Assessment of the GNSS-RTK for Application in Precision Forest Operations

Cho, Hyun-Min; Park, Jin-Woo; Lee, Jung-Soo; Han, Sang-Kyun

doi:10.3390/rs16010148

Cited by 1 publication

(1 citation statement)

References 31 publications

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“…Prior to the drone surveys a set of ground control points (GCPs) were uniformly distributed and measured along the coastline of each study area. The GCPs were measured with a Global Navigation Satellite System Real-Time Kinematics (GNSS RTK) GPS [49] for achieving high accuracy (± 2cm). This level of accuracy is crucial in drone surveys that produce imagery with centimeter-scale spatial resolution while the onboard GPS sensor has a horizontal accuracy of approximately two meters.…”

Section: Onshore Surveymentioning

confidence: 99%

Refraction-aware Structure-from-Motion for Airborne Bathymetry

Makris,

Nicodemou,

Alevizos

et al. 2024

Preprint

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In this work, we introduce the first pipeline that combines a refraction-aware Structure-from-Motion (SfM) method with a deep learning model specifically designed for airborne bathymetry. We accurately estimate the 3D positions of the submerged points by integrating refraction geometry within the SfM optimization problem. This way, no refraction correction as post-processing is required. Experiments with simulated data that approach the real-world capturing conditions demonstrate that SfM with refraction correction is extremely accurate, with submillimeter errors. We integrate our refraction-aware SfM within a deep learning framework that also takes into account radiometrical information, developing a combined spectral and geometry-based approach, with further improvements on accuracy and robustness to different seafloor types, both textured and textureless. We conducted experiments with real-world data at 2 locations in the southern Mediterranean Sea, with varying seafloor types which demonstrate the benefits of refraction correction for the deep learning framework. We open-source our refraction-aware SfM, providing researchers in airborne bathymetry with a practical tool to apply SfM in shallow water areas.

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Section: Onshore Surveymentioning

confidence: 99%