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Posts Tagged ‘GNSS’

Quick Fix for Precise Positions: A family of new tools helps solutions providers leverage positioning technologies to create customized, high-value solutions

Monday, September 26th, 2016

The strategy of vertical segmentation continues to play a key role in the geospatial arena. Often referred to as “verticalization,” the vertical approach enables GIS users and solutions providers to focus on specific markets and applications. By leveraging geospatial technologies and software to create specialized solutions, developers can optimize fit to task and help users achieve high levels of value and productivity. The vertical approach also provides opportunities to develop new business and clients in applications where spatial information can improve decision processes and efficiency.

 

We can illustrate the vertical approach by looking at how utility companies use geospatial information. Utilities need specialized solutions to gather, analyze and share position and attribute data while meeting required levels of precision and detail. For example, electric and water utilities use GIS to locate and manage assets. In times of service outages, they can combine the GIS data with customer reports to pinpoint the location and cause of the trouble. These applications seem similar, but marked differences exist in the workflows and data. Electric crews can use meter-level data to locate poles, but water technicians may need centimeter precision to find valves in flooded streets. Creating solutions for the two segments involves leveraging the similarities while providing tools tailored to the different needs.

 

Although verticalization opens the door to using spatial information in a broad range of industries and disciplines, meeting a large number of specialized needs can tax the capabilities of manufacturers and software houses. This issue can be solved by using tools that enable users, service providers and independent developers to create new vertical solutions.

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Expanding the Data Stream: A skillful blend of people and technology can provide valuable data for GIS

Friday, August 12th, 2016

GIS is an essential component in many decision and management processes. A well-structured GIS provides invaluable tools to visualize, analyze and query geospatial data and associated information about features and objects in both the natural and built environments. Because a GIS database can contain information on a wide variety of features and terrain, it is commonly built and maintained using information produced by a broad range of input and data sources.

As applications for GIS data expand, so does the demand for new and efficient ways to collect and deliver quality, actionable spatial data from the field. Satisfying the seemingly insatiable demand for data doesn’t always involve traditional GIS field technicians. Certain types of geospatial data can be produced by the general public. And in some cases, data collection doesn’t involve humans at all.

The Triple Play of Data Collection

Today’s widely available options for connectivity and Internet-based communications are enabling new approaches to collecting and using GIS information. We can divide the techniques into three broad classifications: crew sourced, crowd sourced and automated acquisition.

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Beyond the Field: GIS data is more than positions and attributes. Here’s how the additional information can work for you.

Monday, June 27th, 2016

When most people think of GIS, they think of maps, and rightfully so. For decades, typical consumers of spatial data were cities, municipalities and other organizations that used GIS to manage and visualize information about assets and environments. This is continuing, of course, as the use of geospatial information moves into new private, commercial and industrial segments. However, as GIS data flows from the field to end users, opportunities exist to develop information that goes well beyond the traditional positions and attributes.

 
Three Components for Data Delivery
To understand this potential, let’s look at how GIS data moves through an organization. There are three components to the process.

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