LidarBoX: a 3D-printed, open-source altimeter system to improve photogrammetric accuracy for off-the-shelf drones

Drones, or unoccupied aircraft systems (UAS), have become increasingly accessible and a widely used tool across disciplines. Off-the-shelf drones have, for instance, popularized and advanced wildlife research by providing a privileged birds’-eye view for collecting high-resolution imagery for morphometric and behavioral sampling, which was otherwise costly or impractical. Biologically meaningful measurements extracted from such overhead images require an accurate and precise estimate of the altitude, but current commercial drones rely on inaccurate and imprecise barometer estimates. Recent proposals for coupling altimeter systems to drones have provided customized, open-source solutions; yet assembling such altimeter systems requires advanced technical skills, thereby potentially restricting its use to specialists. Here, we built upon these recent advances to provide a template for a 3D printed enclosure for an altimeter system that is inexpensive, self-contained, easy to set-up, and transferable across commercial drone models. We depart from a published, successful data logger system composed of a GPS and LiDAR sensor, and design a more compact and self-powered version of this system (“LidarBoX”) that can be easily attached to a variety of commercial drones. We tested the updated system by comparing flight times with and without LidarBoX attached, validating the improvement in measurement accuracy of using the LiDAR sensor over the barometer for recording altitude, and demonstrated its utility in sampling morphometric data from free-ranging marine megafauna. To make this altimeter system more accessible, we also provide a full list of components, an open-source repository with design code and files, as well as a how-to assembly guide for non-specialists. We hope this work helps to popularize the use of precise altimeter systems on commercial drones to help further improve the accuracy and reliability of drones as a sampling platform for ecology and wildlife research.