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As Seen In: GISCafe Explores Artificial Intelligence Impact on GIS and Asset Management


Artificial intelligence/machine learning helps Trimble eCognition software recognize and classify features in satellite and aerial imagery, such as buildings, roads and vegetation. Source: Trimble

By Gareth Gibson, Marketing Director, Mapping & GIS Solutions at Trimble Inc. 

The GIS industry is experiencing a period of rapid change and growth, and the increasing use of artificial intelligence and machine learning (AI/ML) is playing a crucial role in driving this development. By enabling GIS professionals to process and analyze data quickly and accurately, these technologies are helping to unlock the full potential of GIS and drive innovation and progress in the field.

Powerful AI/ML Hits Mainstream

When predicting trends in the GIS (geographic information system) industry in 2023, consider the major breakthroughs the IT industry experienced in 2022. Of particular interest are the AI/ML systems that burst into our collective consciousness, with several headline-grabbing products making waves.

One notable example is ChatGPT, the AI/ML-based artificial assistant application from OpenAI. ChatGPT can be accessed from any internet-connected device with a web browser and has an uncanny ability to provide human-like written responses to almost any form of text input. While the tool is currently only available as a research release, it garnered huge interest (millions of users around the globe) as early adopters found unique and interesting ways to interact with the tool. It’s been used for tasks ranging from intelligible responses to questions or prompts like “write an essay about the negative effects of COVID-19 on the semiconductor supply chain” to extracting complex information from unstructured data, like identifying patterns in unstructured text such as survey responses or newspaper articles on a topic.

ChatGPT highlights just how far the field of AI/ML systems has come in a relatively short time. And because it is so accessible (all you need is a phone and an internet connection) it has significantly raised the profile of the technology, making everyone who tries it curious about the ways it may influence and change industries in exciting and unexpected ways. (While tempting, I can confirm ChatGPT did not write this article.) 

The term “AI/ML system” refers to the integration and use of machine learning techniques in the development of artificial intelligence systems and applications. Machine learning is a subfield of artificial intelligence that involves the use of algorithms and statistical models to enable systems to learn and improve their performance over time, without explicit programming. By combining AI and ML, it is possible to build systems that can learn from data and make “intelligent” decisions, as well as adapt and improve their performance over time. AI/ML has many applications in a wide range of fields, including computer vision, natural language processing, robotics and more. 

Data Analysis Impacts on GIS

In the fields of mapping, GIS, and asset management, one of the greatest benefits of AI/ML systems will most likely come from the ability to process and analyze large amounts of data far more quickly and accurately than any human can. These technologies enable GIS professionals and asset owners to extract valuable insights and information from spatial and asset-based datasets previously too large or complex to analyze manually and quickly identify patterns. This results in more informed decisions and a better understanding of the world around us.

Some real-world examples of how AI/ML systems are already in use in GIS solutions include:

  • Image recognition and classification — Recognizing and classifying features in satellite and aerial imagery, such as buildings, roads and vegetation. These tools can be used to extract useful information from large datasets of images and can help automate mapping and data analysis tasks.

  • Predictive modeling — Building predictive models for forecasting events or patterns based on historical data. These models can be used in a variety of GIS applications, such as predicting land use patterns or assessing the risk of natural disasters. Predictive modeling is hugely important for asset and landowners who want to optimize resource use, worker safety and return on investment in asset infrastructure.

  • Enterprise asset management — Integrating connected data into leading-edge asset management solutions provides owners with game-changing visibility throughout the entire asset lifecycle. During Planning, Design, and Construction, as well as in the Operations and Maintenance phase, government agencies and other asset owners are armed with more informed decision-making capabilities. They can identify risk exposure, analyze multiple scenarios across multiple timeframes to determine the best investment strategies for the short and long term, and ultimately allocate limited funds most effectively.

  • Spatial analysis — Performing complex spatial analysis tasks, such as identifying patterns and trends in data and predicting the likelihood of certain events occurring in a particular location.

  • Robotic mapping — Enabling robots and autonomous vehicles to navigate and map their surroundings using sensors and cameras.

These are just a few examples of AI/ML technologies driving innovation and progress in the GIS industry. The sophistication and capabilities of these tools will only improve and expand, enabling organizations to do more with their data to make more informed and accurate decisions. It is fascinating to watch this technology evolve to help and improve the way we work.

First published in GISCafe here.