Coastal Altimetry Using Interferometric Phase From GEO Satellite in Quasi-Zenith Satellite System

He, Yunqiao; Gao, Fan; Xu, Tianhe; Meng, Xinyue; Wang, Nazi

doi:10.1109/lgrs.2021.3068376

Cited by 12 publications

(6 citation statements)

References 18 publications

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“…Multi-sensor integration. In order to obtain finer surface 3D information, multisensor integration and fusion will be an inevitable choice for the development of satellite-based earth observation technology, to achieve the high accuracy of satellite-based LiDAR measurement data and the high resolution of optical/ microwave imaging technology combined to give full play to the advantages of multiple detection means [22,[95][96][97]. The need to study the automatic and accurate matching between LiDAR measurement data and imaging sensor data, as well as the overall fusion strategy for the difference in accuracy between the two, are issues that need to be further studied and solved.…”

Section: Discussionmentioning

confidence: 99%

GIS and Spatial Analysis

2023

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networks, such as road networks, transit systems, and bike lanes, are a key application. It helps to optimize routes, identify chokepoints, and plan for future growth.In addition, they have an important role into infrastructure assets management, such as bridges, tunnels, and pipelines. This can help to identify maintenance needs, track inspections, and plan for replacements.Another common use is for identifying suitable locations for new infrastructure projects, such as highways, airports, and transit stations, minimizing the environmental impacts and optimizing the use of resources. Furthermore, one can model and analyze the environmental impacts of those infrastructure projects, such as air and water pollution, noise pollution, and habitat destruction. This approach enables to mitigate the impacts and ensure compliance with regulations.Managing and responding to emergencies, such as natural disasters, traffic accidents, and power outages, are one of the major GIS applications. It reinforces public safety and minimizes the impact of these events [8]. Mining exploration and monitoringGIS allows for the efficient management and analysis of large amounts of spatial data, which is critical in the mining industry. GIS technology is well adapted to create detailed maps of mining sites, showing the location of ore deposits, infrastructure, and other important features. This information is further used to plan and manage mining operations, as well as to identify potential areas for further exploration [9].Spatial analysis techniques, such as geostatistics, help to analyze and model mining data, including geologic and geochemical data, to identify patterns and trends. These analyses can help to optimize the location of mining operations, reduce costs, and increase the accuracy of mineral resource estimates.In addition, GIS and spatial analysis are fitted for environmental monitoring, such as tracking changes in vegetation, water quality, and air quality around mining sites, ensuring that mining operations are conducted in an environmentally responsible manner and to mitigate any negative impacts. Lidar applicationsLidar (Light Detection and Ranging) is a remote-sensing technology that uses lasers to measure distances to the Earth's surface and creates highly accurate 3D models of landscapes and other features [10].GIS can be used to manage and analyze Lidar data, which can be in the form of point clouds or raster data. Point clouds are collections of 3D points that represent the surface of the Earth, while raster data are a grid of cells that represent the elevation of the Earth's surface. GIS software can process and display both types of data, allowing for analysis and visualization of Lidar-derived information.Spatial analysis techniques, such as terrain analysis, viewshed analysis, and slope analysis, permit to extract valuable information from Lidar data. For example, terrain analysis makes possible to identify areas of high and low elevation, while viewshed analysis determines the areas that are visible from a cer...

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Section: Discussionmentioning

confidence: 99%

GIS and Spatial Analysis

2023

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“…Phase-based GNSS-IR sea level altimetry can make use of data that is very close to zenith [65], [66]. In the raytracing results (low-right part in Fig.…”

Section: Discussionmentioning

confidence: 99%

A Novel Tropospheric Error Formula for Ground-Based GNSS Interferometric Reflectometry

Feng,

Haas,

Elgered

2023

IEEE Trans. Geosci. Remote Sensing

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We deduce a Novel Interferometric Tropospheric Error (NITE) formula for ground-based GNSS interferometric reflectometry (GNSS-IR). This formula contains two parts: a geometric displacement error that accounts for the reflection point change due to the atmosphere and the earth curvature, and a path delay derived following the definition of the mapping function (with the small curve path effect included). We validate the NITE formula together with two previously used approaches, the bending angle correction and the mapping function path delay (MPF delay) using raytracing and radiosonde data. The raytracing results show that the NITE formula is more accurate than the previous approaches. Numerically, the geometric displacement error is < 5 % of the path delay error for a GNSS antenna located 20 m above sea level. We further evaluate six tropospheric correction strategies for GNSS-IR sea level monitoring through two sets of experiments. With an elevation angle range test, we show that applying no tropospheric correction and applying the bending angle correction plus the MPF delay both introduce large elevation-dependent biases. Analyzing the time series of differences between GNSS-IR and tide gauges sea level, we show that the bending angle correction with the widely used Bennett equation introduces long-term (4 h to several months) trends in the sea-level retrievals. We identify one station where the NITE formula produces better long-term (τ > 4 h) sea-level retrievals. Finally, we show that at low elevation angles, the bending angle correction can be reformulated as an MPF delay.

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“…However, this is a complex problem. Scholars have proposed methods to avoid calculating the integer ambiguity [27][28][29], and these methods can achieve a temporal resolution of up to 1 min. Nonetheless, during emergency situations such as flash floods, water authorities require even higher temporal resolution of water level data to effectively develop emergency response measures.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Water Level Monitoring Based on GNSS Dual-Antenna Attitude Measurement

Pengjie

Pang

et al. 2023

Remote Sensing

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Real-time and high-precision water level monitoring is crucial for the fields of hydrology, hydraulic engineering, and disaster prevention and control. The most prevalent method for measuring water level is through the use of water level gauges, which can be costly and have limited coverage. In recent years, Global Navigation Satellite System Reflectometry (GNSS-R) technology has emerged as a promising approach for water level monitoring due to its low cost and high coverage. However, a limitation of current GNSS-R technology is the extended time required to record signals, which hinders its potential for real-time application. This paper introduces a novel real-time water level monitoring method based on GNSS dual-antenna attitude measurement and develops a model to invert water level based on baseline vector. This method uses double-difference observations to eliminate errors caused by various factors, such as satellite and receiver clock, and ionospheric and tropospheric delay. To avoid the impact of detecting and correcting cycle slips during real-time operations, a single-epoch calculation method is introduced. In order to verify the stability and reliability of our method, field tests were carried out at Dongshahe Station in Beijing. We obtained water level data with a time resolution of 1 Hz through field experiments. Experimental data collected from 12 May to 8 June 2022 and from 4 July to 8 August 2022 showed good agreement with on-site water gauge measurements, with root mean square errors of 2.77 cm and 2.54 cm, respectively. Experimental results demonstrate that this method can achieve high-precision, high-temporal-resolution water level monitoring.

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Coastal Altimetry Using Interferometric Phase From GEO Satellite in Quasi-Zenith Satellite System

Cited by 12 publications

References 18 publications

GIS and Spatial Analysis

GIS and Spatial Analysis

A Novel Tropospheric Error Formula for Ground-Based GNSS Interferometric Reflectometry

Real-Time Water Level Monitoring Based on GNSS Dual-Antenna Attitude Measurement

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