With so many cell phones, packages, vehicles, purchases, and other items moving through time and space, a solid understanding of how spatial data can be used is becoming increasingly important. This post will give you an overview of the various types of spatial data and how to make the most of yours.
What Exactly is Spatial Data?
Spatial data is any type of data that, either directly or indirectly, refer to a specific geographical area or location. Spatial data, also called geospatial data or geographic information can be used to give a numerical representation of a physical object in a geographic coordinate system. However, spatial data is much more than just the spatial component of a map.
Types of Spatial Data
Vector and raster spatial data are the two types of spatial data. Vector data represents features in the world using points, lines, and polygons. Vector data is made up of coordinates, or a series of corresponding coordinates, that are used to determine the location of features. In addition to the coordinates, important metadata about each feature, such as its name or other properties, is also stored.
Raster data, on the other hand, employs images to summarize geographic information in the form of a grid of pixels applied to the earth's surface at a specific scale. Each pixel represents a geographic "bin" that summarizes an area-wide value, such as temperature. Rasters can then be generated at various resolutions based on the observational data available. Some may contain very granular data cells, while others may be coarser and aggregated. Metadata like a Spatial Reference System, projection, boundaries, and position are part of raster data. These things tell the grid how to be placed on the map.
The Advantages of Spatial Data
When making business decisions, spatial data is useful because it provides a more complete context. For example, while locating a new store in an upscale neighborhood may appear to be a no-brainer, there may be significant revenue implications based on spatial factors such as distance to competitors, vehicle parking availability, and public transportation options, as well as proximity to households earning more than $50,000 per year.
Location data reveals real-world patterns and behaviors, such as which roads people use more frequently than others or how their location influences their purchasing decisions. When combined with time-series data, we can see how these outcomes change over time and the path someone takes to make a decision. Vehicles are tracked through space and time in fleet management and other systems that report on the vehicle's current status. These systems can even warn motorists of dangerous roadway conditions or driving behavior. Motorists may only know the vehicle's speed, without a spatial context. For instance, they can see the vehicle is traveling at 70 mph, but they might not know whether it's on an interstate, a main highway, or in a residential zone.
Businesses with access to this information can react to changing market conditions more quickly and make better informed decisions. Consider a restaurant that can provide a coupon to a regular customer who is currently in the area looking for food, rather than emailing them a coupon every week and hoping they remember to use it at the appropriate time. These types of offers are made possible by spatial and time-series data. According to Gartner, real-time location analysis is anticipated to influence 30% of customer interactions by the end of 2022.
If you are looking for more information on Spatial data and how it can help your business, look no further than AirSage.
AirSage harnesses the power of billions of GPS signals. Using a patented big data approach, we extract geospatial insights from raw data.
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