GeoAI

AI-driven geospatial workflows

Discover how organizations are building a more resilient future with accelerated spatial problem-solving

Satellite image of land with extracted buildings colored red and green land and trees

Definition

What is GeoAI?

Geospatial artificial intelligence (GeoAI) is the application of artificial intelligence (AI) fused with geospatial data, science, and technology to accelerate real-world understanding of business opportunities, environmental impacts, and operational risks. Organizations are modernizing operations to run at scale through automated data generation and approachable spatial tools and algorithms. 

Extract rich geospatial data with deep learning

Save time by automating the extraction, classification, and detection of information from data such as imagery, video, point clouds, and text.

Perform predictive analysis using machine learning

Build more accurate models. Detect clusters, calculate change, find patterns, and forecast outcomes with spatial algorithms backed by experts.

Aerial image of buildings, homes, and green trees along a coastline and blue ocean

Model the real world for prediction

Aerial imagery is used to extract imagery of buildings and roads in Grenada to identify the population and infrastructure at risk for landslides.

Value

Why is GeoAI important?

GeoAI is transforming the speed at which we extract meaning from complex datasets, thereby aiding us in addressing the earth’s most pressing challenges. It reveals and helps us perceive intricate patterns and relationships in a variety of data that continues to grow exponentially. Organizations leveraging GeoAI are revolutionizing how they turn data into information, with models that adapt even as data evolves. 

Improve data quality, consistency, and accuracy

Streamline manual data generation workflows by using the power of automation to increase efficiency and reduce costs.

Accelerate the time to situational awareness

Monitor and analyze events, assets, and entities from sensors and sources such as video to enable quicker response times and proactive decisions.

Bring location intelligence to decision-making

Make data-driven decisions with real-world awareness. Improve business outcomes with insight from spatial patterns and accurate predictions.

Aerial image of a landscape that includes a field and hills with green trees, ponds, and roads

Create a sustainable future

Optimize resource management and understand the impact of business decisions on the community to reduce waste and better plan and manage sites.

How is GeoAI used?

GeoAI is used in various industries and applications to tackle challenges and proactively seize opportunities. Explore how GeoAI is used to optimize crop yields, heighten community safety, streamline asset inspection, shorten emergency response times, and more.

  • State and local government

    GeoAI is accelerating the speed at which government officials better serve communities using data. By leveraging GeoAI, governments can model the impacts of urban development, understand the availability of resources to the population, forecast road and infrastructure deterioration, and identify land-use change (such as new buildings) to proactively take action.

  • Natural resources

    GeoAI is revolutionizing the precision agriculture market by aiding the automated detection of invasive species. It helps the oil and gas industry monitor assets through automated extraction of flares, new well pads, or field access roads. Foresters and landowners use GeoAI to give them knowledge about the volumes and species of trees without a time-consuming on-site inspection. 

  • National mapping and statistics

    GeoAI is enhancing the responsiveness, productivity, and speed of product delivery for national mapping agencies. Through automation, these organizations are scaling their internal capacities and production workflows. A national mapping department can quickly update a nation's geographic information system (GIS) in hours, not months or days.

  • Defense and intelligence

    GeoAI is speeding up how organizations extract information, identify patterns, and determine changes in big data. An intelligence organization can support its activity-based intelligence efforts by automating how they analyze information related to events, entities, surveillance video, and remotely sensed data.

  • Public safety

    GeoAI is improving public safety as it relates to traffic accidents, emergency response, and disaster management. Organizations are making communities safer by predicting where accidents are likely to occur and optimizing emergency response times. Damaged infrastructure and navigable roads can be quickly identified to help allocate first responders.

  • Insurance

    GeoAI is helping insurance organizations understand the impact of an event in hours instead of days to improve claim processing and efficiently help members. Insurance companies can use imagery and GeoAI to detect and classify damage that impacts its members. With this understanding, they can get members back on their feet more quickly.

  • AEC

    GeoAI is transforming the architecture, engineering, and construction (AEC) industry with its ability to extract information from imagery, which feeds a digital twin. This data allows decision-makers to improve project management, identify potential risks, and optimize building performance. As a result, architecture firms can design energy-efficient buildings.

  • Business

    GeoAI is accelerating smart business decisions, delivering insight and predictions that drive better market planning, site selection, supply chain efficiency, and customer intelligence. With these insights, a business can respond to customer behavior and determine whether a new market area is viable based on pattern and predictive analysis of market characteristics.

Previous
Next
A large green field with rows of silver square solar panels

GeoAI for good

By providing decision-makers with accurate and timely information, GeoAI has the potential to positively impact various areas of society and contribute to the greater good. Explore how GeoAI is unlocking benefits in areas such as public health and conservation.

Read real-world stories

Getting started with Esri

Shorten the time to insights

Combine the world’s most powerful GIS and location intelligence software with the scalability and power of AI. Esri’s long-standing expertise gives you a trusted solution for extracting meaning from big data. Eliminate the need for large amounts of training data, massive compute resources, and extensive AI knowledge. Modernize how you approach spatial problems at scale with Esri.

START HERE

You don’t have to start from scratch

Getting started with GeoAI can sometimes feel like a daunting task. Use pretrained deep learning models and spatial machine learning tools backed by spatial experts. Our trained deep learning models provide the means for anyone to start extracting, classifying, detecting, and problem-solving with the data you have—no training data required. And our machine learning tools allow you to get started with UI-based tools with data-driven defaults that help guide you.

Explore pretrained models
Make predictions using ArcGIS
Satellite image showing a cluster of buildings with some outlined in red

FINE-TUNE TO YOUR NEEDS

Tweak our models to get them just right

With a starting point, you now have the means to focus on fine-tuning. Tweak our deep learning models and machine learning algorithms to fit your parameters and desired accuracy. We provide you the flexibility to tap into advanced settings and customize.

Learn how to fine-tune models
Vehicles on a 4-lane highway with a large red semi-trailer truck outlined with a green rectangle

BUILD CUSTOM MODELS

Integrate with open-source packages

If you have established methods, pair them with ours and models from the open-source ecosystem . Easily use popular models from libraries like Timm, MMDetection, and MMSegmentation. Leverage built-in connections to R and Python to bridge the gaps in your custom models.

Explore available models
A multi-colored aerial image in blue, green, red, and pink that identify parcels of land

Dive deeper

Discover more about spatial analysis, spatial data science, and working with remotely sensed data in ArcGIS.

Previous
Next

Learn how you can apply GeoAI

Schedule a conversation with one of our experienced sales consultants. Tell us about the workflows you’re trying to improve, and we’ll show you how GeoAI can support your organization.