Your five-minute guide to geospatial data
Mar 2023
Learn geospatial data in simple terms — how it’s collected, what it’s used for and how it can benefit your business.
Mar 2023
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Maybe you’ve dropped a pin to let a friend know where you are, or you’ve seen ads on your phone for a business nearby that seems perfectly tailored to your needs. These daily occurrences, how locations link to daily life, the way city infrastructure is planned, where engineers choose to build bridges and how infrastructure is maintained, can all be traced back to one thing – geospatial data. The information we gain from gathering and analysing data about our built and natural environments shapes millions of decisions daily.
This article will guide you through an overview of geospatial data – what it is, how it’s used and where you can find it.
What is geospatial data?
In its simplest interpretation, geospatial data is information that describes objects or events with a location on earth. This includes maps, imagery, datasets, and tools that link features, events, and entities to specific locations. This information is then presented in a format connected to a dataset such as map coordinates, street addresses, cities, or postal codes.
What is the difference between GIS and geospatial data?
Once you have obtained geospatial data –the basic information or ‘raw material’ about a particular location – you need a platform to process, analyze and visualize it. This is where a Geographic Information System (GIS) adds value. GIS is software technology that collects, stores, and manages the geospatial data.
How is geospatial data collected?
There are multiple resources used worldwide to collect geospatial data. Aerial imagery, census data, weather data, mobile phone data, drawn images and social media data are just a handful of the most common applications employed to gather and create geospatial data. The combination of these data types together creates stronger overall outcomes. Whether you are studying the habits of a certain population or creating a site map for a new road, different datasets within the larger collection of location data will benefit your use case.
What are the types of geospatial data?
In its most basic form, geospatial data can be split into two categories — vector data and raster data. Vector data represents geographic features using lines, polygons and points.
- Lines – represent linear features, such as roads, pipelines, rivers, etc.
- Polygons – represent area features, such as building footprints, water bodies, land parcels.
- Points – represent specific locations such as cities, trees, building locations, built infrastructure
Raster data is made up of gridded cells (pixels) which are classified by rows and columns, and represent factors including elevation levels, land cover, and temperature.
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How can you use and analyze geospatial data?
Once geospatial data has been identified and collated, it needs to be analyzed to be understood. Simple datasets can tell the story without complex systems or processes –for example, a request for how many properties in an area meet a certain criteria, such as having solar panels or a certain type of roof material, can deliver the outcome without further data processing requirements.
To recognize spatial relationships and to create maps describing these relationships, complex geospatial data can be analysed in Geographic Information System (GIS) software – a technology platform designed to consolidate and visualise geospatial data a more user-friendly map-based visual format than just raw data, statistics or figures.
The ability to see an accurate visual representation of how the data applies to real-world contexts, like maps, sites, and networks gives a workable perspective. This location-based information becomes critical for accurate analysis, management, administration, and governance across a wide range of sectors, which we will outline in more detail.
Geospatial data can also contribute to analyses of change over time, using AI-identification to highlight variations in mapped features, such as tree cover, the built environment, and asset condition.
Types of geospatial data
In its most basic form, geospatial data can be split into two categories — vector data and raster data. Vector data uses lines, polygons and points to represent urban features such as cities and roads, as well as topographic features like mountains and bodies of water. Raster data is like vector data’s more complex sibling — it’s made up of gridded cells which are classified by rows and columns, and represent the likes of elevation levels and temperature.
Examples of geospatial data in use
Across industries, there are three key benefits to using geospatial data. These three facets combine to become time and money-saving assets that businesses and governments rely on.
- The ability to get advanced warning on incoming changes set to affect businesses by flagging anomalies in geospatial data.
- Analyzing geospatial data provides invaluable business insights backed by real-time evidence.
- The numerical precision of geospatial data can greatly improve operational efficiency.
Here are some examples of industries that use geospatial data and the potential outcomes.
Insurance
Analyzing risk at a wide scale can help insurers gain insights for underwriting, while post-catastrophe data can identify areas of property loss and damage, helping insurers respond quickly and with greater confidence in the event of severe events. Gaining a more accurate understanding of risk factors, property by property across wide areas of the population, gives insurance companies greater insights on the most viable future direction for their portfolio.
Engineering and construction
Using GIS and Computer-Aided Design (CAD) systems, engineers can undertake accurate modeling and facilities management, as well as provide location context for projects.
Government
The public sector uses geospatial data for a host of applications including site monitoring, contact tracing, incident mapping and emergency services, vegetation management, and verifying building locations, boundaries, and new developments.
Utilities
Geospatial data helps water, electric, gas, and telecom service providers plan infrastructure based on location and population, identify hazards, and gain visibility on usage habits.
Transport and logistics
Maintaining transportation assets, rail networks, roads, air traffic, long-haul trucking and the postal service requires being able to process large quantities of complex geospatial data.
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Sourcing the best geospatial data
The insights you get out are only as good as the data you put in, which is why it’s crucial to be discerning when sourcing location intelligence. To process the data, geospatial platforms such as Esri ArcGIS lead the way, with the ability to analyse data to provide accurate insights.
Nearmap aerial maps cover more than 80% of the U.S. population. Our regularly captured and published imagery contributes to geospatial data solutions that help both private and public organizations thrive.
If you want to start harnessing the power of aerial imagery for your business, get in touch today.