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GIS is primarily an acronym that stands for Geographic Information Systems, but the term has expanded to reference the entire discipline of geospatial science and technology.
GIS computer programs allow users to manage, store, create, edit, and display spatial data, which includes a location component as well as descriptive or quantitative information. Making maps is just the beginning—GIS enables analysts to monitor change over time and across space, identify patterns and relationships between entities, and explore how geography impacts communities.
Mapping technology is being used in almost every industry, including environmental mitigation, emergency response, farming and forestry, real estate, as well as government and law enforcement.
History and Background
What we know as GIS today began as computational mapping in the 1960s. Land resource managers and navigators transitioned from physically layering paper maps on top of each other to storing coordinate data and developing spatial systems for digital access.
One of these systems was the Canadian Geographic System, developed by Roger Tomlinson, who is now widely regarded as the father of GIS. Tomlinson’s system was used to develop a national land inventory, which layered various types of environmental data to calculate, predict, and enhance crop production, a mission GIS is still used for to this day.
Around the same time, the US Census Bureau began to store their road and boundary data in digital geographic file formats. Institutions like Harvard and Esri started conducting research to enhance both computer graphics and spatial analysis. Throughout the 1970s and 80s, geospatial software was developed for some of the early computers, and by the 90s, as personal computers became more abundant and powerful, GIS proliferated throughout the user base.
It took decades for industries to recognize the power of GIS, and some educators, companies, and even government agencies still don’t fully embrace this technology. However, as the data and software become more mainstream and approachable, the true applications of geospatial tech are being realized.
Types of Data
In order to fully understand GIS software and its applications, you should first be familiar with the two types of spatial data: raster and vector. When used in GIS software, these data types are referred to as “layers,” because they are stacked on top of one another as if they were physically layered on a map.
Raster data can best be compared to photographs. In fact, many data types you’re already familiar with can fit into this category, including JPGs, PNGs, and TIFs. The data is stored in a grid, comprising small square pixels. The size of the pixels dictates the resolution, and each pixel is equipped with a value. Some examples of raster data include elevation, land cover, and of course, satellite imagery.
Vector data is visualized in the form of points, lines, and polygons. When you look at a map and see dots (i.e., locations of individual objects), lines (e.g., roads or pathways), and shapes (like buildings or bodies of water), these are all examples of vector data. In addition to the visual component, these features can be further enhanced with qualitative information, called attributes, accessible in tabular form. For example, the polygons may represent building footprints and location, but their attribution may tell users the type of building (school, store, home, etc.), when it was built, or who owns it.
Both types of data include spatial reference. This component is key to identifying the precise location and scale to which the data belong. The data must be tagged with a projection* so the software knows where on the globe to visualize it and ensure the rest of the data is properly aligned.
*Projections are mechanisms for creating a flat display out of the earth, which is impossible to do perfectly; therefore this process sacrifices one or more of the authentic components of geography, whether that’s size, shape, or distance (think Greenland: it looks massive on the average map because the globe has been stretched to lay flat). When creating data, always select a projection that prioritizes the location you are working with or the format that you’ll be presenting in.
Software and Hardware
The predominant geospatial software platforms are ArcGIS and QGIS. These applications run on desktop or laptop computers and are used to import, manipulate, and visualize spatial data. Using the graphical user interface, operators can get a bird’s eye view of the landscape they’re exploring and layer on different types of raster and vector data to identify patterns, take measurements, make calculations, and configure maps.
These platforms have hundreds of built-in tools, extensions, and plug-ins that can be used to conduct complex analysis. The programs can save you time by automating tedious processes, such as counting the number of points within a given polygon, finding the precise center of an entity, or generating buffers around each feature. More advanced tools include determining site suitability based on your preferred parameters, visualizing statistically significant hot spots or clusters of features, or calculating the least-cost path between locations.
Of course, one of the main functions of GIS is to create maps. These software platforms allow users to alter the way the data is visualized, add labels and legends for clarification, and layer on additional effects and text. There are endless cartographic styles to deploy, as well as types of exports you can generate; you can even create interactive maps to be embedded on websites.
Traditional GIS platforms are accessed via computer, and it is important to have significant processing power, quality graphics, and sometimes even external storage space. However, for field efforts, there are lightweight GIS applications you can access on your mobile phone or tablet, which are critical for on-the-go data collection and navigation.
Applications and Industry
It is impossible to touch on every industry that GIS has permeated, because it’s become such a pervasive technology. Initially, GIS was developed for land management and navigation purposes, which remain major applications for GIS today; government agencies and emergency responders familiarize themselves with land use/land cover (LULC) data for situational awareness, and network analysis tools are only becoming more advanced with time.
Since the early days, urban planning was a major use case for GIS, and that still holds true. Many states, counties, municipalities, cities, and towns have their own online geospatial data portals, where they house official copies of administrative boundaries, parcel tracts, road networks, and other relevant data that is used by local authorities and the public alike. It is important to evaluate stormwater drainage, plumbing, electrical grids, elevation, and many other geographic factors when developing urban settings, all of which can be done using geospatial technology.
The environmental sector has also become a heavy user of GIS in recent years. With the development of robust ecosystem data, analysts and activists are able to perform endangered species habitat mapping, develop biodiversity enhancement plans, delineate wetlands, and even track and predict climate events and natural disasters. Similarly, farming and forestry professionals use GIS to monitor their agricultural and foliage production, incorporating weather and soil data to establish correlations with external factors.
But there are some unexpected GIS applications as well. Banks are creating online mapping tools to direct users to the closest ATMs, and gas stations are broadcasting their price per gallon so drivers are tempted to stop along their route. Retailers are conducting spatial market analysis to determine the best place to build new stores, and economists are spatializing supply chains to uncover weaknesses and inefficiencies. Crime and flight patterns are being mapped and tracked, as are oil spills and wildfires. Plus, predictive analytics are being generated based on the correlation of these events with other factors and circumstances. Along with artificial intelligence, GIS may be one of the best tools we have for predicting the future.
The potential use cases for GIS are rapidly evolving to incorporate industries and users its founders probably never thought possible. With cloud computing, automated models, machine learning, and an array of new data storage technology, there is no limit to what geospatial systems will be able to achieve. There has never been a better time to get educated in geospatial technology and start collaborating with other spatially-minded people.