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Soil moisture mapping using forward scattered GPS L1 signals

Author
Alonso-Arroyo, A.; Forte, G.; Camps, A.; Park, H.; Pascual, D.; Onrubia, R.; Jove-Casulleras, R.
Type of activity
Presentation of work at congresses
Name of edition
33rd IEEE International Geoscience and Remote Sensing Symposium
Date of publication
2013
Presentation's date
2013-07-21
Book of congress proceedings
2013 IEEE International Geoscience & Remote Sensing Symposium: proceedings: July 21–26, 2013: Melbourne, Australia
First page
354
Last page
357
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
https://doi.org/10.1109/IGARSS.2013.6721165 Open in new window
Project funding
Aplicaciones avanzadas en radio ocultaciones y dispersometría utilizando señales GNSS y otras señales de oportunidad
SISTEMA GNSS-R PARA FUTURAS MISIONES SMOS
Repository
http://hdl.handle.net/2117/22269 Open in new window
URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6721165 Open in new window
Abstract
This work presents a novel technique for the determination of soil moisture obtaining 2-D Soil Moisture (SM) information with a single instrument. Both the instrument and the retrieval algorithm used, which is based on inferring the reflection coefficient of the terrain by direct and forward scattering polarimetric measurements of Global Navigation Satellite Systems (GNSS) Signals, are briefly described. Some preliminary results of a field campaign performed on La Pobla de Mafumet (Tarragona, Sp...
Citation
Alonso-Arroyo, A. [et al.]. Soil moisture mapping using forward scattered GPS L1 signals. A: IEEE International Geoscience and Remote Sensing Symposium. "2013 IEEE International Geoscience & Remote Sensing Symposium: proceedings: July 21–26, 2013: Melbourne, Australia". Melboune: Institute of Electrical and Electronics Engineers (IEEE), 2013, p. 354-357.
Keywords
Forest Fire prevention, Global Navigation Satellite System Reflectometry (GNSS-R), Smart-Irrigation, Soil Moisture (SM), Waveform-Peak
Group of research
CTE-CRAE - Space Science and Technology Research Group
RSLAB - Remote Sensing Lab

Participants