GNSS remote sensing
Global navigation satellite systems have become an indispensable tool in positioning. Applications of its potential are very wide spread and found in a large varity of user's fields. Besides the primary GNSS' goal, the positioning, GNSS remote sensing is a field of research of rapidly increasing interest. At our lab we focus on GNSS Remote Sensing of snow coverage. A further research activity focusses on the determination of the water vapor distribution in the atmosphere and the estimation of the gradient of the electron content in the Earth's ionosphere.
Project list:
3D integrated sensing of troposphere using ground and space-based GNSS observations
This project, led by Wroclaw University of Environmental and Life Sciences (UPWr), aims on the use of the inverse Radon transform on dense space-based and ground-based GNSS observations for providing integrated 3D models of troposphere that will improve precipitation and humidity forecasts. As consortium member, MPG will support the project with ray-tracing algorithms, their integration into the tomography workflow as well as simulations of future GNSS and dense CubeSat constellations.
Start date:
01.10.2021
Project partners:
Wroclaw University of Environmental and Life Sciences, University of Wroclaw, Spire Global
Contacts at MPG:
Gregor Möller ()
Financiers (external)
National Science Centre Poland
Links:
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Water vapor fields by space-born geodetic sensing, tomographic fusion, and atmospheric modeling
By using GNSS and InSAR based techniques in combination with high resolution regional atmospheric weather models and geostatistical data merging techniques, the proposed project aims at developing and evaluating new approaches to derive improved spatio-temporal estimates of the atmospheric water vapor distribution. In particular, tomographic-based approaches for the evaluation of geodetic and remote sensing data will be further developed to improve the vertical and horizontal resolution of the investigated atmospheric state variables. The generated products are used for comparison and assimilation with atmospheric model-based information to finally obtain an optimal estimate of the atmospheric water vapor distribution.
Start date:
01.01.2018
Project partners:
Augsburg University, Karlsruhe Institute of Technology
Contacts at MPG:
Endrit Shehaj ()
Alain Geiger ()
Gregor Möller ()
Markus Rothacher ()
Financiers (external)
SNF swiss national science foundation
Links:
external page https://www.uni-augsburg.de/en/fakultaet/fai/geo/prof/georkl/forschung/project-atmowater/
GNSS Reflectometry
Over the past two decades, GNSS reflectometry (GNSS-R) established as a passive remote sensing technique with various ground, airborne and space applications. It involves the monitoring of the oceans (like sea level, wave height and wind speed), the determination of snow heights, or the sensing of the surface soil moisture content. After studying the determination of snow water equivalent from GNSS antennas buried below the snow, we current focusses on ground-based applications with dual-circularized antennas, and on the GNSS-R processing of data collected from low-cost GNSS sensors.
Start date:
01.03.2021
Project partners:
-
Contacts at MPG:
Roland Hohensinn ()
Links:
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Machine Learning for Troposphere
The scope of this project is to use machine-learning algorithms to predict tropospheric pathdelays experienced in space-geodetic techniques (such as GNSS) from meteorological parameters (pressure, temperature and water vapor pressure). These alternative delays, obtained without processing any GNSS observations, can be used by any user inside the trained network.
Start date:
01.07.2019
Project partners:
Space Geodesy Group (B. Soja) and Eco Vision Lab (J. Wegner and S. D'Aronco)
Contacts at MPG:
Endrit Shehaj ()
Alain Geiger ()
Gregor Möller ()
Markus Rothacher ()
Links:
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Cross-validation of tropospheric delays by means of InSAR, GNSS and Numerical Weather Prediction observations
In this project, tropospheric pathdelays retrieved by means of GNSS and InSAR techniques are cross-validated. Numerical Weather Prediction data are also used as an independent technique for validation of the results. The scope is to evaluate the possibility of using GNSS retrieved pathdelays to enhance the processing of InSAR observations. Furthermore, a rigorous combination can be provided as well, which will benefit from the complementary spatio-temporal characteristics of GNSS and InSAR and therefore, allows for computation of high-resolution pathdelay maps inside the InSAR scene.
Start date:
01.01.2020
Project partners:
Earth Observation and Remote Sensing Group (O. Frey)
Contacts at MPG:
Endrit Shehaj ()
Gregor Möller ()
Alain Geiger ()
Markus Rothacher ()
Links:
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