From Photos to 3D Models: An Introduction to Photogrammetry and 3D Data in GIS

At my most recent company, Cupix, we worked with a 3D digital solution that transforms 2D images into detailed 3D models. The outputs included point clouds, meshes, and dollhouse-style views of real-world environments. This process is powered by photogrammetry—a technique that has become increasingly popular across industries like architecture, engineering, and construction (AEC), especially as the concept of digital twins gains momentum.

What Is Photogrammetry?

Photogrammetry is the science of using photographs and digital imagery to make accurate measurements and create 3D models or digital elevation models (DEMs). By capturing multiple overlapping images—typically using drones or handheld cameras—specialized software like Pix4D, Agisoft Metashape, or Esri’s SiteScan can reconstruct the geometry of physical spaces.

It’s particularly valuable in industries that require accurate spatial data, such as construction monitoring, site planning, and infrastructure maintenance.

Photogrammetry Method, Source: https://thehaskinssociety.wildapricot.org/photogrammetry

The Rise of Digital Twins

A digital twin is a dynamic, digital replica of a physical object or environment, continuously updated with real-world data. As organizations invest more in monitoring, simulation, and predictive modeling, photogrammetry becomes a foundational technology in building and maintaining these digital twins.

2D vs. 3D: What’s the Difference?

The key difference between 2D and 3D data in GIS lies in height awareness.

• 2D data is flat and uses a horizontal coordinate system (x, y) to locate features on a map.

• 3D data adds a vertical component (z-value), enabling features to be visualized and analyzed in three dimensions.

In 3D GIS environments, both horizontal and vertical coordinate systems define how features relate to one another in space.

Vertical Coordinate System

Types of 3D Data in ArcGIS

This summary is based on Esri’s Introduction to 3D Data, which provides a foundation for understanding the most common types of 3D data in ArcGIS:

Functional Surfaces

• TIN (Triangulated Irregular Network): Represents terrain using interconnected triangles, often used in elevation modeling.

  
  

  

  TIN (Triangulated Irregular Network), Source: Esri

  
  

• Raster Surfaces: Gridded data such as DEMs, used for representing elevation or other continuous surfaces.

Integrated Meshes

• Created from drone imagery or photogrammetry.

• Composed of triangles that form detailed surfaces of landscapes or buildings.

• Useful for visualizing real-world environments as consolidated 3D scenes.

Mesh features consist of triangles arranged in different ways to form three-dimensional shapes. The triangular structure of mesh features is generally not visible in ArcGIS Pro. Source: Esri

Point Clouds

• Comprised of millions of 3D points (x, y, z), often collected using LiDAR.

• Stored in formats like .LAS or compressed .LAZ.

• Commonly used for terrain analysis, tree canopy modeling, and infrastructure inspection.

  
  

  

  Lidar sensors send out laser beams aimed at a target. The laser light that bounces back from the target, known as a return, is captured and evaluated by the receivers within the lidar sensor. Source: Esri

  
  

  

  Point Cloud

  
  

Multipatch Features

• Represent the exterior surfaces of 3D objects (e.g., buildings).

• Can include texture and color information.

• Cannot be viewed properly in 2D maps.

• Allow for storing display properties within the feature itself.

  
  

  

  
  

2D Features with 3D Properties

• Points, lines, and polygons may include height values (z-values) or vertical attributes.

• Can be extruded in 3D scenes to represent objects like poles, building footprints, or zoning volumes.

• Work well in both 2D and 3D environments, depending on context.

In the accompanying video, I demonstrate how each of these data types appears in ArcGIS Pro—Esri’s powerful desktop GIS application. From point clouds to integrated meshes, the video provides a visual walkthrough of how spatial data becomes more meaningful when viewed in three dimensions.

Final Thoughts

As industries continue to evolve toward smarter, more data-driven systems, the ability to work with 3D data is becoming a core skill for GIS professionals, designers, and planners alike. Understanding the building blocks—like photogrammetry and 3D data types—is the first step toward creating digital twins and spatial tools that reflect the real world with clarity and precision.