Dataset Information

Experimental verification of seafloor crustal deformation observations by UAV-based GNSS-A.

ABSTRACT: The Global Navigation Satellite System-Acoustic ranging combination technique (GNSS-A) is the only geodetic observation method that can precisely detect absolute horizontal and vertical seafloor crustal deformations at the centimetre scale. GNSS-A has detected many geophysical phenomena and is expected to make great contributions to earthquake disaster prevention science and geodesy. However, current observation methods that use vessels and buoys suffer from high cost or poor real-time performance, which leads to low observation frequency and delays in obtaining and transmitting disaster prevention information. To overcome these problems, a new sea surface platform is needed. Here, we present an unmanned aerial vehicle (UAV) system developed for GNSS-A surveys capable of landing on the sea surface. Submetre-level seafloor positioning is achieved based on real-time single-frequency GNSS data acquired over an actual site. UAV-based GNSS-A allows high-frequency, near real-time deployment, and low-cost seafloor geodetic observations. This system could be deployed to acquire high-frequency observations with centimetre-scale accuracies when using dual-frequency GNSS.

SUBMITTER: Yokota Y

PROVIDER: S-EPMC10011411 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Experimental verification of seafloor crustal deformation observations by UAV-based GNSS-A.

Yokota Yusuke Y Kaneda Masata M Hashimoto Takenori T Yamaura Shusaku S Kouno Kenji K Hirakawa Yoshiaki Y

Scientific reports 20230313 1

The Global Navigation Satellite System-Acoustic ranging combination technique (GNSS-A) is the only geodetic observation method that can precisely detect absolute horizontal and vertical seafloor crustal deformations at the centimetre scale. GNSS-A has detected many geophysical phenomena and is expected to make great contributions to earthquake disaster prevention science and geodesy. However, current observation methods that use vessels and buoys suffer from high cost or poor real-time performan ...[more]

PMID: 36914688

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Project description:There is currently a gap in satellite observations of the moisture structure during heavy precipitation conditions, since infrared and microwave sounders cannot sense water-vapour structure near the surface in the presence of intense precipitation. Conversely, Global Navigation Satellite System (GNSS) radio occultations (RO) can profile the moisture structure with high precision and vertical resolution, but cannot indicate the presence of precipitation directly. Polarimetric RO (PRO) measurements have been proposed as a method to characterize heavy rain in GNSS RO, by measuring the polarimetric differential phase delay induced by large size hydrometeors. Previous studies have shown that the PRO polarimetric phase shift is sensitive to the path-integrated rain rate under intense precipitation scenarios, but there is no current method to invert PRO measurements into quantitative estimates of the path-averaged rain rate. In this manuscript, a probabilistic inversion approach to the GNSS PRO observables is proposed, where the GPM precipitation products are used for the construction of an a priori look-up table (LUT) database. The performance of the LUTs is assessed for use in the inversion of satellite-based GNSS PRO observations, based on synthetically generated PRO data of actual events, which correspond to co-locations between GNSS RO profiles and the TRMM observations. The synthetic data include end-to-end propagation effects of the polarimetric observables and a simple separation algorithm to isolate the hydrometeor component of the observation. The assessment results in agreement better than ±1 mm/hr between the reference LUT and the actual rain statistics of the synthetic data, proving the suitability of the GPM-based probabilistic inversion tool. These findings indicate that the GNSS PRO products are capable of extending the current GNSS RO ones by associating indications of rain-rate probabilities at different altitudes, at ∼250 m vertical resolution and under intense precipitation scenarios with the standard vertical thermodynamic profiles.

Dataset Information

Experimental verification of seafloor crustal deformation observations by UAV-based GNSS-A.

Publications

Experimental verification of seafloor crustal deformation observations by UAV-based GNSS-A.

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