Introducing: Nearmap for Post-catastrophe Response
Post-catastrophe imagery and AI-derived property damage and condition data unite to help insurers process customer claims more efficiently.
Post-catastrophe imagery and AI-derived property damage and condition data unite to help insurers process customer claims more efficiently.
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, 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 made daily.
This article will talk you through everything you need to know about geospatial data — what it is, how it’s used and where you can source it.
In the simplest terms, geospatial data is any data that describes objects or events with a location on the earth. It’s things like maps, imagery, datasets, tools, and procedures working together to tie events, features, and entities to locations. This information is then presented in a format connected to a dataset such as map coordinates, street addresses, cities, or postcodes.
There are multiple, diverse 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 a stronger overall outcome for the user. 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.
Most commonly, geospatial data is used within geographic information systems (GIS) to recognise spatial relationships and to create maps describing these relationships. Within the GIS, users are able to view the data in a more user-friendly format than just raw data. They can see an accurate visual representation of how the data works in real-world contexts, like maps, sites, and networks. This location-based information becomes critical for analysis, management, administration, and governance across a wide range of sectors, which we will outline in more detail.
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.
Why is geospatial data important? Like all gathered information, geospatial data reveals important insights for multiple industries across the world. Below, we provide some examples of industries that use geospatial data and how they use it.
Geospatial intelligence can be used to create a next-level retail experience — think targeted marketing for customers and site analysis for ideal new store locations.
Using GIS and Computer-Aided Design (CAD) systems, engineers can undertake accurate modelling and facilities management, as well as provide location context for projects.
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.
Banks and financial institutions use location data to discover risk zones and other patterns, then adjust services and offers based on this intelligence.
Geospatial data helps water, power, gas, and telco service providers plan infrastructure based on location and population, identify hazards, and gain visibility on usage habits.
Maintaining things like railway assets, airport assets, air traffic, long-haul trucking and the postal service requires being able to process large quantities of complex geospatial data.
Across all industries, there are three key benefits to using geospatial data. These three facets combine to become time and money-saving assets that industries rely on.
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. Geospatial platforms such as Esri ArcGIS lead the way, with the ability to process trustworthy, reliable data to provide accurate insights.
Nearmap aerial maps cover up to 95% of the Australian population in mostly urban and some remote areas. Our regularly captured and published imagery contributes to geospatial data solutions that help both private and public organisations thrive.
If you want to start harnessing the power of aerial imagery for your business, get in touch today for a free quote.
While we make every effort to ensure the accuracy of the data and analysis in blog articles, this information is not to be relied on as professional advice. No endorsement or approval of any third parties or their advice, opinions, information, products or services is expressed or implied by any information in the blog. Should you seek to rely in any way whatsoever upon this content, you do so at your own risk.
