UAV photogrammetry for red tide monitoring and geo-localization via onboard GNSS/IMU data

Abstract

As one of the worst ecological disasters in the world’s oceans, red tide seriously threatens marine ecology. Red tide monitoring is essential for preserving the ocean ecosystem. However, traditional photogrammetric processing workflows, e.g. SfM (Structure from Motion) and MVS (Multi-view Stereo) based image orientation and dense matching, do not apply to offshore images due to the low texture of ocean color. The primary contribution of this study is a UAV (Unmanned Aerial Vehicle)-based photogrammetric solution for red tide monitoring and direct geo-localization. First, a direct geo-localization model has been created, which solely uses onboard sensor data for the 3D coordinate calculation of 2D image targets based on the collinear equation. Second, two UAVs are chosen as photogrammetric systems that can supply the necessary data for the direct geo-localization model, including high-resolution images, camera intrinsic and extrinsic parameters. Third, a human annotation technique has been utilized to identify red tide regions whose ground polygons can be further estimated using the direct geo-localization model, taking into account how difficult it is to detect red tides automatically. Finally, the accuracy of direct geo-localization and the viability of the proposed solution has been evaluated and verified using real UAV datasets. The experimental results show that the direct geo-localization precision is better than 20 m when only onboard sensor data is used. The suggested workflow is appropriate for monitoring red tides, which can provide critical information for managing marine ecosystems. The executable toolkit would be made publicly available at https://github.com/json87/PhotoDigitizer.