Geospatial technology brings tools and data together to describe, map, and analyze the world around us and worlds yet to be discovered.
The term geospatial is a relatively new invention at least in the parlance of mainstream developers. Geospatial can refer to types of data or to types of technology. The word itself is a combination of geographic and spatial – indicating an alignment between geography and the general idea of spatial/locational properties. Spatial concepts (think geometry and statistics) do not necessarily represent a place on a planet until they are combined with ideas of geography in general.
Built on the history of Geographic of Information Systems (GIS)
GIS is a technical domain, usually for geographers, that allows users to make digital maps and subject them to various types of analysis. Sources of GIS data may include satellite or aerial imagery (raster data) or line map data (vector data) delineating points, lines, or regions of interest – created by surveyors, engineers, photo interpreters, etc.
While many GIS projects output maps, their primary goal is to develop observations about a project area and overlapping properties and values. For example, land-use planning typically requires a GIS process to compare/contrast all the competing values – economic, social, environmental, etc. These are thought of as layers of spatial data that overlap one another and can be combined to show different management priorities or scenarios.
Where do deer live in the winter compared to a planned highway development in a popular tourist corridoor – many values in one location often need advanced tools to build a complete picture.
Geography made digital
While GIS helps bring geography into the digital domain, geospatial technology helps bring it to life for more people. Beyond specific GIS projects, there are many more data sources, cartographic products and ways to output maps for different consumers . Collectively, these fall into the region of geospatial data and technology.
Web-based mapping really helped propel the generalized use of geographic data into the mainstream. Before Google Maps was introduced in 2005, there were only a handful of common web-based mapping tools available for the public to use. Developers started to build their own open-source platforms to share information and collect input.
This required a whole stack of technology including geographic data, web servers, spatial databases, rendering libraries, web-interaction libraries (zoom/click/pan), and the internet itself. Geographers or GIS users may only be a small part of the overall project or not involved at all.
In the end, a handful of different technologies are needed to bring digital geospatial data to life.
Broader than just spatial analytics
Building new geospatial web-mapping tools was one part of the journey. Naturally, the more people use mapping tools, the more questions they want to answer. For example, consider how popular Google Maps became due to its driving directions. This level of spatial analytics was profoundly useful for those driving in a new location. But only a small set of built-in analytics was really ever possible with this platform – or so it seemed.
Data analysts and GIS users are used to running specific types of routines on data to get an answer. For example, calculate an optimal route from A to B. Or what is the expected water course derived from this elevation model?
However, with modern geospatial technology, the user may view and interact with the data in a more real-time approach to build understanding before they ever run an analytical routine.
They may never click a “analyze” button but can use a 3D map view to get a sense of where water will flow, or look at the streets around them to compute their own driving path in their head. In this sense, geospatial tools help them leverage geographic data in a context that is intensely personal.
Collection of mapping technology
So what tools and technology are considered geospatial in nature? As noted in the “stack” of technology above, it is a wide-ranging set of technology. It can be helpful to look at the two types of end-users that typically leverage geospatial technology: software developers and data analysts.
Geospatial developers take data of interest, depending on their domain, and create applications that allow their target audience to interact with the data in a meaningful way. This may mean taking data that is not always spatial in nature – like a list of addresses or stores running sales – and turn it into a component on a map for viewing and querying.
Location-based applications using GPS tracking on a device are also used by developers to give localized awareness of nearby data or attributes the developer wants to expose.
Geospatial analysts – often work more behind-the-scenes and provide types of data analysis outputs that get used by application developers, GIS users, or even in reports or web sites for general public consumption.
Geospatial analytics for all
Analysis with geospatial data components is not limited to one domain of analyst anymore. Data scientists or business analysts may combine data from many sources – spatial or not – to provide a common operating picture of a business or project.
Therefore, libraries and processes for analyzing geospatial data have become ubiquitous or are at least a common subset of analytical routines that many have access to. Both desktop and web-based approaches to sharing data along with analytical tools continues to grow in popularity.
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