• 14:40 Exploring the validity range of the polarimetric two-scale two-component model for soil moisture retrieval by using AGRISAR data

  Di Martino, Gerardo (1); Iodice, Antonio (1); Natale, Antonio (2); Riccio, Daniele (1); Ruello, Giuseppe (1) 1: Universita' degli Studi di Napoli Federico II, Napoli, Italy; 2: IREA - CNR, Napoli, Italy

  Show abstract

  In recent years considerable effort has been spent by the scientific community for research on soil moisture retrieval from multi-angle, -frequency or -polarization Synthetic Aperture Radar (SAR) data [1]. In particular, to this aim we proposed a Polarimetric Two-Scale Model (PTSM) [2-3] able to predict the second order statistics of the scattering matrix relevant to bare soils. Based on this model, we developed a retrieval algorithm able to get both soil moisture and ground roughness exploiting measured co-pol and cross-pol ratios [2], or the co-pol ratio and the HH-VV correlation coefficient [3]. Then, in order to account for the presence of a moderate vegetation, we inserted the PTSM in a two-component scattering model, so obtaining a polarimetric two-scale two-component model (PTSTCM); based on it, we developed a modified retrieval algorithm able to remove the (secondary) volume scattering contribution [4,5]. In particular, we used the PTSM to describe the surface scattering component, and a randomly oriented thin dipole model [6] to describe the volume scattering contribution from the vegetation layer which covers the scattering surface. We have shown that suitable combinations of the NRCS and HH-VV correlation, that we term "modified co-polarized ratio" and "modified HH-VV correlation coefficient", are related only to the surface parameters, because volumetric contribution cancels out. This in principle allows us obtaining a reasonable estimation of the soil moisture even in moderately vegetated areas, where the volumetric scattering contribution is non-negligible. In the present work, we first of all extend the employed volume scattering model by using not only a uniform distribution of dipole orientation, as in [4,5], but also a prevalently vertical or prevalently horizontal distribution. In addition, we test the PTSTCM by applying it to polarimetric SAR data acquired on areas for which, at the same times of SAR acquisitions, ground measurements of soil moisture were performed. In particular, we employ the huge AGRISAR [7] database, which includes data from several fields covering a period that spans all the phases of vegetation growth. Results of PTSTCM are also compared with those of available three-component methods (3CMs) [8,9] employing more simplified surface scattering models. A complete description and discussion of results will be provided at the conference; here, by summarising and simplifying the discussion, we can state that obtained results confirm that use of PTSTCM is more convenient for low vegetation, due to the fact that surface scattering is better modelled; that results of PTSTCM and 3CMs are similar for intermediate vegetation, because the surface component is still dominant, but its importance decreases and double bounce (ignored by PTSTCM) starts playing a role; and, finally, that 3CMs are more convenient for high vegetation, because the advantage of the more refined surface scattering model of PTSTCM is of little importance in this case, whereas it is necessary to account for double scattering. REFERENCES [1] K.C. Kornelsen, P. Coulibaly, "Advances in soil moisture retrieval from Synthetic Aperture Radar and hydrological applications", Journal of Hydrology, 476, pp. 460-489, Nov. 2012. [2] A. Iodice, A. Natale, D. Riccio, "Retrieval of Soil Surface Parameters via a Polarimetric Two-Scale Model", IEEE Trans. Geosci. Remote Sens., Vol. 49, no. 7, pp. 2531-2547, July 2011. [3] A. Iodice, A. Natale, D. Riccio, "Polarimetric Two-Scale Model for Soil Moisture Retrieval via Dual-Pol HH-VV SAR Data", IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. vol. 11, no. 3, pp. 1163-1171, June 2013. [4] A. Iodice, A. Natale, D. Riccio, "Soil moisture retrieval via a Polarimetric Two-Scale and Two-Component scattering model", Proceedings of PolInSAR 2013, Frascati, Italy, 2013. [5] A. Iodice, A. Natale, D. Riccio, "Soil moisture retrieval in moderately vegetated areas via a Polarimetric Two-Scale Model", Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, pp. 759-762, Melbourne, Australia, 21-26 July 2013. [6] A. Freeman and S. L. Durden, "A three-component scattering model for polarimetric SAR data", IEEE Trans. Geosci. Remote Sens., vol. 36, no. 3, pp. 963-973, May 1998. [7] "AGRISAR 2006 Agricultural Bio-/Geophysical Retrievals from Frequent Repeat SAR and Optical Imaging", Final Report, Jan. 2008. [8] I. Hajnsek, T. Jagdhuber,H. Schön, K. P. Papathanassiou,” Potential of estimating soil moisture under vegetation cover by means of PolSAR”, IEEE Trans. Geosci. Remote Sens., vol.47, no.2, pp. 442-454, February 2009. [9] T. Jagdhuber, "Soil Parameter Retrieval under Vegetation Cover Using SAR Polarimetry", Ph.D. Dissertation, 2012. Available online at http://opus.kobv.de/ubp/volltexte/2012/6051/

  
   

• 15:20 Time Series Analysis of Hybrid Polarimetric RISAT-1 Data for Soil Moisture Estimation

  Gramini Ganesan, Ponnurangam (1,3); Jagdhuber, Thomas (1); Hajnsek, Irena (1,2); Y. S., Rao (3) 1: German Aerospace Center (DLR), Germany; 2: ETH Zurich,Switzerland; 3: Indian Institute of Technology Bombay, India

  Show abstract

  Hybrid polarimetry gains strongly in interest within the SAR community due to the availability of first hybrid polarimetric data for earth observation from the Indian RISAT-1 satellite. Hybrid Polarimetric SAR (PolSAR) has many advantages in terms of PRF, swath width and data rate compared to fully PolSAR. It has already been shown in [1] that hybrid PolSAR data are capable of preserving important polarimetric information inferior to that of fully PolSAR, but superior to classical dual-linear PolSAR. Hence, there is a need to assess the potential of hybrid PolSAR to extract geo-physical parameters. In this paper, the capabilities of hybrid PolSAR are investigated to estimate soil moisture on bare and vegetation covered soils in agriculture. Therefore, a methodology, based on a model-based compact polarimetric decomposition together with a surface component inversion is under development to retrieve surface soil moisture from hybrid polarimetric SAR data [2]. The model-based compact decomposition technique is used to obtain the surface scattering component under the assumption of a randomly oriented vegetation volume. After vegetation removal, the surface scattering component is inverted for soil moisture by comparing it with a rank-1surface scattering component described by the IEM. The developed methodology is based on a two-layer (Random-Volume-over-Ground) scattering model for agriculture. Hence, the inversion results comprise both bare and vegetated soils. The developed algorithm is applied on a time series of hybrid polarimetric C-band RISAT-1 RCTLR (Right Circular Transmit Linear Receive) data from the Wallerfing test site in Lower Bavaria, Germany. The time-series data have been acquired from April to August 2014 (each month one acquisition) including the entire vegetation growth period. All the time-series data were acquired at various incidence angles in Fine Resolution StripMap-1 (FRS-1) mode, which has a spatial resolution of 3 m x 2 m (azimuth x range). Intensive ground measurements of soil and vegetation parameters for four different agriculture crop types (corn, cucumber, sugar beet and wheat) were collected synchronous with the satellite overpasses. In order to analyze the effect of soil roughness on the developed inversion algorithm, surface roughness has been additionally measured on the agriculture fields for the bare soil acquisition in April. During SAR data processing, the data were radiometrically calibrated. Afterwards, the developed compact polarimetric decomposition technique was applied and the surface component is extracted from the hybrid polarimetric RISAT-1 data. In order to invert soil moisture, the surface scattering component is modeled using the IEM for various dielectric constants of the soil and the corresponding incidence angle. The dielectric constant of the soil is then inverted by comparing the estimated and the modeled surface scattering component through a minimization procedure. Finally, the inverted dielectric constant is converted into soil moisture using the Topp model. In a final step, the estimated soil moisture from hybrid PolSAR is validated with ground measured soil moisture for a quality assessment. The estimated soil moisture shows an RMS error of less than 5 vol% for rough and smooth bare soils. For vegetated soils, the effect of incidence angle and vegetation cover on soil moisture inversion was analyzed for each acquisition. For all crops and all dates, an overall RMS error from 5.7 vol% to 6.6 vol% is achieved for medium incident angle ranges and at higher incident angle, an RMS error from 7.7 vol% to 10.2 vol% is obtained. The times series analysis of hybrid PolSAR data demonstrated the feasibility of retrieving soil moisture even in vegetation cover at medium incidence angle. [1] Cloude, S. R., Goodenough, D. G., and Chen, H (2012), Compact decomposition theory. IEEE Geoscience and Remote Sensing Letters, vol. 9, 1, pp. 28-32. [2] Ponnurangam, G. G., Jagdhuber, T., Hajnsek, I., and Rao, Y.S. (2014), Soil moisture inversion using hybrid polarimetric RISAT-1 data. Proceedings of 10th European Conference on Synthetic Aperture Radar (EUSAR’2014), June 3-5, Berlin, pp.1–4.

  
   

• 15:00 Interferometric phase based soil moisture change detection using dual pol SAR data

  Yin, Qiang (1,2,3); Hong, Wen (2); Li, Yang (2,3); Huang, Pingping (4) 1: ESRIN, European Space Agency; 2: Institute of Electronics, Chinese Academy of Sciences, China, People's Republic of; 3: University of Chinese Academy of Sciences; 4: Inner Mongolia University of Technology

  Show abstract

  Soil moisture is the key parameter of hydrology, climate and ecology models, and plays important role on drought monitoring, yield estimation of crops and so on. Synthetic aperture radar (SAR) data has been successfully employed in the soil moisture estimation for years, because of its high resolution compared to the passive microwave remote sensing approach. However, most of the research done has focused on the utilization of amplitude information of SAR data or multi-polarization SAR data, for which the estimation results are not stable, mainly because they are interfered by the roughness and topography. In the other hand, the phase information contained in microwave data hasn’t been fully utilized. To analysis the soil moisture change from differential interferometric SAR data (DInSAR) is a recently developed technique. Compared to the conventional water content estimation methods employing amplitude information of SAR data, this kind of technique has its particular advantages, respectively the separation of roughness effects, the stability with existed topography, and high phase accuracy with low calibration requirement on the data amplitude. In addition, the scattering modelling on the relation between interferometric phase and dielectric constant of soil is further promising in its capability to analyse the influences and sensitivity of the system parameters on the soil moisture inversion. However, multi-temporal data is necessary for differential processing in order to eliminate the topographic phase item. In absence of DInSAR data, the alternative is the use of high accuracy DEM data, which is always not available as well. In this paper we propose a method for soil moisture change detection using interferometric phase information of dual pol SAR data. Because the different phase sensitivity of polarimetric channel on the soil moisture change, it is possible to invert the latter by introducing polarimetric SAR data information into the coherent scattering model. In this way, the topography induced phase could be eliminated. Simulations are presented to show the range of soil moisture changes that can be inverted under the different conditions of system phase accuracy. Relevant experiment with Envisat ASAR data will be implemented, with comparison to the AgriSAR campaign ground truth measurement. Considering the low coherence of 35 days interval interferogram, the coming Sentinel 1A data will be also utilized due to the data availability.

  
   

• 15:40 Round Table Discussion

  Show abstract

  Round Table Discussion

  
   

Highlights

In May 2013, the Biomass mission concept was selected to become the next in the series of satellites developed to further our understanding of Earth.

Released: 21/06/2013

REPLAY EARTH EXPLORER 7 USER CONSULTATION MEETING (PART 1)

Released: 11/03/2013

POLinSAR 2013 Workshop

Released: 22/02/2013