Archive for the ‘Uncategorized’ Category
Wednesday, December 21st, 2016
The rapid evolution of geospatial technologies brings to mind a Yogi Berra quote: “When you come to a fork in the road, take it.” Berra made the remark while giving directions to his home—either choice would take you to Berra’s home in the same amount of time. Like many “Yogi-isms” that blended wisdom and counterintuitive logic, this quote carried a deeper message: Seemingly divergent paths can lead to the same result.
Berra’s advice especially strikes a chord with geospatial data collection, where GIS and other positioning professionals can choose from a pair of approaches to gathering data in the field. Purpose-built data collection devices, which have been the norm for a decade or more, are now sharing the stage with Bring Your Own Device (BYOD) solutions such as consumer-grade smartphones and tablets.
Both are good options. The happy dilemma lies in determining which approach provides the best route to the objective: efficiently gathering accurate information that can be quickly provided to the people who need and use it.
There are convincing arguments both for BYOD and commercial data collection solutions. On the commercial side, specialized field hardware such as the Trimble® Geo7 series GNSS handheld is rugged and well suited for operation in challenging environments. The displays and keyboards provide good visibility in sunlight and perform well under difficult conditions. The devices can run task-specific software provided by manufacturers such as Trimble and Esri. Alternatively, software development kits (SDKs) and application programming interfaces (APIs) enable third-party developers to create their own specialized applications for the rugged units.
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.
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.
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.
Wednesday, June 1st, 2016
GIS taps into an essential human characteristic: We are visual beings. By providing the ability to show many kinds of data on one map, GIS enables people to visualize and analyze patterns, trends and relationships. It’s transforming the way companies and governments manage assets and activities.
As geospatial professionals, we are familiar with the basic aspects of GIS such as collecting and sharing spatial information. Regardless of how it will be used, data gathering and processing for GIS applications is built around core technologies for positioning and data management. GIS leverages these common characteristics to address an extensive array of needs for information and workflows. More than any other facet of the geospatial industry, GIS faces a wide—and demanding—variety of applications and opportunities.
Wednesday, April 27th, 2016
Like many catch phrases, the concept of “Big Data” comes with multiple definitions. From the GIS viewpoint, big data describes data sets that are so large—both in volume and complexity—that they require advanced tools and skills for management, processing and analysis. Such huge data sets can be a lot of work, but the extra effort pays off substantially. Geospatial big data provides detail and contextual information that provides immediate and long-term value across multiple disciplines and applications.
Geospatial big data can include information from an assortment of sensors and data collection methods. Points and features with their associated attributes can be gathered using handheld or survey-grade GNSS, dedicated field computers or even smartphones. These data sets are small compared to other techniques, but they provide very high levels of precision and detail and can be updated rapidly. Mobile mapping systems combine lidar, imaging, GNSS and other sensors to capture large quantities of 3D information. The data is then fused to develop comprehensive models and databases. Data collected from airborne and satellite platforms range from imagery and lidar to multi-spectral remote sensing.
Monday, March 14th, 2016
You may already own a big part of the future of GIS—your smartphone. Here’s how it can transform the way you work.
It’s no secret that geographic information systems have big appetites for data. The demand isn’t slowing. Industry segments including government, utilities, transportation, energy and their mobile workforces are discovering the value of spatial information to managing resources and activities. The trend has produced growing demands for tools to manage and use geospatial data.
In addition to gathering data to create new databases and GIS layers, significant resources are devoted to maintaining spatial data. Once a GIS is populated, its information must be continually refreshed as growth and change affects natural and built environments. Incomplete or out-of-date data can reduce confidence in the accuracy of the GIS, potentially drawing down the value of the information and services it provides. It’s a risk that GIS professionals can’t afford to take.
Thursday, February 11th, 2016
Aerial imagery has long been a staple of GIS. By providing viewpoints from high above the ground, aerial images enable people to understand the geographic context of individual features. Orthoimages developed from aerial photographs routinely serve as background maps of terrestrial data for numerous GIS applications. GIS analysts use photogrammetry to develop terrain models and measure specific objects or features. Airborne remote sensing using infrared wavelengths supports GIS in the study of vegetation and thermal characteristics of natural or built objects.
When combined with other data in a GIS, aerial imagery supports a more complete, accurate analysis of a scene. As an example, forest managers can identify areas where homes and buildings are close to overgrown or unhealthy forests that are susceptible to wildfires. The foresters can work with local agencies and property owners to mitigate fire risk and develop emergency plans.
To obtain aerial imagery, GIS professionals can turn either to third-party service providers or in-house resources. Most commercial aerial imagery is captured using manned aircraft equipped with sophisticated cameras or lidar, depending on the type of application and imagery needed for a project. Manned aircraft are typically operated by service providers and offer important benefits such as the ability to cover large areas and fly at high altitudes as well as capture very-high resolution images with advanced, large-format sensors. The results are excellent, but come with tradeoffs. Costs for manned aircraft can be high, and jam-packed flight schedules or changing weather conditions can introduce risk to expected lead time for collection and processing of aerial images.
Tuesday, January 19th, 2016
The use of spatial information is growing rapidly in both the consumer and professional arenas. The growth, with its voracious appetite for data, is moving the geospatial industry into new application domains. These domains have significant variations in the type and precision of data needed, the environments where it is collected and the workflows of the people collecting it. A forester, archaeologist, environmental engineer and wetlands biologist all gather GIS data (features, attributes, positions, etc.), but to significantly different ends. In many disciplines, an object’s location is a minor component among many attributes that are needed.
The increase in data volume and types has had a profound impact on the geospatial industry. Geospatial manufacturers historically emphasized their positioning technologies. Position sensors are still needed of course, but they are not the entire solution. Today’s GIS solutions must speak the language of the users, making it fast and efficient to capture the pertinent data while presenting information and instructions in familiar terms.