9.4 Aerial-Ground Fusion Processing
Planning the takeoff and landing points, capturing the ground scan, flying the drone mission, and shooting the vertical bridge photos that lock the two together. The whole job is decided by how you capture the bridge in the field.
What This Mode Produces
Aerial-Ground Map Fusion merges a ground scan with drone aerial imagery into one model that covers interior and ground-level geometry, the roof, and the surrounding site. The ground scan supplies precise interior detail. The drone supplies the roof and the areas no handheld scanner can reach. Use it for campus facilities, construction sites, and heritage or landmark documentation where roof and aerial context are required. Skip it for interior-only work, at any scale.
Every aerial-ground job needs three things captured in the field: the ground scan, the drone mission photos, and the vertical bridge photos at each takeoff and landing point. This is the same for every scanner, whether L2 Pro, K2, or PortalCam. The bridge photos are what tie the aerial data to the ground data, and they cannot be added later. If any of the three is missing, reconstruction either fails or produces a broken model.
Plan the Site and the Flight
The ground scan and the drone flight are joined by shared points on the ground called aerial-ground fusion points. Placing them well is the entire job. Plan them before anyone powers on a device.
- Survey the site first. Use satellite imagery or an aerial photo to lay out the site before you arrive.
- Choose the fusion points: at least 4, covering 8 approach directions. Pick open, unobstructed areas spread evenly across the site to serve as the drone's takeoff and landing points. These same spots become the fusion points that tie air to ground. On most mid-size jobs, 4 to 5 points is right. Keep adjacent points no more than about 165 ft apart, and on dense sites plan roughly one point per quarter acre. Points clustered at one end of a large site do not constrain the far end, and the model will drift there.
- Pick feature-rich spots, not blank pavement. The fusion matches geometry visible in both datasets. A paved area with planters, signage, bollards, or building corners gives it far more to lock onto than an empty square.
- Confirm each point is visible from both air and ground. The drone and the scanner must both be able to see the same fixed targets, roughly 65 to 130 ft from the point, since that shared view is what the bridge photos will capture.
- Keep the point areas unchanged between visits. If the scan and the flight happen on different days, parked vehicles or staged materials that move between them degrade the fusion at that point.
Capture the Ground Scan
Scan the site as usual, with two additions that create the fusion points.
- Mark a fusion point at each takeoff and landing location. At each chosen spot, mark an aerial-ground fusion point and circle it once so the scanner captures a complete cloud around it. LCC Studio identifies these points automatically during processing, so they do not need names.
- Route the scan path through every fusion point. Plan the walking path so it passes through each point, and close two loops within 6.5 to 10 ft of each point. The double loop closure at the point is what gives the fusion a reliable tie.
- Cover the rest of the site normally, and watch the live cloud. Follow standard scan technique for the interior and ground-level exterior between the fusion points. Monitor the real-time point cloud as you go: drift, misalignment, layering, or large-scale noise in the live view means that stretch needs a rescan before you leave the site.
Ground data is raw scan segments only, and Aerial-Ground Fusion is not Map Fusion. The output of a completed Map Fusion project cannot be used as ground data, and Map Fusion cannot be combined with an aerial-ground job in any direction. A single project accepts up to 10 raw ground segments under a 200-minute total, the same segment ceiling as Map Fusion. Plan each segment at 20 to 30 minutes, sized to the workstation that will process the job (Section 7), split per standard scan-splitting practice, and hold RTK Fixed in every segment.
Fly the Drone Mission
The mission is the overhead mapping flight. The goal is complete, high-overlap coverage of every surface you want in the model.
| Setting | Value |
|---|---|
| Coordinate system | WGS84, matched on the controller and the scanner |
| Flight pattern | Smart grid, framed to the survey area on the controller map, extended 6.5 to 10 ft beyond the target area |
| Capture mode | Oblique |
| GSD (ground sample distance) | 1 cm or smaller |
| Gimbal angle | 45 degrees; steeper for taller buildings needing more facade detail |
| Flight height | Above the tallest building in the survey area |
| Side and forward overlap | 85% each |
| Camera | Mapping-grade wide-angle lens, distortion correction disabled, one focal length for the entire image set |
| RTK | Fixed solution maintained for the whole capture. A drone without RTK can be used on one specific path only, described in Section 6 |
The core principle is overlap: every ground object of interest needs more than 85% overlap across the image set. Higher overlap produces a more complete reconstruction. For large areas with complex structures, add 1 to 2 passes at higher altitudes; the height difference between adjacent passes must not exceed twice the lower altitude.
Hold the 1 cm GSD. XGRIDS' own comparisons show the difference plainly: a 0.4 cm GSD flight resolves individual bolts and cabling, 1.3 cm still reads as clean geometry, and 2 cm collapses fine structure into mush. A coarser GSD makes the flight faster and the model worse; the flight time saved is never worth the reshoot.
Capture the Vertical Bridge Photos
The vertical bridge is the step that decides whether the ground scan and the drone mission actually merge. The mission photographs the site from above; the ground scan captures it from eye level; on their own, the software has no way to connect the two. The bridge fills that gap. At each marked point, the drone climbs a vertical column, photographing the same scene continuously from just above the ground all the way past the mission's flight height. That unbroken run of images is what lets the fusion lock the two datasets together.
One bridge column, seen from the side. Every photo in the climb aims at the same fixed target. Repeat the climb from 3 directions at every marked point.
Capture a bridge column at every marked takeoff and landing point:
- Start low, just above the ground. Position the drone over the marked spot 1.5 to 3 ft off the ground, and aim the camera at a fixed target 65 to 130 ft away that is visible to both the drone and the scanner, in a texture-rich direction. Every photo in the set aims at that same target.
- Climb straight up past flight height, shooting as you go. Enable timed capture at 0.5-second intervals and rise slowly and steadily from just above the ground to above the mission's flight altitude, collecting 30 to 40 photos across the full climb and holding at least 85% overlap between one shot and the next. The lowest photo sits within 3 ft of the ground; the highest sits above the mission flight height. Control the climb speed by hand so the interval shots keep their overlap.
- Fly the column from 3 directions. Repeat the climb aimed from the left, the center, and the right of the target, so each of the 3 directions is its own 30-to-40-photo set at 85% overlap. On drones with Point of Interest and Orbit functions, set the target as the POI and let Orbit hold the aim while you manage the climb.
Details that matter on the bridge:
- How high to rise between shots. Space the 30 to 40 photos evenly across the climb so consecutive shots overlap by at least 85%. On a tall column this is a small step: for a climb to 250 ft, a photo roughly every 6 to 8 ft; on a lower flight the step is shorter.
- How many photos per point. About 30 to 40 per direction, across 3 directions, so roughly 90 to 120 photos at each takeoff and landing point. Budget the flight time and the battery for that.
- The descent counts too. Photos taken during a continuous ascent or a continuous descent are all valid, so a climb-and-descend pass at one point can cover two directions.
- Same camera rules as the mission. Wide-angle mode, distortion correction disabled, RTK Fixed held for every shot, and no blurred, overexposed, or underexposed frames. Photos without a Fixed RTK record are thrown out in processing.
- Do not mark or name control points for the bridge photos. These are imagery, not survey points. You do not add a control point or a name for them. Just fly the column and shoot.
- Keep the bridge photos with the mission photos on L series and K2. On those scanners, every bridge photo goes into the same folder as the drone mission photos; there is no separate upload for them. On PortalCam, the takeoff and landing photo sets are uploaded as their own per-point folders alongside the aerial photos, so keep each point's set in its own folder from the start. See Section 7.
Aerial Data Requirements
Before processing begins, LCC Studio rejects an aerial image set that does not meet these. On L series and K2 jobs the set is the mission photos and the bridge photos together, in one folder. On PortalCam jobs the takeoff and landing photo folders are uploaded per fusion point alongside the aerial photos; the counts and formats below apply to the full combined set.
| Requirement | Specification |
|---|---|
| Image count | 100 to 10,000 images per project, mission and bridge photos combined. |
| File format | JPG or JPEG only. PNG and RAW are not supported. |
| Resolution | Greater than 1024 x 768 pixels, consistent across every image in the set. |
| Focal length | One focal length across the entire set. Mixed focal lengths from a multifocal camera cause reconstruction errors. |
| RTK | On the RTK path, which is the default: a valid Fixed record on every photo. The RTK status field in the photo metadata must read 50, and photos with any other value are excluded from processing. There is one supported path for a drone without RTK, described immediately below. |
| Lens and correction | Mapping-grade wide-angle lens with the camera's distortion correction disabled. |
Pairing the drone RTK with the ground scan
The bridge photos tie the two datasets together visually. Positioning ties them together in space, and how you supply that positioning depends on the ground device. A switch in the reconstruction parameters, on by default, controls whether the drone's own RTK data is used at all. Turning it off makes the system ignore the drone's RTK completely.
Match the pairing to the equipment you actually have before the flight, because the wrong pairing is not something processing can repair.
| Ground data | Drone data | Result |
|---|---|---|
| L2 Pro with RTK | Drone with RTK | Recommended. The highest-accuracy pairing. Leave the drone RTK setting on. |
| PortalCam with aerial-ground fusion control points | Drone with RTK | Recommended. Leave the drone RTK setting on. |
| PortalCam with aerial-ground fusion control points | Drone without RTK | Recommended. Turn the drone RTK setting off. This is the path that allows a consumer drone. |
| L2 Pro with RTK | Drone without RTK | Avoid. Reconstruction may fail, or the model may separate into layers. |
An RTK ground scan does not rescue a non-RTK drone. Pairing an L2 Pro RTK scan with a drone that has no RTK is the one combination XGRIDS advises against. It often shows up as layer separation rather than an outright error, which means it can survive a quick review and reach the client before anyone notices. If the drone has no RTK, the supported route is PortalCam ground data with its fusion control points, not an L2 Pro scan with better positioning.
This does not replace the bridge photos. Every pairing above still needs the vertical bridge columns flown at each marked point, on every scanner. RTK handles where the data sits in space; the bridge handles how the aerial and ground views connect visually. A job that gets the RTK pairing right and skips the bridge still fails.
No bridge photos means no reliable fusion. If the vertical bridge columns were not flown and only mission photos are uploaded, the result is degraded or the reconstruction fails outright. Bridge photos cannot be added after the flight. Plan and capture them at every marked point during the shoot.
Before committing a multi-hour run, run the XGRIDS quality inspection tool against the assembled data. It verifies RTK status, coordinate systems, point distribution, photo counts, and capture duration in minutes, not hours. The full tool workflow and the nine checks it supports are documented in 6.4 Aerial-Ground Fusion.
Run the Fusion
Processing takes two inputs: the scanner project file (or raw segments), and the drone photos.
- Organize the inputs first. Keep the scanner data in one place. On L series and K2 jobs, put every drone photo, mission and bridge, into a single image folder; do not sort the bridge photos into separate subfolders. On PortalCam jobs, keep the aerial photos in their folder and each fusion point's takeoff and landing photos in their own per-point folders; uploading only the aerial photos without the marked fusion points and their photo folders degrades the fusion or fails the reconstruction.
- Create the project. Click Create and select Aerial-Ground Map Fusion. This mode is distinct from Map Fusion and Single Model and cannot be switched later without reprocessing.
- Add the ground data. Under Ground Data, add the raw scanner data: up to 10 raw segments, planned at 20 to 30 minutes each, under a 200-minute total. Map Fusion output is not accepted. LCC reads the fusion point markers from the scan and identifies them automatically. The interface shows the device type it detects.
- Add the aerial data. Under Aerial Data, select the drone photos: on L series and K2, the single folder holding the full set; on PortalCam, the aerial photos plus the takeoff and landing photo folders for the corresponding fusion points.
- Set parameters and start. Quality Standard for a first run. Maximum Gaussian Points applies per block in this mode and the system auto-adjusts it. Set the drone RTK option to match what the drone actually recorded, per the pairing table in Section 6: on when the flight carried RTK, off on the PortalCam and non-RTK-drone path. Start the reconstruction.
Check the fusion at the ground-to-air transition
When processing finishes, open the model and check the one place a bad fusion shows up: where the ground data meets the aerial data. Find a wall or a tall feature that both the scanner and the drone captured, then follow it from the ground, which came from the scanner, up to the roofline, which came from the drone. It should read as one continuous surface.
A bad fusion at that spot looks like a horizontal step, a sideways offset, a doubled or ghosted wall, or a visible break at the height where the two datasets meet. Any of those means the bridge column at that point did not give the fusion enough overlap between ground and air. That point needs its bridge re-flown; the break cannot be fixed in post.
Processing requirements
| Component | Specification |
|---|---|
| CPU | AMD Ryzen 9 9950X or an equivalent 16-core or higher desktop CPU. |
| Memory | 64 GB (2 x 32 GB) minimum. For large datasets, roughly 150 minutes of capture or more at high quality, 128 GB (2 x 64 GB). |
| GPU | NVIDIA RTX 3090 minimum; RTX 4090 or 4090D for best performance. |
| Processing time | At Standard quality on the recommended hardware, about 20 to 30 minutes of processing per minute of ground capture, plus added time for the drone and bridge imagery. A 60-minute ground capture is therefore on the order of 20 to 30 hours before the aerial processing. Slow quality and very large image sets extend it. |
Memory sets how much capture one job can hold; plan segments at 20 to 30 minutes. Per the official configuration reference, 64 GB stably processes up to 30 minutes of capture data, with failure risk rising past 45 minutes; 128 GB stably processes up to 60 minutes, with risk rising past 90. That is why the field rule is 20-to-30-minute scan segments, sized to the workstation, under the project ceiling of 10 segments and a 200-minute total (the Map Fusion segment ceiling). After importing data, watch the estimated memory bar: red means capacity is exceeded and the reconstruction is likely to fail. Plan the capture around the machine, or the machine around the capture, before anyone drives to the site.
The big published capacity numbers are server figures, not workstation figures. XGRIDS' 500-minute, 10,000-photo class of aerial-ground job runs on the LCC Studio Linux Server version with multi-GPU parallel processing, which is a private-deployment product; the Windows version does not support multi-GPU. A Windows workstation job is bounded by the memory figures above and the 10-segment, 200-minute ground ceiling. Do not quote server-class capacity to a client for a workstation pipeline.
This mode has the highest hardware demand in LCC Studio. Running it below the minimum produces either a processing failure or an unusable result. Confirm the workstation meets the spec before committing a multi-hour run, and if memory is short, drop to Standard quality rather than pushing a job the machine cannot hold.
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