With an increase in programming literacy, GIS applications now use programming more than ever. From the mapping of tabular data to the most advanced AI workflows, programming serves to make spatial analysis more efficient and scalable than ever before. Programming alone cannot accomplish many GIS tasks, such as georeferencing and digitization, but it can automate many of the time consuming processes, once that process has been established.
All GIS software is built on programming languages and the GIS libraries which are written in programming languages, such as C++ or Python. For example: when using a GIS software such as ArcGIS Pro or QGIS, you are also using programming libraries such as GDAL/OGR. Instead of using GDAL through traditional software, you can directly use GDAL through your Python code, allowing you to save the time and resources for other tasks. This is very important for repetitive tasks, or tasks which require more computational power than your computer allows. Using Python, you can automate a process, and have this process run on a cluster computer in parallel. If you are doing transformations of thousands of satellite images, or finding the intersections of every waterway and roadway in a country, or running global scale statistics, you will need to use Python.
Other programming languages are quickly becoming popular for mapping. For example: R is a statistics language that has statistical packages for spatial statistics. While spatial statistics can be conducted using traditional GIS software such as GeoDa, cutting edge statistical methods are usually implemented using code, because this allows researchers to modify existing methods and create new ones from scratch, rather than being confined to the methods available in a traditional GIS software. Once a new method is widely understood, refined, and accepted, it may become part of a GIS tool or plugin. However, in order to replicate the latest research, you may need to use a contemporary GIS approach which is centered around programming and GIS.
Popular programming languages for GIS include: Python, C++, R, and Javascript.
Python is often the best choice for scientific workflows and easy automation, while C++ is better for big data, parallel computing, and faster computing times. Either can be used for creating new algorithms and examining existing methods, but Python is now a leader in the scientific community, making Python the programming language of choice for integrating more advanced analysis methods, such as artificial intelligence. Javascript is often used in the creation of interactive data visualizations such as webmaps and dashboards.
Research reproducibility is another factor that favors programming. When researchers use open source programming, it makes their research output more reproducible and verifiable. Sharing source code increases workflow transparency, and allows other researchers to improve upon your work. Two hallmarks of high quality experiments are replicability and repeatability. Additional benefits to using contemporary GIS methods include integration with version control software such as Git, cross-platform compatibility, greater scalability, and increased collaborative potential.
Many companies are actively incorporating GIS methods and analysis into their products and services. From logistical behemoths like Amazon, to Covid-19 maps from the NY Times, companies of all size and industry are improving by finding meaningful ways of using GIS to augment their business.
To illustrate how many industries are using GIS below is a brief list of businesses and industries you may have heard of that use GIS:
| Industry | Example Companies | How they use GIS |
| Agriculture | Bayer, Monsanto, Syngenta, John Deere | Using precision agriculture, farmers and agriculture firms use the latest remote sensing data to determine which crops are over or under nourished, prone to flooding, prone to disease, ready for harvest, and track and resolve inefficiencies. Tractors are often semi-autonomous. |
| Automotive | General Motors, Tata Motors, Ford, Tesla, Geely, VW, Toyota, Honda | Many major car manufacturers are working on some level of spatial awareness, and some are working on developing autonomous or semi-autonomous vehicles. Many cars come with built in LiDAR, radar, and GPS sensors. |
| Aviation and aerospace | Boeing, NASA, SpaceX, commercial airlines, Northrop Grumman | A large amount of GIS data comes from remote sensing platforms such as drones and satellites, but many GIS tools are used to improve the precision and accuracy of our latest airplanes, rockets, and drones. |
| Cloud services, telecommunications | AWS, Azure, Sprint, Verizon, ATT | Computer networks are as fast as they are, thanks to GIS which seeks to optimize the amount of time it takes for data to get from its origin to its destination at a low cost. This is especially true for the first and last mile of transmission - the placement of cell phone towers is important to users and requires GIS. |
| Ride and Bike share programs | Uber, Lyft, Lime, bike share programs | Uber and Lyft give drivers recommendations for nearby ride-hailers, and also solve a traveling salesman problem in a way that optimizes the experience for the driver and user. Bike and scooter share programs use GIS to track vehicles, plan where stations are, and when and how many vehicles to deliver. |
| Food delivery | DoorDash, Instacart, Grubhub, Uber Eats | Similar to ride sharing apps, Instacart and others use GIS to inform drivers what the best route is route their deliveries. |
| Search and recommendations | Google, Bing, Yahoo, Yelp | Many users care more about nearby goods and services, so websites will use GIS to organize results based on proximity. |
| Social media | Meta, Alphabet, Twitter, TikTok | Social media uses GIS to connect users with local trends, popular posts, and businesses |
| Logistics | UPS, FedEx, DHL, Amazon.com, USPS, Walmart, Target | Getting goods from one place to another in a cost effective and short time is accomplished using GIS. |
| Insurance | Allianz, Cigna, State Farm | GIS is used to estimate and manage risks, such as flood, fire, hurricane, drought, social unrest, political uncertainty, threats to health and safety |
Additionally, GIS is used many government agencies, such as city and urban planning departments and city services, highway, weather, and transportation departments, police and fire departments, EMS, state level departments of public health, and 3-4 letter agencies such as: USGS, EPA, BLM, CDC, DOE, DOD, NGA, CIA, DOA, FEMA, NOAA, NWS.