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Artificial Intelligence-driven geospatial analytics could change the world
Artificial Intelligence-driven geospatial analytics could change the world
Today artificial intelligence is shaping a better way. Although AI is still relatively new to the geospatial industry, it allows professionals in various fields to work more efficiently and accurately, respond to issues faster, and save money. Property insurance companies can better pinpoint risks. Banks can speed up disbursement of loans to farmers. Utilities can better understand where to and where not to lay transmission lines and more.
Artificial intelligence processes multiple layers of complex data and images to provide insights more accurately and faster than humans.
Prospects and Problems of Geospatial Technology
Commercial companies want to gain insights from geospatial data, but they want an easier way to find them. Deloitte reports that by next year, 36% of large and medium-sized organizations are expected to deploy location intelligence software, up from 10% in 2019.
Geospatial data is a bunch of information: GIS maps, lidar images, survey records. Remote sensing data obtained from satellites require processing to be useful to most researchers and other users. A single data source is often insufficient, so modeling often requires piecing together disjointed data sources.
Geospatial analysis requires multiple steps and specialized skills. Data needs to be collected from various sources and converted into multi-layered visual representations and mappings. Sources include Earth observation, geographic information systems (GIS), global satellite navigation systems and drone 3D scanning.
Needs to analyze the mapping to determine the pattern. This process may require remote sensing and image processing tools, mapping skills and other specialized talents, as well as specific programming languages.
Meticulous Research reports that the use of AI-based GIS solutions across different industries is rapidly advancing the data collection and cleaning process to improve forecast accuracy. The geospatial analytics market is expected to grow at a CAGR of 17.6% from 2021 to 2028, reaching $256 billion.
AI unlocks the potential of geospatial data
Deloitte points to areas of application: businesses optimizing their supply chain networks; governments improving land management practices; power companies managing vegetation along power grids risk.
Technology solutions are leveraging artificial intelligence to act faster, save money and stay safe. AI can handle menial tasks, analyze large amounts of data points, improve accuracy, and deliver timely takeaways.
Through automation, artificial intelligence can extract information and provide insights in real time. AI algorithms can predict wildfire risk, identify wetlands, classify vegetation types to evaluate reclamation activities and provide countless applications.
For example, energy companies can use this technology to understand the environmental risks faced by their pipelines, such as landslides and floods, and how best to prioritize monitoring efforts. Better manage the environment, save money, and help ensure public safety.
Conventional climate models may be too broad and outdated. Trends in increased precipitation over the years may be less important than understanding where soil erosion poses landslide risks to infrastructure. Without the need for on-the-ground assessments, teams using artificial intelligence to analyze lidar image information can assess impacts without putting people in harm’s way.
What will happen in the future
As geospatial technology and imaging technology continue to improve, the possibilities for the future can be imagined. Just look at your phone to see how much progress has been made in just a few years. What's your best camera? Your smartphone. What's the best sat nav system for you? Your smartphone.
It’s no coincidence that artificial intelligence is now helping analyze satellite images to better understand climate change. "Our goal is to pioneer a new combination of deep learning algorithms and decades of physics knowledge to create synthetic high-resolution satellite images of Antarctic surface melt," said Guido Cervone, associate director of Penn State's Institute for Computational and Data Sciences.
AI-led approaches to geospatial analysis will revolutionize the way many professionals work – more efficiently, accurately, timely and securely, and more insightfully. At the same time, it will change their industry and the world.
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