium, a wholly owned subsidiary of 1Spatial that provides online data validation services based on 1Spatial Radius Studio technology. Esri Business Analyst Online is an SaaS solution for custom site evaluation and market analysis. Digital Map Products offers SaaS products for spatial development, government and real estate markets.
Cloud computing is not a fad -- it is a real trend with a compelling value proposition. Google CIO Ben Fried said, “The economics of cloud computing are driving down the cost structure of business so far and so fast that it’s scary” (CIO Journal). In the geospatial industry, cloud computing is a growing segment in which we are seeing the emergence of a myriad of innovative solutions. Many of these solutions are helping to bridge the gap between traditional GIS and business solutions as well as consumer applications. However, the impact encompasses the entire industry. In this article I have made an attempt to describe the geospatial cloud with a variety of examples. The references mentioned are not intended to be comprehensive but rather representative of key areas. As this is a rapidly changing field, I invite readers to comment on any noteworthy omissions that may have escaped my attention.
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