GNSS Reflectometry

Reflected Global navigation satellite system (GNSS) from the ground can be used to estimate surface parameters. This type of measurement is called GNSS-reflectometry (GNSS-R), and multiple spaceborne systems have been developed for GNSS-R measurements. CYGNSS is one of the leading systems developed for GNSS-R. It was launched at the end of 2016, and it consisted of eight satellites; one of them deorbited in June 2024. 

Modelling

This project focuses on modeling GNSS-R signals over land and retrieving surface properties, such as soil moisture, from GNSS-R measurements. 

The developed model, named improved geometric optics with topography (IGOT) model, is applicable to surfaces with topographic reliefs and light vegetation. A version of the model is extended to forested areas by improving accounting for vegetation attenuation and adding the vegetation volume scattering effects. Moreover, the analytical sensitivity of the model to land surface parameters is investigated. The model is validated against NASA CYGNSS mission observations over multiple areas with good performance.

We developed multiple algorithms for retrieving soil moisture from CYGNSS measurements using physics-based methods and ML-based methods.

Applications

Another aspect of the GNSS Reflectometry project is to use the reflectivities from CYGNSS to map wildfire-burned areas at high temporal resolution and low latency. We developed texture and machine learning based algorithms to generate burned area maps.

Publications

Journals

• A. Melebari, J. D. Campbell, E. Hodges, and M. Moghaddam, “Analytical Assessment of GNSS-R Delay Doppler Map Sensitivity to Land Surface Variables Using a Physics-Based Model,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 63, pp. 1-15, 2025, Art no. 2000915, doi: 10.1109/TGRS.2025.3532591.
• A. Melebari, J. D. Campbell, E. Hodges, and M. Moghaddam, “Improved Geometric Optics with Topography (IGOT) Model for GNSS-R Delay-Doppler Maps Using Three-Scale Surface Roughness,” Remote Sensing, vol. 15, no. 7, p. 1880, Mar. 2023, doi: 10.3390/rs15071880.
• A. Azemati, A. Melebari, J. D. Campbell, J. P. Walker, and M. Moghaddam, “GNSS-R Soil Moisture Retrieval for Flat Vegetated Surfaces Using a Physics-Based Bistatic Scattering Model and Hybrid Global/Local Optimization,” Remote Sensing, vol. 14, no. 13, p. 3129, Jun. 2022, doi: 10.3390/rs14133129.
• E. Hodges, J. D. Campbell, A. Melebari, A. Bringer, J. T. Johnson, and M. Moghaddam, “Using Lidar Digital Elevation Models for Reflectometry Land Applications,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-9, 2023, Art no. 5800509, doi: 10.1109/TGRS.2023.3256303.
• J. D. Campbell, R. Akbar, A. Bringer, D. Comite, L Dente, S. T. Gleason, L. Guerriero, E. Hodges, J. T. Johnson, S. Kim, A. Melebari, N. Pierdicca, C. S. Ruf, L. Tsang, T. Wang, H. Xu, J. Zhu, and M. Moghaddam, “Intercomparison of Electromagnetic Scattering Models for Delay-Doppler Maps Along a CYGNSS Land Track With Topography,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-13, 2022, Art no. 2007413, doi: 10.1109/TGRS.2022.3210160.
• J. D. Campbell, A. Melebari, and M. Moghaddam, “Modeling the Effects of Topography on Delay-Doppler Maps,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 1740-1751, 2020, doi: 10.1109/JSTARS.2020.2981570.

Conferences

• A. Melebari, J. D. Campbell, E. Hodges, and M. Moghaddam, “Sensitivity Analysis of GNSS-R Delay Doppler Maps to Soil Moisture and Vegetation Using a Physics-Based Model,” IGARSS 2024 – 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 823-826, doi: 10.1109/IGARSS53475.2024.10641646.
• A. Melebari, E. Hodges, J. D. Campbell, and M. Moghaddam, “Surface Soil Moisture Retrieval from GNSS-R Observations Using a Physics-Based Method over Topographical Terrains”, American Geophysical Union (AGU) Annual Meeting 2023, San Francisco, CA, USA, 2023.
• A. Melebari, J. D. Campbell, E. Hodges, and M. Moghaddam, “Validation of the Improved Geometric Optics with Topography (IGOT) GNSS-R Model Using CYGNSS Land Observations,” IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 507-509, doi: 10.1109/IGARSS52108.2023.10283325.
• A. Melebari et al., “CYGNSS SoilSCAPE Sites: Sensor Calibration and Data Analysis,” IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 4628-4630, doi: 10.1109/IGARSS52108.2023.10282411.
• A. Melebari, G. Tsagkatakis, R. Akbar, E. Hodges, J. D. Campbell, J. P. Walker, and M. Moghaddam, “Soil Moisture Retrieval from CYGNSS Observations: Comparison of Results from a Physics-based Method and a Machine-learning-based Method,” 2022 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM), Boulder, CO, USA, 2022.
• A. Melebari, E. Hodges, G. Tsagkatakis, A. Azemati, R. Akbar, J. P. Walker, J. D. Campbell, and M. Moghaddam, “Soil Moisture Retrieval from CYGNSS Using Physics-Based and Machine Learning Methods and Use of Lidar-Derived Surface Gradients for Improved Forward Modeling,” presented at the IEEE Specialist Meeting on Reflectometry using GNSS and other Signals of Opportunity (GNSS+R) 2021, Sep 2021, Virtual.
• E. Hodges, J. D. Campbell, A. Melebari, T. Wang, J. T. Johnson, and M. Moghaddam, “Detection and Statistical Modeling of the Effect of Mima Mounds on Bistatic Radar Scattering,” 2025 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM), Boulder, CO, USA, 2025, pp. 404-405, doi: 10.23919/USNC-URSINRSM66067.2025.10907019.
• P. Shokri, G. Tsagkatakis, A. Melebari, E. Hodges, and M. Moghaddam, “Integrating Physics and Machine Learning for Soil Moisture Retrieval Using CYGNSS Observations”, in American Geophysical Union (AGU) Annual Meeting 2024, Washington, D.C., USA, 2024.
• G. Tsagkatakis, A. Melebari, R. Akbar, J. D. Campbell, E. Hodges, and M. Moghaddam, “Uncertainty Quantification in Machine Learning Based Retrieval of Soil Moisture from GNSS-R Observations,” IGARSS 2024 – 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 1824-1828, doi: 10.1109/IGARSS53475.2024.10642241.
• G. Tsagkatakis, A. Melebari, J. D. Campbell, E. Hodges, and M. Moghaddam, “Quantifying Uncertainty in Machine Learning Based Soil Moisture Retrieval From GNSS-R Measurements,” 2024 International Conference on Electromagnetics in Advanced Applications (ICEAA), Lisbon, Portugal, 2024, pp. 492-492, doi: 10.1109/ICEAA61917.2024.10701691.
• A. Kannan, A. Melebari, G. Tsagkatakis, K. Nelson, V. Ravindra, S. Nag, M. Moghaddam, “Mapping Wildfire Burned Area Using GNSS-Reflectometry in Densely Vegetated Regions with Complex Topography: A Machine Learning Approach,” IGARSS 2024 – 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 2072-2076, doi: 10.1109/IGARSS53475.2024.10641487.
• S. Nag, V. Ravindra, R. Levinson, M. Moghaddam, K. Nelson, J. Mandel, A. Kochanski, A. F. Caus, A. Melebari, A. Kannan, R. Ketzner “Distributed Spacecraft with Heuristic Intelligence to Monitor Wildfire Spread for Responsive Control,” IGARSS 2024 – 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 699-703, doi: 10.1109/IGARSS53475.2024.10640833.
• A. Kannan et al., ‘Mapping Wildfire Burned Area using GNSS Reflectometry with Machine Learning”, American Geophysical Union (AGU) Annual Meeting 2023, San Francisco, CA, USA, 2023.
• J. D. Campbell, A. Melebari, E. Hodges, and M. Moghaddam, “Integration of Vegetation and Topography Models for GNSS-R,” 2023 International Conference on Electromagnetics in Advanced Applications (ICEAA), Venice, Italy, 2023, pp. 589-589, doi: 10.1109/ICEAA57318.2023.10297718.
• G. Tsagkatakis, A. Melebari, R. Akbar, J. D. Campbell, E. Hodges, and M. Moghaddam, “Deep Generative Regression Models for Soil Moisture Retrieval From GNSS-R Observations,” 2023 International Conference on Electromagnetics in Advanced Applications (ICEAA), Venice, Italy, 2023, pp. 291-291, doi: 10.1109/ICEAA57318.2023.10297722.
• E. Hodges, A. Melebari, J. D. Campbell, T. Wang, Y. Yi, J. T. Johnson, M. Moghaddam, “A Bistatic GPS Scattering Model for Mima Mounds”, 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023.
• E. Hodges, J. D. Campbell, A. Melebari, A. Bringer, J. T. Johnson, and M. Moghaddam, “Application of LIDAR Digital Elevation Models to CYGNSS Land Modeling,” presented at the Photonics and Electromagnetics Research Symposium (PIERS) 2021, April 2022, Virtual.
• J. D. Campbell, R. Akbar, A. M. Bringer, D. Comite, L. Dente, S. T. Gleason, L. Guerriero, E. Hodges, J. T. Johnson, S.-B. Kim, A. Melebari, N. Pierdicca, C. S. Ruf, L. Tsang, T. Wang, H. Xu, J. Zhu, and M. Moghaddam, “GNSS-R Models for Electromagnetic Scattering from Land Surfaces with Topography,” presented at the Photonics and Electromagnetics Research Symposium (PIERS), April 2022, Virtual
• J. D. Campbell, A. Melebari, E. Hodges, R. Akbar and M. Moghaddam, “Initial Investigation of a GNSS-R Multiscale Rough Surface Forward Model at San Luis Valley Calibration/Validation Sites,” 2021 International Conference on Electromagnetics in Advanced Applications (ICEAA), Honolulu, HI, USA, 2021, pp. 070-070, doi: 10.1109/ICEAA52647.2021.9539759.
• J. D. Campbell, R. Akbar, A. Azemati, A. Bringer, D. Comite, L. Dente, S. T. Gleason; L. Guerriero, E. Hodges, J. T. Johnson, S. Kim, A. Melebari, N. Pierdicca, B. Ren C. S. Ruf, L. Tsang, H. Xu, J. Zhu, M. Moghaddam, “Intercomparison of Models for CYGNSS Delay-Doppler Maps at a Validation Site in the San Luis Valley of Colorado,” 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 2021, pp. 2001-2004, doi: 10.1109/IGARSS47720.2021.9553296.
• A. Azemati, A. Melebari, J. D. Campbell, E. Hodges, and M. Moghaddam, “A Time-Series Study of Bistatic Delay-Doppler Maps Over Vegetated Terrain: Comparison of Simulations and CYGNSS Observations,” in Proceedings of the 2021 International Union of Radio Science General Assembly and Scientific Symposium (URSI GASS), 2021A. Azemati, A. Etminan, A. Melebari, J. D. Campbell, E. Hodges, and M. Moghaddam, “Root-Zone Soil Moisture Retrieval from CYGNSS Over-Land Observations via Bistatic Vegetation Scattering model and Hybrid Global and Local Optimization Scheme,” 2021 International Conference on Electromagnetics in Advanced Applications (ICEAA), Honolulu, HI, USA, 2021, pp. 030-030, doi: 10.1109/ICEAA52647.2021.9539580.