LiDAR capture

Drone LiDAR measures surface elevations that can be used to calculate stockpile volume above an agreed base surface. Comparing existing and proposed surfaces can also support cut-and-fill estimates. The calculation requires defined boundaries, compatible units, and a suitable reference surface. Results describe volume, not weight; estimating tonnage additionally requires appropriate material-density information.

LiDAR stockpile volume accuracy depends on the measured surface, point classification, pile boundaries, and the assumed base beneath the material. Vegetation, obstructed edges, or an uncertain base can change the estimate. Centimeter-level point-position accuracy does not automatically translate into a fixed percentage of volume accuracy. The checking method and acceptable uncertainty should be agreed upon for the project.

Yes. Drone LiDAR can support tree-height estimates and canopy height models by comparing vegetation elevations with a ground model. The result describes height above local ground, not elevation above sea level. Reliability depends on treetop and ground coverage, vegetation conditions, point density, and classification. Individual tree measurements and broader canopy mapping require different collection and analysis choices.

DJI specifies Zenmuse L3 point-cloud accuracy of 3 cm vertical RMSE and 4 cm horizontal RMSE at a 120 m flight altitude under defined laboratory conditions. Its tests used a position-calibrated D-RTK 3 station, specified flight and calibration settings, exposed hard-surface checkpoints, and DJI Terra processing settings. RMSE is a statistical error measure, not a maximum error for every point. These specifications are not a guarantee for each site; project accuracy requires appropriate independent checks.

LiDAR mapping deliverables can include point clouds, digital elevation models, contours, canopy height models, three-dimensional models, and material-volume calculations, depending on the agreed scope. The right combination depends on your project goals. Before collection, we confirm the outputs, file formats, coordinate references, units, and accuracy requirements relevant to their intended use.

Yes. Comparing LiDAR surfaces from different dates can help quantify terrain changes or changes in stockpile volumes. Reliable comparisons require compatible coordinate systems and vertical references, consistent boundaries, and suitable surface quality. Changes must be evaluated against the uncertainty of both datasets; small differences may reflect measurement uncertainty rather than actual site changes.