Geospatial Intelligence (GEOINT) is the discipline of analyzing and interpreting information about the Earth’s surface and its geospatial features, as well as human activities that take place on it. Engineers use advanced tools and techniques such as AI-based detection using satellite imagery, geospatial entity recognition, and Open Source Intelligence analyzing crowdsourced data. GEOINT is a critical component of modern decision-making processes in fields such as national security, disaster response, urban planning, natural resource management, and many others.
Using GEOINT capabilities to best effect, one must possess a deep understanding of various concepts and principles related to geography, cartography, remote sensing, image analysis, data management, and visualization. In addition, knowledge of geospatial data formats and standards, as well as geospatial analysis techniques and statistical methods, is essential for effectively analyzing and interpreting geospatial data.
Expertise in geospatial tools and technologies, such as GIS software, satellite imagery processing software, and various types of remote sensing sensors, is essential for effectively capturing, processing, analyzing, and visualizing geospatial data. Finally, a strong understanding of the ethical and legal implications of GEOINT is also critical for ensuring that the information gained through geospatial analysis is used ethically and appropriately.
Geospatial Intelligence Capabilities
GEOINT is a complex field that encompasses a wide range of capabilities and tools. We introduce some of the most important GEOINT capabilities.
Geospatial Data Acquisition
The ability to collect, process, and analyze geospatial data from a variety of sources, including satellite imagery, LiDAR, GPS, and any spatially enabled crowdsourced data. Since geospatial data is the primary source for all GEOINT workflows, it is established as being the geospatial ground of truth.
 ArcGIS Living Atlas
ArcGIS Living Atlas of the World is the foremost collection of geographic information from around the globe. It includes maps, apps, and data layers to support your work.
 ArcGIS Open Data Hub
ArcGIS Hub is an easy-to-configure cloud platform that organizes people, data, and tools to accomplish initiatives and goals.
 Copernicus Open Access Hub
The Copernicus Open Access Hub provides complete and open access to Sentinel-1, Sentinel-2, Sentinel-3 and Sentinel-5P user products, starting from the In-Orbit Commissioning Review (IOCR).
 Natural Earth
Natural Earth is a public domain map dataset for making a variety of visually pleasing, well-crafted maps with cartography or GIS software.
OpenStreetMap is built by a community of mappers that contribute and maintain data about roads, trails, cafés, railway stations, and much more, all over the world.
Geospatial Data Management
The ability to effectively manage and store geospatial data, including metadata, in order to ensure that it is easily discoverable, understandable, and reusable, which can help to promote collaboration, facilitate research, and increase the overall impact of GEOINT. Often these FAIR data principles are a set of guidelines designed to promote the use of spatially enabled data in a consistent and reusable manner.
The ability to use statistical and mathematical techniques to analyze geospatial data and develop predictive models that support decision-making.
The ability to create and present geospatial data in a visual format that is easy to understand and interpret, using tools such as maps, charts, and graphs.
Geospatial Intelligence Analysis
The ability to integrate and analyze geospatial data with other forms of intelligence, such as human intelligence, signals intelligence, and open-source intelligence, to produce actionable intelligence. These other intelligence disciplines provide the high-level context to geospatial data and include additional perspective to ensure more comprehensive GEOINT insights.
All source intelligence provides the most comprehensive intelligence insights by considering all forms of intelligence. It includes information from all accessible sources, while multi-source intelligence uses a more targeted approach, focusing only on specific sources.
The ability to interpret and analyze geospatial data, including satellite imagery and other remote sensing data, using advanced analytical techniques to identify and extract information from images.
Geospatial Intelligence Training
The ability to provide training and education to GEOINT professionals on a wide range of topics, including data acquisition, analysis, and visualization techniques, as well as ethical and legal considerations in the field.
Geospatial Intelligence Workflow
The GEOINT workflow, also known as the intelligence cycle, is a process that is used to gather, analyze, and disseminate intelligence information. The intelligence cycle consists of six major steps: planning and direction, collection, processing, analysis and production, dissemination, and evaluation.
GEOINT preparation is a process used by planners to gain a better understanding of the physical environment in which operations will take place. It involves the collection, analysis, and dissemination of geospatial data in order to support mission planning, target analysis, and situational awareness.
There are several documents that describe the geospatial intelligence workflow and the intelligence cycle in more detail.
Intelligence doctrine and guidance
This type of document outlines the principles, policies, and procedures that govern intelligence activities within an organization. It may include guidance on the intelligence cycle and the roles and responsibilities of different stakeholders within the intelligence community.
Standard operating procedures
Are detailed instructions that outline the steps and processes that should be followed to carry out specific tasks or activities. They may include guidance on the intelligence cycle and how to apply it in different contexts.
Training materials, such as manuals or course materials, may include information on the intelligence cycle and how to apply it in different situations.
Best practices and case studies
Best practices and case studies can provide examples of how the intelligence cycle has been applied in real-world situations and can offer guidance on how to effectively use the intelligence cycle in different contexts.
Geospatial Intelligence Services
GEOINT services offer ready-to-use very high readiness joint geospatial capabilities. You can integrate these geospatial capabilities into any workflow.
 geoconflicts API @RapidAPI
Query armed conflict events worldwide and visualize them using spatial aggregations.
 geoprotests API @RapidAPI
Query broadcasted events worldwide and visualize them using spatial aggregations.
Geospatial Intelligence Tools
GEOINT tools assemble ready-to-use very high readiness joint geospatial capabilities. You can use these geospatial capabilities to build and extend various mapping and GEOINT enabled applications.
 georapid-py @GitHub
Query broadcasted news worldwide and visualize them using spatial aggregations. This modern Python module represents an idiomatic client accessing the Geospatial Knowledge APIs being hosted at Rapid API Hub.
 geoint-py @GitHub
A bunch of geospatial intelligence workflows implemented using Python.