1. SNOW MONITORING USING GNSS-R TECHNIQUES § Remote Sensing Lab, Dept. TSC, Building D3, Universitat Politècnica de Catalunya, Barcelona, Spain and IEEC CRAE/UPC ∞ SMOS-Barcelona Expert Centre, Barcelona, Spain Tel. +34934054664, E-08034 Barcelona, Spain. E-mail: nereida@tsc.upc.edu N. Rodriguez-Alvarez §, A. Aguasca §, E. Valencia §, X. Bosch-Lluis §, I. Ramos-Perez §, H. Park §, A. Camps §∞, M. Vall-llossera §∞ IGARSS’11 – Vancouver, Canada, 24 th -29 th July 2011 FR4.T05: GNSS Remote Sensing in Atmosphere, Ocean and Hydrology II

2. © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 1.INTRODUCTION 2.THE SMIGOL REFLECTOMETER 3.FUNDAMENTALS OF THE INTERFERENCE PATTERN TECHNIQUE 4.FIELD EXPERIMENT 5.RESULTS 6.CONCLUSIONS 7.ACKNOWLEDGEMENTS INDEX (1/14) SNOW MONITORING USING GNSS-R TECHNIQUES

3. Use of Global Navigation Satellite Signals Reflections (GNSS-R) techniques REMOTE SENSING OceanLandIce Altimetry Sea State Soil Moisture Vegetation height Surface topography Altimetry Age INTRODUCTION (2/14) © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 Inland waters Reservoir Level SNOW MONITORING USING GNSS-R TECHNIQUES Snow Thickness

4. Based on he interference pattern of the GPS direct and reflected signals, after reflecting from the surface. Objective: GNSS-R Technique studied: The Interference Pattern Technique (IPT) Snow thickness monitoring. (3/14) © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 INTRODUCTION SNOW MONITORING USING GNSS-R TECHNIQUES

5. Central frequency = 1.57542 GHz (GPS L1) Measures the interference between direct and reflected signals during all the satellite passages. THE SMIGOL REFLECTOMETER The Soil Moisture Interference-pattern GNSS Observations at L-band (SMIGOL) Reflectometer is the instrument implementing the IPT. Figure 1. The SMIGOL Reflectometer architecture. elevation angle of GPS satellite changes (Fig. 2). Samples @ 1 s received interferometric power depends on the elevation angle (Fig. 3) Result Figure 2. The received power is function of the GPS satellite position Main architecture (Fig. 1) (4/14) Figure 2. The received power is function of the GPS satellite position Figure 3. Received interference power as a function of the elevation angle © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 SNOW MONITORING USING GNSS-R TECHNIQUES

6. THE USE OF THE IPT FOR WATER LEVEL MONITORING Received interferometric power Where : Figure 4. The SMIGOL Reflectometer basic configuration FUNDAMENTALS OF THE INTERFERENCE PATTERN TECHNIQUE (5/14) © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 SNOW MONITORING USING GNSS-R TECHNIQUES

7. (6/14) © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 FUNDAMENTALS OF THE INTERFERENCE PATTERN TECHNIQUE Figure 5. Received interference power assuming snow thickness layer of (a) 5 cm and (b) 40 cm. (a) (b) An equivalent situation was previously studied: vegetation height retrieval. As it was found there, when the snow thickness increases the number of notches and change their position. EFFECT OF THE SNOW THICKNESS SNOW MONITORING USING GNSS-R TECHNIQUES NOTCH NOTCHES

8. (7/14) © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 FUNDAMENTALS OF THE INTERFERENCE PATTERN TECHNIQUE THE ALGORITHM FOR RETRIEVAL From theory the notches evolution dependence on the elevation angles is found, fig. 6. SNOW MONITORING USING GNSS-R TECHNIQUES For the first DoY of measurement, select the notches in the received powers sequences and compute the snow thickness based on fig. 6. In order to solve the uncertainly, assume that 5 cm is the snow thickness (known from ground-truth), and choose the nearest solution. The solution for each satellite is stored for being used as the calibration measurement. From that measurement the evolution of notches is tracked. The criterion to solve the uncertainty, when processing the following measurement days, has been stated to be that snow falling affects all the surface in the same way and then the most probable solution obtained from fig. 6 is selected. Figure 6. Theoretical evolution of notches. The notches position and the number of them (each black line defines the evolution of one notch) describe the snow thickness. The snow layer has been simulated considering a snow wetness volume of 2% and a snow density of 8 %.

9. FIELD EXPERIMENT (8/14) © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 Figure 7. The measurements site, Pla de Beret, Vall d’Aran, Lleida, Spain (42º42’44’’N, 0º56’22’’E) THE MEASUREMENT SITE SNOW MONITORING USING GNSS-R TECHNIQUES Site: Meteorological station located at Pla de Beret, Vall d’Aran, Lleida, Spain. Site coordinates 42º42’44’’N, 0º56’22’’E Collaboration: -Institut Geològic de Catalunya, Barcelona, Spain -Conselh Generau d’Aran, located at Vielha, Val d’Aran, Lleida, Spain

10. (9/14) © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 Figure 9. SMIGOL-Reflectometer measuring snow thickness Figure 10. SMIGOL-Reflectometer field of view Field experiment lasted 6 months from: November, 5 th, 2010 to May, 25 th, 2011 SMIGOL-Reflectometer is an autonomous instrument powered by solar panels and batteries Ground-truth measured using an ultrasonic sensor, attached at a meteorological station mast. FIELD EXPERIMENT SNOW MONITORING USING GNSS-R TECHNIQUES Figure 8. Ground-truth for half of the field experiment. THE MEASUREMENTS

11. (10/14) © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 FIELD EXPERIMENT Figure 11. The SMIGOL-Reflectometer measured powers and the simulated powers by applying the algorithm for (a) satellite 16 on DoY = 303 and (b) satellite 31 on DoY = 344. THE PROCESSING The SMIGOL-Reflectometer measurements were processed and the algorithm to compute the equivalent snow thickness was applied to the measurements. Notches were selected and their position was analyzed, following fig. 6 and the criterion stated in the algorithm. SNOW MONITORING USING GNSS-R TECHNIQUES

12. RESULTS (11/14) © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 SNOW THICKNESS MAPS RETRIEVED SNOW MONITORING USING GNSS-R TECHNIQUES

13. RESULTS © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 (12/13) SNOW MONITORING USING GNSS-R TECHNIQUES RETRIEVAL RESULTS. Correlation of the retrievals with the ground-truth snow thickness

14. CONCLUSIONS © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 The Interference Pattern Technique and the SMIGOL-Reflectometer are able to monitor the snow thickness variations. The retrieval algorithm developed is based on the position of notches, plus a tracking function that daily analyzes the movement of that notches in the received power plots. The correlation values of the measurements with the ground-truth in different points of the surface show that the technique can monitor changes in the snow thickness. (13/14) SNOW MONITORING USING GNSS-R TECHNIQUES

15. This work has been sponsored with funds from the Plan Nacional del Espacio of the Spanish Ministry in the frame of the project with reference ESP2007-65567-C04-02 and also by funds from the project with reference AYA2008-05906-C02-01/ESP and the project AYA2010-22062-C05-05/ESP. ACKNOWLEDGEMENTS (14/14) © R.S. Lab, UPC 2011. IGARSS 2011, Vancouver, Canada, 24 th -29 th July 2011 SNOW MONITORING USING GNSS-R TECHNIQUES

16. THANK YOU