Results 81 to 90 of about 2,048 (223)

Data intensive scientific analysis with grid computing [PDF]

open access: yes, 2011
At the end of September 2009, a new Italian GPS receiver for radio occultation was launched from the Satish Dhawan Space Center (Sriharikota, India) on the Indian Remote Sensing OCEANSAT-2 satellite.
E. Kursinski   +12 more
core   +1 more source

Regional Land Surface Conditions Developed Using the High‐Resolution Land Data Assimilation System: Challenges Over Complex Orography Himalayan Region

open access: yesMeteorological Applications, Volume 32, Issue 4, July/August 2025.
High‐resolution land data assimilation system (HRLDAS) simulations at 2 km resolution from 2011 to 2021 over Uttarakhand. HRLDAS outperforms global and regional analyses by capturing finer spatial heterogeneity, with lower soil moisture error and high soil temperature correlation (0.94) against satellite and in situ observations.
Buri Vinodhkumar   +5 more
wiley   +1 more source

PRETTY: Grazing altimetry measurements based on the interferometric method [PDF]

open access: yes, 2017
The exploitation of signals stemming from global navigation systems for passive bistatic radar applications has beenproposed and implemented within numerous studies.
Beck, Peter   +7 more
core  

UAV based GNSS reflectometry

open access: yes, 2023
Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats ...
openaire   +1 more source

Evaluating Water Levels From the Surface Water and Ocean Topography (SWOT) Mission in a Hyper‐Tidal Coastal and Estuarine Environment

open access: yesEarth and Space Science, Volume 12, Issue 7, July 2025.
Abstract The launch of the Surface Water and Ocean Topography (SWOT) satellite in December 2022 started a new era of swath altimetry, introducing an unprecedented global data set of high‐resolution two‐dimensional water level imagery. During its initial calibration and validation phase (cal/val), SWOT conducted daily observations for 3 months providing
I. D. Lichtman   +6 more
wiley   +1 more source

Improving GNSS-R sea level determination through inverse modeling of SNR data [PDF]

open access: yes, 2016
This paper presents a new method for retrieving sea surface heights from Global Navigation Satellite Systems reflectometry (GNSS-R) data by inverse modeling of SNR observations from a single geodetic receiver.
Haas, Rüdiger   +2 more
core   +1 more source

Helmert Variance Component Estimation for Multi-GNSS Relative Positioning [PDF]

open access: yes, 2020
The Multi-constellation Global Navigation Satellite System (Multi-GNSS) has become the standard implementation of high accuracy positioning and navigation applications.
Fang, Zhenlong   +5 more
core   +2 more sources

One‐Hundred Fundamental, Open Questions to Integrate Methodological Approaches in Lake Ice Research

open access: yesWater Resources Research, Volume 61, Issue 5, May 2025.
Abstract The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate ...
Joshua Culpepper   +25 more
wiley   +1 more source

Developing the Test Bench for a Next-Generation Bistatic GNSS Reflectometry Receiver Instrument [PDF]

open access: yes, 2018
Recently, scientists have started to exploit global navigational satellite system (GNSS) signals for geophysical remote sensing using a technique called "reflectometry" (GNSS-R).
Linnabary, Ryan B.
core  

Feasibility Demonstration of Using the Signal‐to‐Noise Ratio Observations From Geodetic GNSS Receivers to Retrieve Dry Snow Density

open access: yesWater Resources Research, Volume 61, Issue 4, April 2025.
Abstract The geodetic Global Navigation Satellite System (GNSS) receiver has been proven to retrieve snow depth using the phase change rate of the signal‐to‐noise ratio (SNR) observations. Snow density can be related to snow permittivity and is theoretically sensitive to the amplitude of the GNSS reflected signal. However, retrieving snow density using
J. Zhang   +7 more
wiley   +1 more source

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