An easy glossary of geospatial and GIS terms
If you’ve ever come across terms like “geospatial data,” “DEM,” or “point cloud,” and wondered what they mean, you’re not alone. The world of Geographic Information Systems (GIS) and geospatial technology is filled with jargon that can feel overwhelming if you’re new to the field. But don’t worry — we’re here to break it all down for you, no degree in cartography required.
This guide walks through some of the key terms, providing simple explanations to help you feel more confident the next time you encounter them. Let’s dive in!
Geospatial data
At its core, geospatial data is information that has a location tied to it. This could be the coordinates of a specific building or the outline of a country’s borders. It's what helps us map and understand physical spaces. What makes geospatial data valuable isn’t just that it shows where something is, but that it allows different datasets to be compared and understood in the same spatial context.
Once data is geospatially referenced, it can be layered with other information such as elevation, imagery, or asset data. This shared spatial context is what allows teams to discuss the same site, area, or feature without ambiguity.
Examples:
- A set of inspection notes becomes far more useful when each observation is tied to a precise location, allowing multiple people to review and interpret the same information on a map.
- Imagine you’re looking at a map of your city on your phone. The streets, parks, and restaurants displayed are all examples of geospatial data — they exist in a specific location on Earth.
GIS (geographic information system)
A geographic information system (GIS) is the tool used to analyze, store, and visualize geospatial data. Think of it as the brain behind the map. Rather than working with isolated files or maps, GIS allows multiple datasets to be viewed and explored together.
Modern GIS workflows often focus on collaboration and comparison, making it easier for teams to review data, overlay different layers, and understand how spatial information connects across a project.
Example:
A planning team might use GIS to review terrain, infrastructure, and environmental data together to better understand constraints and opportunities in a given area.
GPS (global positioning system)
We’re all familiar with GPS — it’s what powers the location services on your phone or the navigation system in your car. GPS is a satellite-based system that tells you exactly where you are on the globe, by providing coordinates like latitude and longitude.
Example: When you use Google Maps to get directions, GPS is what provides your real-time location on the map.
Remote sensing
Remote sensing refers to the process of gathering data about the Earth’s surface without physically touching it. Typically, this is done using satellites or drones, which capture images and data from the air or space.
Example: Satellites orbiting the Earth can collect images of forest coverage over time to monitor deforestation or track changes in sea levels.
Orthomosaic
An orthomosaic is a high-resolution map created by stitching together many overlapping aerial images and correcting them for distortion. Because orthomosaics are geometrically accurate, measurements taken from them reflect real-world distances and areas.
Orthomosaics are often used as a shared reference layer, providing a clear, up-to-date visual view of a site that different stakeholders can refer back to.
Example:
On construction or infrastructure projects, orthomosaics are commonly reviewed to understand site progress and identify areas that need closer inspection.
DEM (digital elevation model)
A digital elevation model (DEM) is a digital representation of the Earth’s terrain surface, showing elevation values across an area. DEMs focus on ground elevation and typically exclude surface features like buildings or vegetation.
Elevation data plays a key role in understanding how landscapes behave, particularly when assessing slope, drainage, or potential change over time.
Example:
Engineers may use DEMs to assess how terrain influences water flow or to identify areas where erosion risk may be higher.
Contour lines
You’ve probably seen contour lines on a topographic map. These wavy lines show the elevation and shape of the land. The closer together the lines are, the steeper the terrain.
Example: If you’ve ever gone hiking, those contour lines on your map tell you how hard the climb will be. Lines packed closely together mean it’s going to be a steep ascent!
Point cloud
A point cloud is a collection of millions of individual 3D points, each representing a precise position in space. These points are generated using technologies like LiDAR or photogrammetry and form the foundation for many 3D spatial outputs.
Point clouds are valuable because they preserve detailed spatial information, allowing measurements, analysis, and interpretation from multiple perspectives.
Example:
In infrastructure and construction, point clouds are often reviewed to understand complex structures or terrain before creating simplified models.
Georeferencing
Georeferencing is the process of aligning spatial data (like an image or map) with a specific location on Earth. This makes sure that when you overlay one layer on top of another in a GIS, they match up perfectly.
Example: You could take an old paper map, scan it, and georeference it so it lines up correctly with modern satellite imagery in a GIS platform.
Geodatabase
A geodatabase is just like a regular database, but it stores spatial data. It’s where all your maps, layers, and location-based information are kept when working in GIS.
Example: If you were working on a city planning project, your geodatabase might contain layers for roads, buildings, and parks — all neatly organized in one place.
Layer
In GIS, a layer is a set of data that you can view separately or combine with other data. For instance, you might have one layer showing the streets of a city and another layer showing the locations of hospitals. By layering them together, you can analyze how accessible hospitals are from different parts of the city.
Example: Layers work like transparencies you can stack on top of each other, letting you view different types of data in one map.
Raster data vs. vector data
These are the two main types of geospatial data formats: raster and vector data.
Raster data is made up of pixels or grid cells, with each cell containing a value. Satellite imagery, aerial photos, and elevation grids are common raster datasets. Raster data is particularly useful for representing continuous surfaces.
Vector data uses points, lines, and polygons to represent discrete features such as assets, boundaries, or routes. Vector data is often easier to query and analyze for specific features.
Example:
An orthomosaic image is raster data, while inspection points or asset boundaries placed on top of it are vector data.
LiDAR (light detection and ranging)
LiDAR is a remote sensing method that uses laser pulses to measure distances to the Earth. This creates highly accurate, high-resolution 3D models of the terrain.
Example: LiDAR is used in self-driving cars to detect nearby objects, or in forestry to measure tree height and canopy density.
GCP (ground control point)
A ground control point (GCP) is a specific point on the ground with known coordinates. It’s used to improve the accuracy of drone mapping and geospatial data by ensuring that what you see in the images matches up with real-world positions.
Example: In construction, GCPs help drone maps line up perfectly with ground features, so measurements for building sites are precise.
UTM (universal transverse mercator)
The UTM is a system of dividing the world into a grid to make mapping easier. It uses meters instead of degrees to measure locations, which can be more practical for some types of work.
Example: While latitude and longitude tell you where you are in degrees, UTM tells you your exact position in meters on a flat grid — much easier for engineers!
Attribute data
Attribute data describes the characteristics of geographic features. In a GIS, it’s the additional information about a feature that helps provide context. For example, a road might have attribute data that tells you its name, speed limit, or whether it's a one-way street.
Example: Attribute data is what allows you to click on a point on a map and get detailed information, like the type of tree species in a park.
Spatial analysis
Spatial analysis to the process of examining geospatial data to identify patterns, relationships, or trends based on location. It goes beyond visualization and focuses on answering questions using spatial logic.
By combining multiple layers of data, spatial analysis helps turn maps into insight rather than static visuals.
Example:
A city might use spatial analysis to identify areas where population growth overlaps with limited access to essential services.
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Geospatial and GIS terms may seem complicated at first, but with a little practice, they become second nature. Whether you’re working on a large-scale environmental project or just want to better understand how GPS works, knowing these key terms will make navigating the geospatial world much easier.
Looking for a way to dive deeper into geospatial data and make it work for your projects? Birdi’s tools can help you visualize, process, and analyze your geospatial data with ease. Give it a try and see the difference it can make!