Single-Pass Soil Moisture Retrieval Using GNSS-R at L1 and L5 Bands: Results from Airborne Experiment
Global Navigation Satellite System—Reflectometry (GNSS-R) has already proven its potential for retrieving a number of geophysical parameters, including soil moisture. However, single-pass GNSS-R soil moisture retrieval is still a challenge. This study presents a comparison of two different data sets...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/4/797 |
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| author | Joan Francesc Munoz-Martin Raul Onrubia Daniel Pascual Hyuk Park Miriam Pablos Adriano Camps Christoph Rüdiger Jeffrey Walker Alessandra Monerris |
| author_facet | Joan Francesc Munoz-Martin Raul Onrubia Daniel Pascual Hyuk Park Miriam Pablos Adriano Camps Christoph Rüdiger Jeffrey Walker Alessandra Monerris |
| author_sort | Joan Francesc Munoz-Martin |
| collection | DOAJ |
| description | Global Navigation Satellite System—Reflectometry (GNSS-R) has already proven its potential for retrieving a number of geophysical parameters, including soil moisture. However, single-pass GNSS-R soil moisture retrieval is still a challenge. This study presents a comparison of two different data sets acquired with the Microwave Interferometer Reflectometer (MIR), an airborne-based dual-band (L1/E1 and L5/E5a), multiconstellation (GPS and Galileo) GNSS-R instrument with two 19-element antenna arrays with four electronically steered beams each. The instrument was flown twice over the OzNet soil moisture monitoring network in southern New South Wales (Australia): the first flight was performed after a long period without rain, and the second one just after a rain event. In this work, the impact of surface roughness and vegetation attenuation in the reflectivity of the GNSS-R signal is assessed at both L1 and L5 bands. The work analyzes the reflectivity at different integration times, and finally, an artificial neural network is used to retrieve soil moisture from the reflectivity values. The algorithm is trained and compared to a 20-m resolution downscaled soil moisture estimate derived from SMOS soil moisture, Sentinel-2 normalized difference vegetation index (NDVI) data, and ECMWF Land Surface Temperature. |
| first_indexed | 2024-03-09T00:39:28Z |
| format | Article |
| id | doaj.art-610a7ce07b0140dbbb0243172057a3c9 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T00:39:28Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-610a7ce07b0140dbbb0243172057a3c92023-12-11T17:56:00ZengMDPI AGRemote Sensing2072-42922021-02-0113479710.3390/rs13040797Single-Pass Soil Moisture Retrieval Using GNSS-R at L1 and L5 Bands: Results from Airborne ExperimentJoan Francesc Munoz-Martin0Raul Onrubia1Daniel Pascual2Hyuk Park3Miriam Pablos4Adriano Camps5Christoph Rüdiger6Jeffrey Walker7Alessandra Monerris8CommSensLab—UPC, Universitat Politècnica de Catalunya—BarcelonaTech, and IEEC/CTE-UPC, 08034 Barcelona, SpainCommSensLab—UPC, Universitat Politècnica de Catalunya—BarcelonaTech, and IEEC/CTE-UPC, 08034 Barcelona, SpainCommSensLab—UPC, Universitat Politècnica de Catalunya—BarcelonaTech, and IEEC/CTE-UPC, 08034 Barcelona, SpainCommSensLab—UPC, Universitat Politècnica de Catalunya—BarcelonaTech, and IEEC/CTE-UPC, 08034 Barcelona, SpainPhysical and Technological Oceanography Group, Consejo Superior de Investigaciones Científicas (ICM-CSIC), Centre of Excellence Severo Ochoa, Institut de Ciències del Mar, Passeig Marítim de la Barceloneta 37-49, 08003 Barcelona, SpainCommSensLab—UPC, Universitat Politècnica de Catalunya—BarcelonaTech, and IEEC/CTE-UPC, 08034 Barcelona, SpainDepartment of Civil Engineering, Monash University, Clayton, VIC 3800, AustraliaDepartment of Civil Engineering, Monash University, Clayton, VIC 3800, AustraliaDepartment of Infrastructure Engineering, The University of Melbourne, Parkville, VIC 3010, AustraliaGlobal Navigation Satellite System—Reflectometry (GNSS-R) has already proven its potential for retrieving a number of geophysical parameters, including soil moisture. However, single-pass GNSS-R soil moisture retrieval is still a challenge. This study presents a comparison of two different data sets acquired with the Microwave Interferometer Reflectometer (MIR), an airborne-based dual-band (L1/E1 and L5/E5a), multiconstellation (GPS and Galileo) GNSS-R instrument with two 19-element antenna arrays with four electronically steered beams each. The instrument was flown twice over the OzNet soil moisture monitoring network in southern New South Wales (Australia): the first flight was performed after a long period without rain, and the second one just after a rain event. In this work, the impact of surface roughness and vegetation attenuation in the reflectivity of the GNSS-R signal is assessed at both L1 and L5 bands. The work analyzes the reflectivity at different integration times, and finally, an artificial neural network is used to retrieve soil moisture from the reflectivity values. The algorithm is trained and compared to a 20-m resolution downscaled soil moisture estimate derived from SMOS soil moisture, Sentinel-2 normalized difference vegetation index (NDVI) data, and ECMWF Land Surface Temperature.https://www.mdpi.com/2072-4292/13/4/797GNSS-Rdual-bandairbornesoil moisturesurface roughnessvegetation |
| spellingShingle | Joan Francesc Munoz-Martin Raul Onrubia Daniel Pascual Hyuk Park Miriam Pablos Adriano Camps Christoph Rüdiger Jeffrey Walker Alessandra Monerris Single-Pass Soil Moisture Retrieval Using GNSS-R at L1 and L5 Bands: Results from Airborne Experiment Remote Sensing GNSS-R dual-band airborne soil moisture surface roughness vegetation |
| title | Single-Pass Soil Moisture Retrieval Using GNSS-R at L1 and L5 Bands: Results from Airborne Experiment |
| title_full | Single-Pass Soil Moisture Retrieval Using GNSS-R at L1 and L5 Bands: Results from Airborne Experiment |
| title_fullStr | Single-Pass Soil Moisture Retrieval Using GNSS-R at L1 and L5 Bands: Results from Airborne Experiment |
| title_full_unstemmed | Single-Pass Soil Moisture Retrieval Using GNSS-R at L1 and L5 Bands: Results from Airborne Experiment |
| title_short | Single-Pass Soil Moisture Retrieval Using GNSS-R at L1 and L5 Bands: Results from Airborne Experiment |
| title_sort | single pass soil moisture retrieval using gnss r at l1 and l5 bands results from airborne experiment |
| topic | GNSS-R dual-band airborne soil moisture surface roughness vegetation |
| url | https://www.mdpi.com/2072-4292/13/4/797 |
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