Developing an Autonomous Unmanned Aerial System to Estimate Field Terrain Corrections for Gravity Measurements

We have developed a method employing an autonomous Unmanned Aerial System (UAS) to provide a more robust measure of the Field Terrain Correction (FTC) for gravity measurements than is offered by traditional methods. The resolution of digital terrain that is typically available for much of the United States (10 or 30m) is too low to adequately estimate the FTC in steep terrain. Most often, the FTC, which corresponds to the innermost zone around the gravity station (e.g., extending to 68m radius for the Hayford-Bowie zones A&B), is estimated in the field with the aid of templates and charts that attempt to approximate sectors of the terrain as uniform slopes. The aforementioned techniques can result in significant error if they are not performed by experienced practitioners, particularly when the terrain is complex. In our approach, we dispatch a UAS to collect images around the gravity station, which we use to construct a Digital Elevation Model (DEM) of the area with the Structure from Motion (SfM) method. The resulting DEMs allow us to precisely calculate the FTC. We have developed software to automate most of the procedure including the autonomous flight and image capturing by the UAS. As part of our initial testing, we have experimented with a variety of flight paths, at several sites spanning a range of terrain conditions, to determine the most efficient flight characteristics for this application. Selecting field sites where existing LiDAR data were available, has enabled us to characterize errors in the DEMs derived from SfM and to assess the tradeoffs between flight time, processing time, and accuracy of the resulting FTCs. Our methodology is fast (flight time: 3-4 minutes, depending on weather conditions) and robust primarily because the UAS flight is automated. It can be used to calculate the FTC of a variety of terrain conditions and delivers results that are much more precise than existing methods that do not make use of high-resolution digital terrain data.