SOIL MOISTURE AND VEGETATION HEIGHT ... - Semantic Scholar
SOIL MOISTURE AND VEGETATION HEIGHT RETRIEVAL USING GNSS-R TECHNIQUES N. Rodriguez-Alvarez§, A. Monerris†§, X. Bosch-Lluis§, A. Camps§†, M. Vall-Llossera§ J. F. Marchan-Hernandez§ , ω ω ω I. Ramos-Perez§, E. Valencia§, J. Martínez-Fernández , N. Sánchez-Martín , G. Baroncini-Turricchia , C. Pérezω Gutiérrez §
Remote Sensing Lab, Dept. TSC, Building D3, Polytechnical University of Catalonia, Barcelona, Spain and IEEC CRAE/UPC † SMOS-Barcelona Expert Centre, Barcelona, Spain ω Centro Hispanoluso de Investigaciones Agrarias (CIALE), University of Salamanca, Salamanca, Spain Tel. +34+934017362, E-08034 Barcelona, Spain. E-mail: [email protected] ABSTRACT
Global Navigation Satellite Signals Reflections (GNSS-R) techniques are currently being used for remote sensing purposes retrieving geophysical parameters over different types of surfaces. Over the ocean, sea state information can be retrieved to improve the ocean salinity retrieval [1]. Furthermore, over land these techniques can be used to retrieve soil moisture [2]. This paper presents the theoretical and experimental results of using GNSS-R to retrieve soil moisture when vegetation is present. The particular technique being applied in this study is the Interference Pattern Technique (IPT) [3] that measures the interference pattern of the GPS direct and reflected signals, after reflecting over the surface. Index Terms— GNSS-R, Interferometric-pattern, Soil moisture, Vegetation, Growth, Retrieval
section 2 the SMIGOL Reflectometer is defined, in section 3 the fundamentals of the IPT for vegetation height and soil moisture retrievals are explained, in section 4 the experimental results in two field campaigns are presented and finally, in section 5 some conclusions are extracted. 2. THE SMIGOL REFLECTOMETER The Soil Moisture Interference-pattern GNSS Observations at L-band (SMIGOL) Reflectometer is the instrument implementing the IPT. An extended description of the instrument is available in the accompanying paper entitled Topography Retrieval Using GNSS-R Techniques. The SMIGOL Reflectometer, which works in the GPS frequency band (1.54752 GHz), measures the signals coming from the GPS satellites. The basic architecture is shown in Fig. 1.
1. INTRODUCTION Some previous studies have proven that the soil moisture of a bare soil surface can be retrieved using the IPT, [4]. In the present paper an improvement of the algorithms of this technique is implemented to achieve retrievals of soil moisture when vegetation is present, studying the effects and new features of the interferometric powers. In this process, the vegetation height is also inferred from the measurements. The present paper is structured as follows: in _____________________________________________________________ This work, conducted as part of the award “Passive Advanced Unit (PAU): A Hybrid L-band Radiometer, GNSS-Reflectometer and IR-Radiometer for Passive Remote Sensing of the Ocean” made under the European Heads of Research Councils and European Science Foundation EURYI (European Young Investigator) Awards scheme in 2004, was supported by funds from the Participating Organizations of EURYI and the EC Sixth Framework Program. Also by funds from the Plan Nacional del Espacio of the Spanish Ministry in the frame of the project with reference ESP2007-65567C04-02. And also by funds from the project with reference AYA2008-05906-C0201/ESP
Figure 1. The SMIGOL Reflectometer architecture.
As the SMIGOL Reflectometer points to the horizon, the resultant received signal is the interference between the direct GPS signal and the reflected GPS signal, after reflecting over the soil. These signals arrive to the antenna patch, within the same GPS chip interval, where they are coherently added. Then, the GPS receiver processes these signals and transmits to the PC the raw data. Using the SMIGOL retrieval algorithms, the different geophysical parameters are obtained. When a satellite is detected, the
receiver starts the acquisition of its interferometric signals during the satellite passage. Each time sample corresponds to the elevation angle value of the GPS satellite position, so at the end it can be observed the received power as a function of the elevation angle. 3. FUNDAMENTALS OF THE INTERFERENCE PATTERN TECHNIQUE In [4] it was probed that bare soil surface moisture can be retrieved using the IPT. In the accompanying paper The GPS and Radiometric Joint Observations Experiment at REMEDHUS SITE (Zamora-Salamanca Region, Spain, new results about this kind of retrieval are shown. Furthermore, in the accompanying paper Topography Retrieval Using GNSS-R Techniques, it is shown how this technique can retrieve the topographical profile of the surface. The retrieval applied in the present paper focuses on the soil moisture retrieval when soils are covered by vegetation, analyzing the effects of the vegetation height and the equivalent reflectivity of the soil + vegetation layer set. In order to consider the vegetation effects it is necessary to introduce an electromagnetic model capable to describe the behaviour of the reflected signals when they impinge over the ensemble surface + vegetation. A software package developed at the Universitat Politècnica de Catalunya, the Emisveg software [5], is used to compute all the interactions between the signal and the scenario elements (soil + vegetation). Originally, this tool was conceived to simulate the polarimetric emission of the vegetation at L-band and it is now used to model the scattering of the GPS signals in the ensemble soil + vegetation. The vegetation is modelled using L-systems and trunk, branches, leaves and fruits have their particular scattering models. As the experimental campaigns have been carried out over wheat fields, the Emisveg software has been configured to simulate this kind of fields, see fig. 2.
(a)
(a)
(b)
(c) (d) Figure 3. Theoretical simulations computed for 30 cm wheat height with (a) 0% and (b) 20 % soil surface moisture and for 50 cm wheat height with (c) 0% and (b) 20 % of soil surface moisture, for different soil surface roughness values.
On one hand, comparing Figs. 3a and 3b, or Figs. 3c and 3d, it can be deduced that soil surface moisture and soil surface roughness are not affecting to the position of the different notches, which are the minimum oscillations observed in the interferometric patterns. Observing Figs. 3a and 3.c, it can be seen that the number of notches is different, while Fig. 3a presents two notches, Fig. 3c presents four notches. This feature is related to the vegetation height and the multiple reflections that take place on it. On the other hand, comparing Figs. 3a and 3b, it can be seen that when soil moisture increases the amplitude of the oscillations increases, then the notches amplitude increases too. The theory for these two conclusions has been developed and is shown in Figs. 4 and 5.
(b)
Figure 2. Emisveg software products for wheat features. (a) Wheat plant and (b) wheat field within the antenna footprint.
A full set of simulations has been performed considering different vegetation heights, roughness, and soil moisture values, producing a wide range of reflectivities. These reflectivities have been added to the SMIGOL software, extending the algorithms for vegetation soil modelling. In Figure 3 simulations of the interferometric received powers considering different values of the vegetation height, soil moisture and roughness are shown.
Figure 4. Vegetation height as a function of the incidence angle where notches take place.
In Fig. 4 it is shown how when vegetation height increases the notch positions moves to the left and also other notches appear. Based on this result an algorithm for the retrieval of the vegetation height has been implemented; the notches positions of the SMIGOL Reflectometer measurements are selected and the vegetation height is computed by inspection of the relations in Fig. 4. Knowing the vegetation height, the algorithm for the soil moisture retrieval is applied (Fig. 5).
Notches are found in the received interferometric powers and, then, the height values are computed by using the relations in Fig. 5.
(a)
(b)
(c) (d) Figure 5. Notches amplitudes as a function of the soil moisture content of the surface, for different values of the vegetation height.
The algorithm proceeds computing the amplitude of each notch in the SMIGOL measurements and then, using the relations in fig. 5, the soil moisture is inferred. 4. EXPERIMENTAL RESULTS The experimental measurements carried out in two field campaigns to prove the theoretical model developed are now presented. The SMIGOL Reflectometer was first deployed in PALAU field campaign over a wheat field since February to October 2008, in Palau d’Anglesola (Lleida, Spain), covering different growth stages of the wheat, from no vegetation up to 60 cm vegetation height, including the dry up process of the wheat, fig. 6.
All satellites available have been processed in terms of vegetation height for four different days: 11th of March, 19th of April, 26th of May and 16th of June. The results have been compared to the ground-truth measured in situ during the field campaign, Fig. 8.
Figure 8. Wheat growing during the field campaign, height retrievals achieved for 11th of March, 19th of April, 26th of May and 16th of June with different satellites and mean values of these retrievals.
As it can be observed in Fig. 8, the mean values of the retrievals agree reasonably well with the randomly selected plants used to obtain the ground-truth. There is certain dispersion in the retrieved heights, but it must be taken into account that the wheat plants don’t have a homogeneous height and each notch corresponds to a different part of the field. Knowing the vegetation height, the soil moisture retrieval algorithm can be applied to the different satellites in order to achieve a soil moisture map. In Fig. 9, it is shown the soil moisture map achieved for the day 11th of March, DoY=71. SMIGOL ECH2O soil Reflectometer moisture probes
(a) (b) (c) (d) Figure 6. The different growth stages of the wheat: (a) 23rd February, 2008, 10 cm (b) 25th April, 2008, 46 cm (c)12th June, 2008, 55 cm and (d) 25th June, 2008, 57 cm.
The vegetation height retrieval works as shows Fig. 7.
30.63 cm
Figure 9. Soil moisture map achieved after applying the soil moisture retrieval algorithm in presence of vegetation, map scale = 13m.
In figure 10, the ground-truth for the 11th of March, DoY=71, is presented.
23.98 cm
Figure 7. Vegetation height information obtained from the measured interference power fro satellite 15 on 11th of March, 2008.
Figure 10. Ground-truth for the soil moisture of the ECH2O probes, from 11th of March (DoY=71) to 17th of March (DoY=78).
In order to validate these results, the SMIGOL Reflectometer was placed at Vadillo de la Guareña, where the GRAJO campaign takes place. The GRAJO, GPS and Radiometric Joint Observations, field campign consists in a radiometer, LAURA [6], and a reflectometer, SMIGOL, measuring the wheat to extract jointly conclusions, see the The GPS and RAdiometric Joint Observations Experiment at REMEDHUS SITE (Zamora-Salamanca Region, Spain, companion paper. This campaign started in November 2009 and SMIGOL has been also measuring the wheat field, covering the different growth stages of the wheat. Four days have been selected to carry out a similar study as in PALAU campaign: 22nd of March, 4th of April, 18th of April and 1st of May. The ground-truth has been provided by the CIALE, University of Salamanca. Figure 11 shows the results for the vegetation height retrieval.
Ground-truth
SMIGOL Reflectometer
Ground-truth
SMIGOL Reflectometer
(a) (b) Figure 13. Soil moisture maps retrieved by SMIGOL at GRAJO campaign in presence of vegetation for (a) 18th of April (DoY=108) and (b) 1st of May (DoY=121), maps scale 27m.
Figures 14a and 14b shows the ground-truth provided by CIALE, University of Salamanca, for the 18th of April (DoY=108) and the 1st of May (DoY=121).
(a) (b) Figure 14. Ground-truth of the soil moisture provided by CIALE and University of Salamanca team for DoY=108 and DoY=121. Figure 11. Wheat growing during the field campaign, height retrievals achieved for 22nd of March, 4th of April, 18th of April and 1st of May with different satellites and mean values of these retrievals.
As it can be seen results are very similar to the PALAU campaign and there is a good agreement between mean values of the retrievals and the measured height of the plants. Taking these results, the soil moisture algorithms have been applied to the measures of the SMIGOL reflectometer. In figure 12 it can be observed the retrieval for satellite 23 on 1st of May.
Figure 12. Measured and retrieved interference power for satellite 23 on DoY=121.
As it can be seen the retrieved power is very similar to the measured one. So it is concluded that algorithms are properly working. In Figs. 13a and 13b, two soil moisture maps have been processed in presence of vegetation.
5. CONCLUSIONS Based on the result of the two field campaigns, PALAU and GRAJO, it can be concluded that the IPT, in combination with the new algorithms, provides satisfactory results on the vegetation height retrievals and also on the soil moisture retrievals when vegetations is present. 6. REFERENCES [1] J.F. Marchan-Hernandez, N. Rodríguez-Álvarez, A. Camps, X. BoschLluis, and I. Ramos-Perez, “Correction of the Sea State Impact in the L-band Brightness Temperature by Means of Delay-Doppler Maps of Global Navigation Satellite Signals Reflected over the Sea Surface,” IEEE Transactions on Geoscience and Remote Sensing, , vol. 46, issue. 10, part 1, pp. 2914 - 2923, October 2007. [2] D. Masters, V. Zavorotny, S. Katzberg and W. Emery, “GPS signal scattering from land for moisture content determination,” Proceedings of the Internacional Geoscience and Remote Sensing Symposium 2000, vol.7 pp. 30903092, Honolulu, USA. [3] A. Kavak, W.J. Vogel, and G. Xu, “Using GPS to measure ground complex permittivity”, Electronic Letters, vol. 34, no.3, pp. 254-255, February 1998 [4] N. Rodriguez-Alvarez, J.F. Marchan, A. Camps, E. Valencia, X. BoschLluis, I. Ramos-Pérez, J.M. Nieto, “Soil Moisture Retrieval Using GNSS-R Techniques: Measurement Campaign in a Wheat Field,” Proceedings of IEEE International Geoscience and Remote Sensing Symposium 2008, vol. 2, issue. 2, pp. 245-248, from July 7 to July 11, 2008, Boston, USA. [5] Martinez-Vazquez, A.; Camps, A.; Duffo, N.; Vall-Ilossera, M.; LopezSanchez, J.M.; “Full polarimetric emissivity of vegetation-covered soils: vegetation structure effects”, Proceedings of the Internacional Geoscience and Remote Sensing Symposium 2002, vol.6, pp. 3542-3544, 24-28 June 2002, IGARSS 2002. [6] A. Camps, J. Font, M. Vall-llossera, C. Gabarr´o, I. Corbella, et al., “The WISE 2000 and 2001 field experiments in support of the SMOS mission: sea surface L-band brightness temperature observations and their application to sea surface salinity retrieval," IEEE Tansactions on Geoscience and Remote Sensing, vol. 42, no. 4, pp. 804-823, April 2004.
Remote Sensing Lab, Dept. TSC, Building D3, Polytechnical University of Catalonia, Barcelona, Spain and IEEC CRAE/UPC † SMOS-Barcelona Expert Centre, Barcelona, Spain ω Centro Hispanoluso de Investigaciones Agrarias (CIALE), University of Salamanca, Salamanca, Spain Tel. +34+934017362, E-08034 Barcelona, Spain. E-mail: [email protected] ABSTRACT
Global Navigation Satellite Signals Reflections (GNSS-R) techniques are currently being used for remote sensing purposes retrieving geophysical parameters over different types of surfaces. Over the ocean, sea state information can be retrieved to improve the ocean salinity retrieval [1]. Furthermore, over land these techniques can be used to retrieve soil moisture [2]. This paper presents the theoretical and experimental results of using GNSS-R to retrieve soil moisture when vegetation is present. The particular technique being applied in this study is the Interference Pattern Technique (IPT) [3] that measures the interference pattern of the GPS direct and reflected signals, after reflecting over the surface. Index Terms— GNSS-R, Interferometric-pattern, Soil moisture, Vegetation, Growth, Retrieval
section 2 the SMIGOL Reflectometer is defined, in section 3 the fundamentals of the IPT for vegetation height and soil moisture retrievals are explained, in section 4 the experimental results in two field campaigns are presented and finally, in section 5 some conclusions are extracted. 2. THE SMIGOL REFLECTOMETER The Soil Moisture Interference-pattern GNSS Observations at L-band (SMIGOL) Reflectometer is the instrument implementing the IPT. An extended description of the instrument is available in the accompanying paper entitled Topography Retrieval Using GNSS-R Techniques. The SMIGOL Reflectometer, which works in the GPS frequency band (1.54752 GHz), measures the signals coming from the GPS satellites. The basic architecture is shown in Fig. 1.
1. INTRODUCTION Some previous studies have proven that the soil moisture of a bare soil surface can be retrieved using the IPT, [4]. In the present paper an improvement of the algorithms of this technique is implemented to achieve retrievals of soil moisture when vegetation is present, studying the effects and new features of the interferometric powers. In this process, the vegetation height is also inferred from the measurements. The present paper is structured as follows: in _____________________________________________________________ This work, conducted as part of the award “Passive Advanced Unit (PAU): A Hybrid L-band Radiometer, GNSS-Reflectometer and IR-Radiometer for Passive Remote Sensing of the Ocean” made under the European Heads of Research Councils and European Science Foundation EURYI (European Young Investigator) Awards scheme in 2004, was supported by funds from the Participating Organizations of EURYI and the EC Sixth Framework Program. Also by funds from the Plan Nacional del Espacio of the Spanish Ministry in the frame of the project with reference ESP2007-65567C04-02. And also by funds from the project with reference AYA2008-05906-C0201/ESP
Figure 1. The SMIGOL Reflectometer architecture.
As the SMIGOL Reflectometer points to the horizon, the resultant received signal is the interference between the direct GPS signal and the reflected GPS signal, after reflecting over the soil. These signals arrive to the antenna patch, within the same GPS chip interval, where they are coherently added. Then, the GPS receiver processes these signals and transmits to the PC the raw data. Using the SMIGOL retrieval algorithms, the different geophysical parameters are obtained. When a satellite is detected, the
receiver starts the acquisition of its interferometric signals during the satellite passage. Each time sample corresponds to the elevation angle value of the GPS satellite position, so at the end it can be observed the received power as a function of the elevation angle. 3. FUNDAMENTALS OF THE INTERFERENCE PATTERN TECHNIQUE In [4] it was probed that bare soil surface moisture can be retrieved using the IPT. In the accompanying paper The GPS and Radiometric Joint Observations Experiment at REMEDHUS SITE (Zamora-Salamanca Region, Spain, new results about this kind of retrieval are shown. Furthermore, in the accompanying paper Topography Retrieval Using GNSS-R Techniques, it is shown how this technique can retrieve the topographical profile of the surface. The retrieval applied in the present paper focuses on the soil moisture retrieval when soils are covered by vegetation, analyzing the effects of the vegetation height and the equivalent reflectivity of the soil + vegetation layer set. In order to consider the vegetation effects it is necessary to introduce an electromagnetic model capable to describe the behaviour of the reflected signals when they impinge over the ensemble surface + vegetation. A software package developed at the Universitat Politècnica de Catalunya, the Emisveg software [5], is used to compute all the interactions between the signal and the scenario elements (soil + vegetation). Originally, this tool was conceived to simulate the polarimetric emission of the vegetation at L-band and it is now used to model the scattering of the GPS signals in the ensemble soil + vegetation. The vegetation is modelled using L-systems and trunk, branches, leaves and fruits have their particular scattering models. As the experimental campaigns have been carried out over wheat fields, the Emisveg software has been configured to simulate this kind of fields, see fig. 2.
(a)
(a)
(b)
(c) (d) Figure 3. Theoretical simulations computed for 30 cm wheat height with (a) 0% and (b) 20 % soil surface moisture and for 50 cm wheat height with (c) 0% and (b) 20 % of soil surface moisture, for different soil surface roughness values.
On one hand, comparing Figs. 3a and 3b, or Figs. 3c and 3d, it can be deduced that soil surface moisture and soil surface roughness are not affecting to the position of the different notches, which are the minimum oscillations observed in the interferometric patterns. Observing Figs. 3a and 3.c, it can be seen that the number of notches is different, while Fig. 3a presents two notches, Fig. 3c presents four notches. This feature is related to the vegetation height and the multiple reflections that take place on it. On the other hand, comparing Figs. 3a and 3b, it can be seen that when soil moisture increases the amplitude of the oscillations increases, then the notches amplitude increases too. The theory for these two conclusions has been developed and is shown in Figs. 4 and 5.
(b)
Figure 2. Emisveg software products for wheat features. (a) Wheat plant and (b) wheat field within the antenna footprint.
A full set of simulations has been performed considering different vegetation heights, roughness, and soil moisture values, producing a wide range of reflectivities. These reflectivities have been added to the SMIGOL software, extending the algorithms for vegetation soil modelling. In Figure 3 simulations of the interferometric received powers considering different values of the vegetation height, soil moisture and roughness are shown.
Figure 4. Vegetation height as a function of the incidence angle where notches take place.
In Fig. 4 it is shown how when vegetation height increases the notch positions moves to the left and also other notches appear. Based on this result an algorithm for the retrieval of the vegetation height has been implemented; the notches positions of the SMIGOL Reflectometer measurements are selected and the vegetation height is computed by inspection of the relations in Fig. 4. Knowing the vegetation height, the algorithm for the soil moisture retrieval is applied (Fig. 5).
Notches are found in the received interferometric powers and, then, the height values are computed by using the relations in Fig. 5.
(a)
(b)
(c) (d) Figure 5. Notches amplitudes as a function of the soil moisture content of the surface, for different values of the vegetation height.
The algorithm proceeds computing the amplitude of each notch in the SMIGOL measurements and then, using the relations in fig. 5, the soil moisture is inferred. 4. EXPERIMENTAL RESULTS The experimental measurements carried out in two field campaigns to prove the theoretical model developed are now presented. The SMIGOL Reflectometer was first deployed in PALAU field campaign over a wheat field since February to October 2008, in Palau d’Anglesola (Lleida, Spain), covering different growth stages of the wheat, from no vegetation up to 60 cm vegetation height, including the dry up process of the wheat, fig. 6.
All satellites available have been processed in terms of vegetation height for four different days: 11th of March, 19th of April, 26th of May and 16th of June. The results have been compared to the ground-truth measured in situ during the field campaign, Fig. 8.
Figure 8. Wheat growing during the field campaign, height retrievals achieved for 11th of March, 19th of April, 26th of May and 16th of June with different satellites and mean values of these retrievals.
As it can be observed in Fig. 8, the mean values of the retrievals agree reasonably well with the randomly selected plants used to obtain the ground-truth. There is certain dispersion in the retrieved heights, but it must be taken into account that the wheat plants don’t have a homogeneous height and each notch corresponds to a different part of the field. Knowing the vegetation height, the soil moisture retrieval algorithm can be applied to the different satellites in order to achieve a soil moisture map. In Fig. 9, it is shown the soil moisture map achieved for the day 11th of March, DoY=71. SMIGOL ECH2O soil Reflectometer moisture probes
(a) (b) (c) (d) Figure 6. The different growth stages of the wheat: (a) 23rd February, 2008, 10 cm (b) 25th April, 2008, 46 cm (c)12th June, 2008, 55 cm and (d) 25th June, 2008, 57 cm.
The vegetation height retrieval works as shows Fig. 7.
30.63 cm
Figure 9. Soil moisture map achieved after applying the soil moisture retrieval algorithm in presence of vegetation, map scale = 13m.
In figure 10, the ground-truth for the 11th of March, DoY=71, is presented.
23.98 cm
Figure 7. Vegetation height information obtained from the measured interference power fro satellite 15 on 11th of March, 2008.
Figure 10. Ground-truth for the soil moisture of the ECH2O probes, from 11th of March (DoY=71) to 17th of March (DoY=78).
In order to validate these results, the SMIGOL Reflectometer was placed at Vadillo de la Guareña, where the GRAJO campaign takes place. The GRAJO, GPS and Radiometric Joint Observations, field campign consists in a radiometer, LAURA [6], and a reflectometer, SMIGOL, measuring the wheat to extract jointly conclusions, see the The GPS and RAdiometric Joint Observations Experiment at REMEDHUS SITE (Zamora-Salamanca Region, Spain, companion paper. This campaign started in November 2009 and SMIGOL has been also measuring the wheat field, covering the different growth stages of the wheat. Four days have been selected to carry out a similar study as in PALAU campaign: 22nd of March, 4th of April, 18th of April and 1st of May. The ground-truth has been provided by the CIALE, University of Salamanca. Figure 11 shows the results for the vegetation height retrieval.
Ground-truth
SMIGOL Reflectometer
Ground-truth
SMIGOL Reflectometer
(a) (b) Figure 13. Soil moisture maps retrieved by SMIGOL at GRAJO campaign in presence of vegetation for (a) 18th of April (DoY=108) and (b) 1st of May (DoY=121), maps scale 27m.
Figures 14a and 14b shows the ground-truth provided by CIALE, University of Salamanca, for the 18th of April (DoY=108) and the 1st of May (DoY=121).
(a) (b) Figure 14. Ground-truth of the soil moisture provided by CIALE and University of Salamanca team for DoY=108 and DoY=121. Figure 11. Wheat growing during the field campaign, height retrievals achieved for 22nd of March, 4th of April, 18th of April and 1st of May with different satellites and mean values of these retrievals.
As it can be seen results are very similar to the PALAU campaign and there is a good agreement between mean values of the retrievals and the measured height of the plants. Taking these results, the soil moisture algorithms have been applied to the measures of the SMIGOL reflectometer. In figure 12 it can be observed the retrieval for satellite 23 on 1st of May.
Figure 12. Measured and retrieved interference power for satellite 23 on DoY=121.
As it can be seen the retrieved power is very similar to the measured one. So it is concluded that algorithms are properly working. In Figs. 13a and 13b, two soil moisture maps have been processed in presence of vegetation.
5. CONCLUSIONS Based on the result of the two field campaigns, PALAU and GRAJO, it can be concluded that the IPT, in combination with the new algorithms, provides satisfactory results on the vegetation height retrievals and also on the soil moisture retrievals when vegetations is present. 6. REFERENCES [1] J.F. Marchan-Hernandez, N. Rodríguez-Álvarez, A. Camps, X. BoschLluis, and I. Ramos-Perez, “Correction of the Sea State Impact in the L-band Brightness Temperature by Means of Delay-Doppler Maps of Global Navigation Satellite Signals Reflected over the Sea Surface,” IEEE Transactions on Geoscience and Remote Sensing, , vol. 46, issue. 10, part 1, pp. 2914 - 2923, October 2007. [2] D. Masters, V. Zavorotny, S. Katzberg and W. Emery, “GPS signal scattering from land for moisture content determination,” Proceedings of the Internacional Geoscience and Remote Sensing Symposium 2000, vol.7 pp. 30903092, Honolulu, USA. [3] A. Kavak, W.J. Vogel, and G. Xu, “Using GPS to measure ground complex permittivity”, Electronic Letters, vol. 34, no.3, pp. 254-255, February 1998 [4] N. Rodriguez-Alvarez, J.F. Marchan, A. Camps, E. Valencia, X. BoschLluis, I. Ramos-Pérez, J.M. Nieto, “Soil Moisture Retrieval Using GNSS-R Techniques: Measurement Campaign in a Wheat Field,” Proceedings of IEEE International Geoscience and Remote Sensing Symposium 2008, vol. 2, issue. 2, pp. 245-248, from July 7 to July 11, 2008, Boston, USA. [5] Martinez-Vazquez, A.; Camps, A.; Duffo, N.; Vall-Ilossera, M.; LopezSanchez, J.M.; “Full polarimetric emissivity of vegetation-covered soils: vegetation structure effects”, Proceedings of the Internacional Geoscience and Remote Sensing Symposium 2002, vol.6, pp. 3542-3544, 24-28 June 2002, IGARSS 2002. [6] A. Camps, J. Font, M. Vall-llossera, C. Gabarr´o, I. Corbella, et al., “The WISE 2000 and 2001 field experiments in support of the SMOS mission: sea surface L-band brightness temperature observations and their application to sea surface salinity retrieval," IEEE Tansactions on Geoscience and Remote Sensing, vol. 42, no. 4, pp. 804-823, April 2004.
