TEC-GIS45-06 · Lesson 7 · 14 clock hours · lab
Dense Point Cloud, DSM, and Orthomosaic Generation
Objective. Students process a complete UAS image set through dense-matching, surface model building, and orthomosaic export stages, producing deliverables that meet a specified GSD and vertical accuracy target.
⚠ Pending professional review
This lesson, its worked examples and its practice questions has not yet been verified by an industry-certified professional or by a certification or approval body. It is a study draft and may contain errors. Do not use it as instructions for work on a job site or on live equipment. Always follow your instructor, your supervising professional, and current official references and regulations.
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Dense Point Cloud, DSM, and Orthomosaic Generation
Why This Workflow Matters
After your UAS imagery is aligned and your Ground Control Points (GCPs) are imported, you have a sparse point cloud and camera positions—but no deliverable products yet. The three stages covered in this lab—dense matching, surface model building, and orthomosaic export—transform raw alignment data into the georeferenced files that engineers, surveyors, and planners actually use. Each stage builds on the one before it, so errors introduced early propagate forward. Working carefully and logging every setting is not busywork; it is how you prove your results are reliable.
Stage 1: Build Dense Cloud
Dense image matching compares overlapping pixels across many photos and reconstructs a dense three-dimensional point cloud—sometimes tens of millions of points for a modest survey area. In Agisoft Metashape the key parameter is Quality: Ultra High, High, Medium, Low, or Lowest. Higher quality uses full-resolution images and produces finer detail but demands far more RAM and processing time. For most survey-grade work, High is appropriate; Medium is acceptable for preliminary products or when computing resources are limited.
The Depth filtering setting controls how aggressively Metashape removes points that are statistically inconsistent with their neighbors. Mild filtering retains more points but may keep noise; Aggressive filtering is cleaner but can remove legitimate breakpoints on edges and roofs. For topographic surveys, Mild or Moderate filtering is typical.
Record your chosen quality and filtering mode in your processing log along with the elapsed time. Processing time varies widely with hardware—a dataset of 200 images at High quality might take 30 minutes on a workstation with a capable GPU or several hours without one.
Stage 2: Build DEM (Digital Elevation Model)
From the dense cloud, Metashape interpolates a raster elevation surface called a Digital Surface Model (DSM) when it includes vegetation and structures, or a Digital Terrain Model (DTM) when ground-level filtering has been applied. In Metashape the menu item is Build DEM; choose the dense cloud as the source.
Set the coordinate system to match your GCPs (typically a projected system such as a State Plane zone in US Survey Feet or meters, combined with a vertical datum). Set the resolution to at or better than your target Ground Sample Distance (GSD). If your flight was designed for a 3 cm GSD, exporting the DEM at 5 cm is acceptable; exporting at 1 m throws away information. Record the output resolution in your log.
Stage 3: Build Orthomosaic
An orthomosaic is a geometrically corrected, mosaicked image in which displacement caused by terrain relief and camera tilt has been removed using the DEM. Every pixel in a true orthomosaic maps to a consistent ground location at a known scale, making measurement possible directly on the image.
In Metashape, Build Orthomosaic uses the DEM you just produced. Select the same coordinate system and a pixel size at or near your design GSD. The blending mode (Mosaic is the default) controls how overlapping image regions are merged; Mosaic prioritizes nadir-facing pixels and generally produces the cleanest result for mapping.
GCP Import and Optimization
Before building dense products, you must import your GCP coordinates, mark targets on the photos, and run Optimize Cameras. Import the GCP coordinate file (CSV or text) using the Reference panel. For each GCP, Metashape prompts you to click the target center in multiple images—aim for at least three images per GCP; more is better. After marking, run Optimize Cameras.
Metashape reports two key accuracy indicators:
- Reprojection error (pixels): the average distance between where the software predicts a tie point or GCP should appear in each image and where it was actually marked. A value below one pixel is generally acceptable; significantly higher values suggest poor target marking or camera calibration issues.
- GCP residuals (ground units): the difference between your imported GCP coordinates and the model's computed positions. These residuals must fall within the accuracy tier you are claiming for your deliverable.
Document pre-optimization and post-optimization values in your processing log. If residuals remain large after optimization, re-examine your target markings before proceeding.
Export and File Management
Export three files:
1. Orthomosaic — GeoTIFF, full resolution, coordinate system matching GCPs.
2. DEM — GeoTIFF, matching resolution and coordinate system.
3. Processing report — PDF generated by Metashape (Export → Generate Report), which records camera positions, GCP residuals, overlap statistics, and software settings.
Follow the naming convention supplied by your instructor (typically: ProjectName_Date_ProductType, for example `SurveyA_20250610_Ortho.tif`). Store all files in the provided project folder structure and back up immediately to the external hard drive before closing Metashape.
Open both GeoTIFFs in ArcGIS Pro and compare them to a basemap. Roads, building corners, and other identifiable features should align visually. Significant offset indicates a coordinate system mismatch or a GCP import error—do not submit until alignment is confirmed.
Workstation Safety and Data Hygiene
Processing large datasets stresses hardware. Do not block workstation vents, and do not run other intensive applications simultaneously. Save your Metashape project frequently—dense cloud generation is not automatically saved and a crash means restarting that stage. Treat all source imagery as irreplaceable: never edit original files; always work from copies in your project folder. Back up before and after each major processing stage.
Key terms9
Dense point cloudA three-dimensional set of millions of points reconstructed by comparing overlapping pixels across many photographs; the primary geometric output of dense image matching.
Digital Surface Model (DSM)A raster elevation surface derived from the dense point cloud that includes the tops of all objects—buildings, trees, and terrain—rather than bare ground only.
OrthomosaicA mosaicked aerial image that has been geometrically corrected for terrain relief and camera tilt using a DEM, so that every pixel is at a consistent map scale and location.
Ground Sample Distance (GSD)The distance on the ground represented by one pixel in an image or raster product; a smaller GSD means finer spatial detail.
Reprojection errorThe average pixel distance between the software-predicted and user-marked position of a tie point or GCP across all images in which it appears; an indicator of alignment quality.
GCP residualThe difference between the known surveyed coordinates of a Ground Control Point and the coordinates computed for that point by the photogrammetric model after optimization.
Depth filteringA Metashape setting that controls how aggressively statistically inconsistent points are removed from the dense cloud; modes range from Mild to Aggressive.
Camera optimizationA Metashape process that refines camera interior and exterior parameters—including lens distortion coefficients—using GCP and tie-point data to reduce systematic errors in the model.
Processing reportA PDF document automatically generated by Metashape that records processing settings, GCP residuals, camera positions, overlap statistics, and software version for quality assurance purposes.
Worked examples4
1. Your design GSD is 3 cm. When you export the DEM, Metashape offers a default resolution of 0.0312 m (3.12 cm). Is this acceptable, and what pixel size in centimeters does it represent?
- Convert the offered resolution to centimeters: 0.0312 m × 100 cm/m = 3.12 cm per pixel.
- Compare to the design GSD: the design target is 3 cm; the offered resolution is 3.12 cm, which is very close to and only slightly coarser than the design GSD.
- Assess acceptability: a resolution slightly coarser than the design GSD is acceptable—you are not discarding significant information. A resolution several times coarser (e.g., 10 cm when GSD is 3 cm) would be wasteful of collected data.
Answer: 3.12 cm per pixel; the export resolution is acceptable because it is within approximately 4% of the design GSD.
2. After GCP optimization, Metashape reports GCP residuals of X = 0.024 m, Y = 0.031 m, Z = 0.048 m. Your project specification requires horizontal accuracy of 5 cm (0.05 m) and vertical accuracy of 10 cm (0.10 m). Do the residuals meet spec?
- Calculate the horizontal residual magnitude using the Pythagorean theorem: horizontal = √(X² + Y²) = √(0.024² + 0.031²) = √(0.000576 + 0.000961) = √0.001537 ≈ 0.0392 m (3.92 cm).
- Compare horizontal residual to specification: 3.92 cm < 5.00 cm — horizontal passes.
- Compare vertical residual to specification: 0.048 m (4.8 cm) < 0.10 m (10 cm) — vertical passes.
- Overall conclusion: both horizontal and vertical residuals are within specification.
Answer: Horizontal residual ≈ 3.92 cm (within 5 cm spec); vertical residual = 4.8 cm (within 10 cm spec). The model meets the stated accuracy requirements.
3. Your UAS image set contains 180 images. During Build Dense Cloud at Medium quality, your workstation processes at roughly 6 images per minute. Estimate how long the dense cloud will take to complete.
- Identify total images: 180.
- Identify processing rate: 6 images per minute.
- Divide total images by rate: 180 ÷ 6 = 30 minutes.
- Note that this is an estimate; actual processing time depends on hardware, image resolution, overlap, and scene complexity.
Answer: Approximately 30 minutes at Medium quality with that processing rate.
4. Your orthomosaic file exported from Metashape is 4,200 pixels wide. The GSD is 4 cm (0.04 m). What is the east–west extent of the mapped area in meters?
- Identify pixel width: 4,200 pixels.
- Identify GSD: 0.04 m per pixel.
- Multiply pixel count by GSD: 4,200 × 0.04 m = 168 m.
Answer: The east–west extent of the mapped area is 168 meters.
The math in this lesson1
Learners convert a 0.0312 m output resolution to 3.12 cm and compare it to the 3 cm design GSD.
N-Q.1
In class: Processing lab: using imagery collected during Lesson 5, students complete the full Metashape workflow—Build Dense Cloud (medium or high quality), Build DEM, Build Orthomosaic—documenting each setting in a processing log and noting estimated processing time. · GCP import and optimization: students import the measured GCP coordinates from Lesson 4 into Metashape, mark targets on images, run optimization, and record pre- and post-optimization reprojection errors and GCP residuals in the processing log. · Export and file management: students export the orthomosaic (GeoTIFF), DEM (GeoTIFF), and processing report (PDF) to a structured project folder following a naming convention provided by the instructor, then verify georeferencing by opening files in ArcGIS Pro and comparing to a basemap.
Materials: Workstations with Metashape and ArcGIS Pro, UAS imagery from Lesson 5, GCP coordinate file from Lesson 4, project folder template, processing log form, external hard drive for backup
Check: Instructor reviews processing log, exported files, and ArcGIS Pro screenshot showing alignment to basemap; GCP residuals must be within the accuracy tier claimed; all three deliverable files must open and display correctly; pass = log complete, residuals within spec, files verified.
Practice check8
Answer each question, then check it. Nothing is recorded; this is your own practice.
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