Benefits of GIS (part 3): GIS solutions for business analytics and predictive modeling
2015-25-05, by admin
Part 3 in the “Benefits of GIS” series. Here we focus on GIS for business intelligence and predictive modeling.
GIS and LBS for business intelligence
An increasingly effective method of data analysis is by combining analytics with location and geographic data. Location matters more and more because of the increased use of smartphones and location-based applications. It is also a source of powerful insights, helping businesses solve problems that they didn’t know they could solve before. It lifts the fog out of business decisions, as it makes transparent exactly where (and when) things occurred: from individual actions such as social check-ins and mobile searches to vital business information such as vehicle break downs, accident locations, or spread of diseases.
In short, the potential for uncovering new solutions is extremely high and can have even greater returns. This is precisely why one of our clients, a giant business intelligence provider needed help adding new geographic data capabilities to their existing application. They already had powerful software that clients loved, but adding location-based data analytics would add an additional level of insights that was unavailable before (not to mention blow their competition out of the water). The new add-on mapped geographic details, buildings and locations, and paired each object with their uses and particular characteristics. Their clients were then able to use this software with their already existing business intelligence data. The result was that they were able to gather more insights about their end-users, modify marketing campaigns and identify new segments – and translate their new findings into tangible income.
LiDAR data for predictive modeling
What is LiDAR Data?
LiDAR, or Light Detection and Ranging, is a remote sensing technology that works by gathering geographical information using a light from a laser (similar to a radar). It can use different types of wavelengths depending on the object. The output is a 3-dimensional point cloud of the object (like the image). It’s a great technology for production of high-resolution, accurate maps.
The major challenge of LiDAR technology is that it typically yields very large datasets. Depending on the format, the file size can vary from 2.6MB to 100MB per square mile and more accuracy means larger files. Therefore large area and high the accuracy means bigger data files, which require more storage space, computing power, staff and time for data processing, and finally network for data transfer.
What’s its use in business?
LiDAR is used in a variety of industries, from archeology, meteorology, and forestry to transportation, robotics and law enforcement. In addition to providing accurate visualizations of the physical world, the data collected from LiDAR measurements can be used to build predictive models. One of the projects we worked on involved processing LiDAR DEM data and finding vegetation growth patterns. The first step was, of course, mapping the height of vegetation in the given area. We could then analyze which plants were present in the area and use statistical prediction to analyze the growth of individual plant species. The prediction tool eliminated the need for fieldwork, which would have been the traditional way of acquiring similar information. The client could move past observation and data analysis and actually figure out better ways to manage land and develop plans for future vegetation growth.
If you’d like to find out more about these methods, feel free to contact us.
We’ll also be at GEO Business Show 2015 on May 27th and May 28th. Come see us at stand B11 to chat about GIS for business intelligence and predictive modeling.
Benefits of GIS (part 1): Improving urban planning and public services
Benefits of GIS (part 2): Resources and land management
New analytics software made possible with data visualization
Image via Evergreen.edu. No changes were made.
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