The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 37–44, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-37-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 37–44, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-37-2022
 
30 May 2022
30 May 2022

INITIAL STUDY ASSESSING THE SUITABILITY OF DRONES WITH LOW-COST GNSS AND IMU FOR MAPPING OVER FEATURELESS TERRAIN USING DIRECT GEOREFERENCING

B. Essel, J. McDonald, M. Bolger, and C. Cahalane B. Essel et al.
  • Maynooth University, Department of Geography, Maynooth, Co. Kildare, Ireland

Keywords: Direct Georeferencing, Drone, Water, Inertial Measurement Unit, Featureless terrain

Abstract. Drone technology has shown the potential to act as the middle ground between satellite, light aircraft, and terrestrial or in-situ methods. However, featureless terrain such as water poses a challenge when it comes to drone mapping. The main challenge is identifying matching points to combine overlapping images into a single dataset. In particular, because traditional methods such as Structure from Motion (SfM) is dependent on tie point collection, its usage over featureless terrain is almost impossible. In solving this problem, we propose that the use of Direct Georeferencing (DG) in registering images be explored as a potential method and we propose a method for correcting errors due to tilt with low-cost IMUs. This study first assesses the accuracy of direct georeferencing using low-cost Inertial Measurement Units (IMU) and Global Navigational Satellite System (GNSS) providing analysis of the error sources associated with direct georeferencing and then demonstrates new approaches to minimize them. To best simulate a water type environment or surface for the initial studies, a drone survey was conducted on flat farmland and a POSE analysis was performed. We then processed the images using direct georeferencing and then compared our error minimisation method to standard Bundle Block Adjustment with GCPs and again with no GCPs. Results showed that using the method proposed in this study helped reduce the Mean Absolute Error associated with direct georeferencing by 54%. These initial results show a clear potential for mapping over inland water using direct georeferencing.