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 Big Geo Data Management
Jason Caldwell, VP
Jason Caldwell, VP
Jason Caldwell is the Vice President of Business Development and Sales at the Sanborn Map Company.

Geospatial Solutions Data Life Cycle: Step 1 – Enterprise System Assessment

November 24th, 2015 by Jason Caldwell, VP

Enterprise System Assessment

This blog entry will focus on the first step of the Geospatial Solutions Data Life Cycle – Assessment.

Organizations all over the world are starting to recognize significant value in geospatial solutions and how geospatial solutions create efficiencies in the management of business operations. However, as organizations deploy geospatial solutions such as orthophotography / orthoimagery, land cover map databases, aerial LiDAR, oblique aerial photography, planimetric mapping and 3D Cities, many variables will affect the organization’s ability to take advantage of the efficiencies provided by geospatial solutions.

A successful Enterprise System Assessment is based on well-defined user needs, functional requirements, and application specifications. In order for clients to get the most success out of Big Geospatial Data, they must first understand their current position and decide on an approach that complements their business operations. This is a critical stage of the lifecycle, as it will provide input for the remainder of the cycle, which includes data acquisition, analysis, distribution and maintenance. The assessment phase will ensure the development of the best solution to fit the organization’s needs.

There are three potential outcomes when completing this assessment: under-engineering, which will not allow the organization to achieve the full efficiencies desired; over-engineering which likely will have cost implications; and peripheral vision, which is designed to ensure that the organization’s related systems are taken into context when creating the requirements for the eventual solution.

Under-engineering the geospatial solutions requirement is one of the highest risks when completing the assessment. The risk is so high because organizations tend to fall into a trap that focuses purely on budget requirements. While there is no escaping the limitations on funding, many organizations have purchased a solution based upon a budget, rather than based upon the organization’s needs. If this error is made, significant money may be spent on a solution that provides no efficiencies to the organization. This effectively means that all money spent on the solution was wasted. An easy example of this unfortunate scenario is the purchase of orthophotography / orthoimagery. It is much less costly to purchase a 1-meter resolution image compared to a 15 cm (6-inch) resolution. However, the 15 cm image provides the ability to identify many more features. As a result, if your only user need dictates the ability to see manholes, purchasing the 1-meter image is a complete waste of money because manholes are not visible. The opposite holds true, as well – over-engineering the solution is a way to waste money, too.

High Res Imagery vs Low Res Imagery

High Resolution vs. Low Resolution Imagery

Over-engineering the geospatial solution is a common issue encountered by business operations. Electing to go with the most accurate, highest quality, most expensive solution is not always in the best interest of the organization either. The enterprise system assessment should identify what is needed, and the organization should use the assessment as a baseline for the geospatial solution creation. As an example, many organizations use 3D Cities building data to meet their geospatial needs. However, there are many levels of quality and associated cost for 3D Cities building data. An organization may have a need to complete geometric wind modeling. Based upon this need, a fully textured structure is not required as these models cost significantly more than the building geometry alone. While the textured building models provide a more visually appealing solution, the additional cost is not warranted for the customer that only needs to conduct geometric modeling. Similar to over- and under-engineering issues discussed above, clearly understanding the peripheral systems and the context to which they will interact with the Geospatial Solutions is an important aspect of the assessment.

3D Buildings

Geometric 3D Model vs. Geometric and Textured 3D model

Wikipedia defines the term Peripheral Vision as being the part of vision that occurs outside the very center of gaze. Sanborn is using this terminology to expand on the idea that there may be systems that sit on the periphery of the geospatial solution that may not be apparent when looking only at the organizational needs. One must look at the bigger picture, and include the peripheral needs, in order to have the context for the Geospatial Solution to be created. An example of this could be relational databases, IT infrastructure and hardware, or even software systems. One of the simplest illustrations for this issue can be seen when organizations purchase large data such as LiDAR Survey / LiDAR Mapping. A LiDAR survey may be comprised of many Terabytes of data, with individual file sizes of several gigabytes. Identifying storage requirements, software limitations and overall CPU configuration to take advantage of the data will be important factors to consider during the assessment phase.

In conclusion, the Enterprise System Assessment can be used for sophisticated GIS system creation. It can also be used to identify specific data needs, as understanding business context is important when designing a geospatial solution. Whether the organization is starting from scratch, or looking to enhance their Geospatial solution, the assessment phase will help identify the business needs at hand and maximize the efficiency desired by the solution.

Check back soon for Part 2 – Data Acquisition…

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