POSSIBILITIES FOR USING LIDAR AND PHOTOGRAMMETRIC DATA OBTAINED WITH AN UNMANNED AERIAL VEHICLE FOR LEVEE MONITORING

• Main Authors: K. Bakuła, W. Ostrowski, M. Szender, W. Plutecki, A. Salach, K. Górski
• Format: Article
• Language: English
• Published: Copernicus Publications 2016-06-01
• Series: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
• Online Access: https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B1/773/2016/isprs-archives-XLI-B1-773-2016.pdf

This paper presents the possibilities for using an unmanned aerial system for evaluation of the condition of levees. The unmanned aerial system is equipped with two types of sensor. One is an ultra-light laser scanner, integrated with a GNSS receiver and an INS system; the other sensor is a digital camera that acquires data with stereoscopic coverage. Sensors have been mounted on the multirotor, unmanned platform the Hawk Moth, constructed by MSP company. LiDAR data and images of levees the length of several hundred metres were acquired during testing of the platform. Flights were performed in several variants. Control points measured with the use of the GNSS technique were considered as reference data. The obtained results are presented in this paper; the methodology of processing the acquired LiDAR data, which increase in accuracy when low accuracy of the navigation systems occurs as a result of systematic errors, is also discussed. The Iterative Closest Point (ICP) algorithm, as well as measurements of control points, were used to georeference the LiDAR data. Final accuracy in the order of centimetres was obtained for generation of the digital terrain model. The final products of the proposed UAV data processing are digital elevation models, an orthophotomap and colour point clouds. The authors conclude that such a platform offers wide possibilities for low-budget flights to deliver the data, which may compete with typical direct surveying measurements performed during monitoring of such objects. However, the biggest advantage is the density and continuity of data, which allows for detection of changes in objects being monitored.