Drone mapping turns planned aerial data collection into measurements, maps, models, and other geospatial products. This section covers mission design, image overlap, positioning, ground control, photogrammetry, LiDAR, point clouds, orthomosaics, elevation models, processing, and accuracy, with an emphasis on how capture decisions affect the final result.
Topic
Drone Mapping: Photogrammetry, LiDAR and Geospatial Workflows
Latest topic news
PX4 precision-landing proposal updates coordinates when EKF origin changes
PX4 PR 29711 describes a precision-landing target mapped from local NED coordinates to latitude and longitude that can become stale when EKF2 resets its navigation origin during GNSS-denied operations. The patch proposes refreshing that mapping.
Read newsPeer-reviewed ESCAPE swarm exploration revisited in new forest-flight reporting
New reporting on 8 November revisits the ESCAPE research from Tongji and partner universities, originally published in December 2025. Its authors tested three LiDAR quadcopters outdoors and four indoors with distributed task allocation; simulations compared the method against Racer and Role.
Read newsArduPilot proposes I2C support for the Pono TSD20 rangefinder
ArduPilot PR 35065 adds a proposed driver for the Pono TSD20 single-point LiDAR in I2C mode, with corresponding SITL simulator and autotest coverage; the proposal identifies rangefinder type 49.
Read newsStudy compares UAV photogrammetry and terrestrial scanning at an open-pit mine
A Measurement journal pre-proof available online on 3 November compares UAV-derived surface models with terrestrial laser scans at an active mine. The authors report a 0.50 m UAV DEM grid and volume-change deviations of 7.42% for a dump and 7.85% for a pit in the studied areas.
Read newsA 360-degree camera offers archaeological surveying when drone flight is restricted
A peer-reviewed paper published on 3 November describes a low-cost ground-based survey method using a spherical camera and ground control points at archaeological sites where drone photography is unavailable or restricted. The authors report photogrammetric results and comparisons with conventional survey sampling and drone-derived imagery.
Read newsTopic articles
A portable drone mapping mission needs more than portable waypoints
A survey can be flown by two aircraft along nearly identical tracks and still produce two datasets with different coverage, blur, coordinate quality and processing success. Copying the waypoint coordinates preserves only part of the plan. The photographs depend on a camera model, its shutter behavior, the aircraft's actual speed and height above the surface, and the way each flight stack interprets the mission.
Read articleWhy forest-canopy drone missions need a surface model, not just GPS waypoints
A waypoint list can tell a drone where to fly. It cannot, by itself, tell the aircraft where a tree crown begins, whether the approach crosses another crown, or how far above the foliage the camera will be when it takes a photograph. For repeatable close-up forest surveys, those are separate geometry problems.
Read articleAn RTK fix is not an accuracy certificate for a drone map
A drone can report an RTK-fixed position for every photograph and still produce an elevation model that fails an independent survey check. The position solution constrains where the camera was, within the uncertainty of the observation and its timing. Photogrammetry must also infer lens geometry, camera orientation and the position of each reconstructed surface point. Those are different estimation problems.
Read articleA mission can have more MAVLink commands than QGroundControl shows as waypoints
A survey mission may show six points on a map while the flight controller holds many more commands. Camera triggers, speed changes and landing-pattern instructions can sit between the navigation points. For operators this is usually a convenience: the ground station combines related actions into one editable visual item. For software deciding whether a mission can be continued, however, the distinction can become a correctness problem.
Read articleForest LiDAR needs a different flight plan for trunk diameter than for tree height
A canopy-height map can look consistent while the same drone survey fails to measure the trunks underneath. The two outputs depend on different parts of a laser point cloud. Tree height mainly needs the canopy surface and a credible ground reference. Diameter at breast height (DBH) needs enough correctly located returns from a narrow, often occluded section of each stem. Improving one does not automatically improve the other.
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