Geospatial intelligence is the ability to process and make decisions based on spatial data. Spatial data is a set of information that describes locations in space.
A large percentage of the data we use today is linked to physical locations. Hence, geospatial intelligence is practical knowledge that requires not only displaying location data but also a deep understanding of where things are, why they are and what is likely to happen in a certain location. By gathering spatial data and using critical spatial analytics, we can solve real-world problems.
In the business world, you’ll hear this referred to as location intelligence. In the defense industry, it’s known as GEOINT. Despite the difference in names, geospatial intelligence serves to harness spatial data through spatial analytics and reasoning.
What Is Geospatial Intelligence?
Geospatial intelligence (also known as location intelligence or GEOINT) is the practice of collecting information and making decisions based on the analysis of spatial data and imagery, which is data that references a specific geographical location.
Why Is Geospatial Intelligence Important?
Business leaders, military officers and public service providers rely on geospatial intelligence insights to plan events, manage markets and respond to emergencies. Use cases of geospatial intelligence are widely spread across domains and industries. Whether we use geospatial intelligence for military, business or public service, it’s critical to providing insights into what happens on Earth, where it happens and why.
How Does Geospatial Intelligence Work?
Geospatial intelligence helps organizations visualize and analyze spatial data to understand why a certain place or feature is important for a given issue. Spatial information is not intelligence per se; instead, the insights we derive from geospatial intelligence are its real value.
For example, we can use satellite imagery to see where things are on Earth in order to provide contextual foundations but we need an analyst to synthesize and communicate information in an organized way to develop a comprehensive intelligence product. Artificial intelligence is, however, revolutionizing geospatial intelligence practices through the automatic classification and detection of objects from satellite imagery.
History of Geospatial Intelligence
Geospatial intelligence can be traced back to the 19th century, with early examples including rudimentary maps and compasses. One of the most well-known early examples of geospatial intelligence is Dr. John Snow’s 1854 London cholera map. By collecting data and mapping the locations of cholera cases in water pumps, Snow identified cholera as a waterborne disease and not airborne one, as it was generally believed to be. Although the term “geospatial intelligence” would not be coined for another 150 years, Snow demonstrated that its core concepts could generate insightful — and, in this case, life-saving — results.
In the 1960s, geospatial intelligence saw many new developments, with the most notable being the creation of geographic information systems (GIS). GIS uses computers to capture, store, manage, analyze and visualize all types of geographic data, allowing individuals to more easily see and interpret the information in ways that can reveal relationships or trends. Roger Tomlinson is considered one of the most important figures in this field, often called the “father of GIS” for helping develop Canada’s geographic information system starting in 1963. The application was one of the first to utilize GIS, and helped analyze the country’s land inventory with the assistance of satellite imagery and global position systems (GPS).
Today, geospatial intelligence is still a rapidly developing field, especially with the advancements in artificial intelligence and data analytics. These technologies enable new forms of analysis and make geospatial intelligence applicable to a wider range of industries, especially defense and national security. Military and intelligence agencies use GEOINT for a number of critical missions. For example, analysts review satellite and drone imagery to monitor foreign military activities, track the movement of assets and identify threats in near real time.
Advantages of Geospatial Intelligence
Stacking different layers of spatial data to produce geospatial intelligence provides many benefits.
Helps Identify Relationships in Spatial Data
Geospatial intelligence helps us identify the relationship between different spatial data sets, which is not readily available without layering together and scrutinizing locational data.
Provides Detailed Location Information
In addition, geospatial intelligence provides detailed information about where things, people or critical resources are located.
Can Help Determine the Probability of Disasters
Geospatial intelligence practices can help prevent disasters by helping us develop models for determining the probability of an event happening in the future.
This can be particularly helpful when tracking the likelihood of a natural disaster or disease outbreak.
Disadvantages of Geospatial Intelligence
Intricate and Discipline-Specific
Despite its many benefits, the main drawback is that spatial intelligence has many components, techniques and processes you need to pull together to achieve your objectives. It’s truly a discipline-specific practice.
Software Packages Will Vary Between Applications
No software package can offer all the spatial intelligence functionality you need across disciplines, industries or applications. The applications of spatial intelligence in defense, for example, are much different than their application in real estate, and as such require different kinds of geospatial intelligence software.
What Software and Tools Are Used in Geospatial Intelligence?
Remote sensing and geographic information systems (GIS) software play a key role in geospatial intelligence. Specialized software like ENVI and ArcGIS spatial analyst or defense mapping can leverage images from satellites and drones, as well as spatial vector data. Google Earth also provides basic functionality for geospatial intelligence purposes. Additionally, we can use many open-source GIS software to derive geospatial intelligence insights, including QGIS and GRASS.
Geospatial Intelligence Use Cases
Defense
The defense industry is a popular use case for. By collecting and analyzing a bevy of satellite imagery and geographical data, defense agencies can monitor for threats, support military operations and assess terrain for strategic planning.
Augmented Reality
Geospatial intelligence is essential for augmented reality. Using sensor data, a computer processes and layers various forms of information to anchor digital content for a game or experience to real-world environments.
Environmental Monitoring
Using satellite imagery, remote sensing and geographic information systems, organizations like the National Oceanic and Atmospheric Administration (NOAA) can collect and analyze data to track various environmental conditions, including climate change and deforestation.
Real Estate
Geospatial intelligence provides real estate professionals with tools to analyze granular data, including demographics, traffic and infrastructure. Leveraging this data can lead to more informed investment choices.
Frequently Asked Questions
What is an example of geospatial intelligence?
An example of geospatial intelligence is a weather center using satellite imagery to actively monitor the location and trajectory of an incoming hurricane.
What is the difference between GIS and geospatial intelligence?
Geospatial intelligence is the practice of analyzing geospatial data and extracting insights to help make decisions, whether for public service, military or other operations. GIS, or a geographic information system, is a computer system used to store and manage geospatial data. It is a tool and type of technology that can help facilitate geospatial intelligence collection.
