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IEEE International Geoscience & Remote Sensing Symposium

作者： Paloscia, S. Pettinato, S. Santi, E. Notarnicola, C. Greifeneder, F. Cuozzo, G. IFAC CNR Florence Italy EURAC Bolzano Italy

ISBN: (纸本)9781509049516

This research aims at analyzing the integration of C and X band data collected from Radarsat2 (RS2) and COSMO-SkyMed (CSK) systems on two Italian test areas, located in South-Tyrol and in Tuscany, close to Florence, to estimate soil moisture (SMC, in %) and vegetation biomass (PWC, in kg/m(2)). Two retrieval approaches based on Support Vector Regression (SVR) and Artificial Neural Network (ANN) have been applied to these areas. Looking at the preliminary results, it has been noted that the integration of X and C band images could provide valuable information for the retrieval of SMC, even though further investigations should be carried out on a larger time-series and set of samples. On the South Tyrol test area, SVR methods provided an accuracy in the estimate of SMC with determination coefficient, R-2> 0.85 and root mean square error, RMSE.<= 4%. By using X band alone, the result obtained is worse: ANN algorithm resulted in R2 from 0.35 to 0.8 and RMSE from 6 to 2 (% SMC), depending on the polarization combinations considered as input. X band allowed instead retrieving the PWC of cereal fields with a satisfactory accuracy (R-2=0.94 and RMSE=0.35 Kg/m(2)).

关键词： Cosmo-SkyMed Radarsat2 agricultural areas soil moisture retrieval inversion algorithms

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Requirements for accurate estimation of anisotropic material parameters by magnetic resonance elastography: A computational study

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MAGNETIC RESONANCE IN MEDICINE 2017年第6期78卷 2360-2372页

作者： Tweten, D. J. Okamoto, R. J. Bayly, P. V. Washington Univ Mech Engn & Mat Sci 1 Brookings Dr St Louis MO 63105 USA Washington Univ Biomed Engn St Louis MO USA

PurposeTo establish the essential requirements for characterization of a transversely isotropic material by magnetic resonance elastography (MRE). Theory and MethodsThree methods for characterizing nearly incompressible, transversely isotropic (ITI) materials were used to analyze data from closed-form expressions for traveling waves, finite-element (FE) simulations of waves in homogeneous ITI material, and FE simulations of waves in heterogeneous material. Key properties are the complex shear modulus (2), shear anisotropy =1/2-1, and tensile anisotropy =E1/E2-1. ResultsEach method provided good estimates of ITI parameters when both slow and fast shear waves with multiple propagation directions were present. No method gave accurate estimates when the displacement field contained only slow shear waves, only fast shear waves, or waves with only a single propagation direction. Methods based on directional filtering are robust to noise and include explicit checks of propagation and polarization. Curl-based methods led to more accurate estimates in low noise conditions. Parameter estimation in heterogeneous materials is challenging for all methods. ConclusionsMultiple shear waves, both slow and fast, with different propagation directions, must be present in the displacement field for accurate parameter estimates in ITI materials. Experimental design and data analysis can ensure that these requirements are met. Magn Reson Med 78:2360-2372, 2017. (c) 2017 International Society for Magnetic Resonance in Medicine.

关键词： MR elastography anisotropy transversely isotropic material shear waves inversion algorithms heterogeneity

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Semi-empirical inversion technique for retrieval of quantitative attenuation profiles with underwater scanning LiDAR system 7

Semi-empirical inversion technique for retrieval of quantita...

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Conference on Ocean Sensing and Monitoring VII

作者： Vuorenkoski, Anni K. Dalgleish, Fraser R. Twardowski, Michael S. Ouyang, Bing Trees, Charles C. Florida Atlantic Univ Harbor Branch Oceanog Inst Ft Pierce FL 34946 USA WET Labs Inc Narragansett RI 02882 USA STO NATO CMRE La Spezia Italy

ISBN: (纸本)9781628415759

A fine structure underwater imaging LiDAR (FSUIL) has recently been developed and initial field trials have been conducted. The instrument, which rapidly scans an array of closely spaced, narrow, collimated laser pulses into the water column produces two-dimensional arrays of backscatter profiles, with fine spatial and temporal resolution. In this paper a novel method to derive attenuation profiles is introduced. This approach is particularly attractive in applications where primary on-board processing is required, and other applications where conventional model-based approaches are not feasible due to a limited computational capacity or lack of a priori knowledge of model input parameters. The paper also includes design details regarding the new FSUIL instrument are given, with field results taken in clear to moderately turbid water being presented to illustrate the various effects and considerations in the analysis of the system data. LiDAR waveforms and LiDAR derived attenuation coefficients are analyzed and compared to calibrated beam attenuation, particulate scattering and absorption coefficients. The system was field tested during the NATO Ligurian Sea LIDAR & Optical Measurements Experiment (LLOMEx) cruise in March 2013, during the spring bloom conditions. Throughout a wide range of environmental conditions, the FSUIL was deployed on an in situ profiler obtaining thousands of three-dimensional LiDAR scans from the near surface down to the lower thermocline. Deployed concurrent to the FSUIL was a range of commercially available off-the-shelf instruments providing side-by-side in-situ attenuation measurement.

关键词： LiDAR multiple scattering attenuation profiles inversion algorithms

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Estimation of material parameters from slow and fast shear waves in an incompressible, transversely isotropic material

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JOURNAL OF BIOMECHANICS 2015年第15期48卷 4002-4009页

作者： Tweten, Dennis J. Okamoto, Ruth J. Schmidt, John L. Garbow, Joel R. Bayly, Philip V. Washington Univ Dept Mech Engn & Mat Sci St Louis MO 63130 USA Washington Univ Dept Radiol St Louis MO 63130 USA Washington Univ Dept Biomed Engn St Louis MO 63130 USA

This paper describes a method to estimate mechanical properties of soft, anisotropic materials from measurements of shear waves with specific polarization and propagation directions. This method is applicable to data from magnetic resonance elastography (MRE), which is a method for measuring shear waves in live subjects or in vitro samples. Here, we simulate MRE data using finite element analysis. A nearly incompressible, transversely isotropic (Ill) material model with three parameters (shear modulus, shear anisotropy, and tensile anisotropy) is used, which is appropriate for many fibrous, biological tissues. Both slow and fast shear waves travel concurrently through such a material with speeds that depend on the propagation direction relative to fiber orientation. A three-parameter estimation approach based on directional filtering and isolation of slow and fast shear wave components (directional filter inversion, or DFI) is introduced. Wave speeds of each isolated shear wave component are estimated using local frequency estimation (LFE), and material properties are calculated using weighted least squares. Data from multiple finite element simulations are used to assess the accuracy and reliability of DFI for estimation of anisotropic material parameters. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： MR elastography Shear waves Anisotropy Transversely isotropic material inversion algorithms

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COSMO-SkyMed and RADARSAT2 image investigation for the monitoring of agricultural areas 15

COSMO-SkyMed and RADARSAT2 image investigation for the monit...

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Conference on SAR Image Analysis, Modeling, and Techniques XV

作者： Paloscia, S. Pettinato, S. Santi, E. Notarnicola, C. Greifeneder, F. Cuozzo, G. Nicolini, I. Demir, B. Bruzzone, L. CNR IFAC I-50019 Florence Italy EURAC Bolzano Italy Univ Trento Trento Trento Italy

ISBN: (纸本)9781628418521

This research aims at investigating the backscatter sensitivity at C and X band to the characteristics of agricultural surfaces and analyzing the integration of these data collected from Radarsat2 (RS2) and COSMO-SkyMed (CSK) systems on tree agricultural test areas in Italy (San Pietro Capofiume, in Emilia Romagna, Sesto Fiorentino, in Tuscany, and Mazia Valley, in South Tyrol). A preliminary test of the sensitivity of SAR signal to the soil and vegetation characteristics was first carried out by also comparing data from previous experiments. From these results, it can be concluded that X-band data are mainly sensitive to vegetation structure and biomass, and to soil moisture of bare or slightly vegetate soils, whereas C-band images could provide valuable information for the retrieval of soil moisture, even in vegetation covered soils. Two retrieval algorithms were implemented for estimating the main geophysical parameters, namely soil moisture content (SMC) and vegetation biomass (PWC) from these sensors. Over Sesto Fiorentino area, an algorithm based on Artificial Neural Network (ANN) technique was implemented for estimating both SMC of bare or scarcely vegetated soil and vegetation biomass of wheat crops at X band. On the South-Tyrol area, a SMC retrieval approach based on the Support Vector Regression methodology, which was already tested in this area using C-band data from ENVISAT/ASAR data, was adopted. This algorithm integrated data at both X and C bands showing encouraging results, even though further investigations shall be carried out on a larger time-series and larger set of samples.

关键词： X-band backscatter C-band backscatter agricultural vegetation soil moisture vegetation biomass inversion algorithms Cosmo-SkyMed (CSK) RadarSAT2 (RS2)

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AN ANALYSIS OF THE CAPABILITIES OF COSMO-SKYMED AND RADARSAT SYSTEMS FOR AGRICULTURAL AREA MONITORING

AN ANALYSIS OF THE CAPABILITIES OF COSMO-SKYMED AND RADARSAT...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Paloscia, S. Pettinato, S. Santi, E. Notarnicola, C. Greifeneder, F. Cuozzo, G. Nicolini, I. Demir, B. Bruzzone, L. CNR IFAC Florence Italy EURAC Bolzano Italy Univ Trento Trento Italy

ISBN: (纸本)9781479979295

This research aims at analyzing the integration of C and X band data collected from Radarsat2 (RS2) and COSMO-SkyMed (CSK) systems on some test areas in Italy, in order to estimate the main geophysical parameters of soil and vegetation, such as soil moisture and vegetation biomass. A check of the sensitivity of SAR signal to the soil parameters was first carried out on both test sites. Over the South-Tyrol area a retrieval approach based on the Support Vector Regression methodology, which was already tested in this area using C-band data from ENVISAT/ASAR data, was carried out. From these preliminary results it can be concluded that X-band images combined with C-band images could provide valuable information for the retrieval of SMC, even though further investigations should be carried out on a larger time-series and larger set of samples.

关键词： Cosmo-SkyMed Radarsat2 agricultural areas soil moisture retrieval inversion algorithms

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AN ANALYSIS OF THE CAPABILITIES OF COSMO-SKYMED AND RADARSAT SYSTEMS FOR AGRICULTURAL AREA MONITORING

AN ANALYSIS OF THE CAPABILITIES OF COSMO-SKYMED AND RADARSAT...

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IEEE International Geoscience and Remote Sensing Symposium

作者： S. Paloscia S. Pettinato E. Santi C. Notarnicola F. Greifeneder G. Cuozzo I. Nicolini B. Demir L. Bruzzone IFAC-CNR EURAC University of Trento

ISBN: (纸本)9781479979301

关键词： Cosmo-SkyMed Radarsat2 Agricultural areas Soil moisture retrieval inversion algorithms

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Soil moisture mapping using Sentinel-1 images: Algorithm and preliminary validation

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REMOTE SENSING OF ENVIRONMENT 2013年 134卷 234-248页

作者： Paloscia, S. Pettinato, S. Santi, E. Notarnicola, C. Pasolli, L. Reppucci, A. Natl Res Council IFAC CNR Inst Appl Phys I-50019 Florence Italy EURAC Res Bolzano Italy Starlab Barcelona Spain

The main objective of this research is to develop, test and validate a soil moisture content (SMC) algorithm for GMES Sentinel-1 characteristics. The SMC product, which is to be generated from Sentinel-1 data, requires an algorithm capable of processing operationally in near-real-time and delivering the product to the GMES services within 3 h from observation. An approach based on an Artificial Neural Network (ANN) has been proposed that represents a good compromise between retrieval accuracy and processing time, thus enabling compliance with the timeliness requirements. The algorithm has been tested and subsequently validated in several test areas in Italy, Australia, and Spain. In all cases the validation results were very much in line with GMES requirements (with RMSE generally <4%SMC - between 1.67%SMC and 6.68%SMC - and very low bias), except for the case of the test area in Spain, where the validation results were penalized by the availability of only VV polarized SAR images and MODIS low-resolution NDVI. Nonetheless, the obtained RMSE was slightly higher than 4%SMC. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Sentinel-1 Backscattering coefficient Soil moisture maps inversion algorithms Artificial Neural Network

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Comparison between SAR Soil Moisture Estimates and Hydrological Model Simulations over the Scrivia Test Site

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REMOTE SENSING 2013年第10期5卷 4961-4976页

作者： Santi, Emanuele Paloscia, Simonetta Pettinato, Simone Notarnicola, Claudia Pasolli, Luca Pistocchi, Alberto Natl Res Council IFAC CNR Ist Fis Applicata Nello Carrara I-50019 Florence Italy EURAC Res Inst Appl Remote Sensing I-39100 Bolzano Italy Gecosistema R&D Unit Trentino Suedtirol I-39100 Bolzano Italy

In this paper, the results of a comparison between the soil moisture content (SMC) estimated from C-band SAR, the SMC simulated by a hydrological model, and the SMC measured on ground are presented. The study was carried out in an agricultural test site located in North-west Italy, in the Scrivia river basin. The hydrological model used for the simulations consists of a one-layer soil water balance model, which was found to be able to partially reproduce the soil moisture variability, retaining at the same time simplicity and effectiveness in describing the topsoil. SMC estimates were derived from the application of a retrieval algorithm, based on an Artificial Neural Network approach, to a time series of ENVISAT/ASAR images acquired over the Scrivia test site. The core of the algorithm was represented by a set of ANNs able to deal with the different SAR configurations in terms of polarizations and available ancillary data. In case of crop covered soils, the effect of vegetation was accounted for using NDVI information, or, if available, for the cross-polarized channel. The algorithm results showed some ability in retrieving SMC with RMSE generally <0.04 m(3)/m(3) and very low bias (i.e., <0.01 m(3)/m(3)), except for the case of VV polarized SAR images: in this case, the obtained RMSE was somewhat higher than 0.04 m(3)/m(3) (0.058 m(3)/m(3)). The algorithm was implemented within the framework of an ESA project concerning the development of an operative algorithm for the SMC retrieval from Sentinel-1 data. The algorithm should take into account the GMES requirements of SMC accuracy (5% in volume), spatial resolution (1 km) and timeliness (3 h from observation). The SMC estimated by the SAR algorithm, the SMC estimated by the hydrological model, and the SMC measured on ground were found to be in good agreement. The hydrological model simulations were performed at two soil depths: 30 and 5 cm and showed that the 30 cm simulations indicated, as expected, SMC values high

关键词： SAR data soil moisture hydrological model Artificial Neural Networks inversion algorithms

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THE CASE FOR A GLOBAL INLAND WATER QUALITY PRODUCT

THE CASE FOR A GLOBAL INLAND WATER QUALITY PRODUCT

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Malthus, Tim J. Hestir, Erin L. Dekker, Arnold G. Brando, Vittorio E. CSIRO Environm Earth Observat Program Div Land & Water Canberra ACT Australia

ISBN: (纸本)9781467311595

This paper argues for the development of a quantitative global inland water quality product based on satellite optical remote sensing. Water quality is a critical component of global fresh water security and ecosystem health, yet is often overlooked when global analyses of water security are undertaken. In the face of declining surface measurements and datasets across the globe, alternatives to conventional water quality measurement are required. The case for an optical remote sensing based inland water quality product is a strong one. Global products of ocean color and their dissemination infrastructure are operational and widely used, providing a framework for global inland products. Furthermore, coastal and inland water quality algorithms based on spectral inversion algorithms are now sufficiently mature to cope with the greater variability of inherent optical properties in these systems. While these algorithms provide the greatest promise for reliable, robust and simultaneous retrieval of several water quality variables across sensors, limited knowledge of the bio-optical properties of inland waters and limited validation currently prevent global implementation. Internationally coordinated efforts are required to accumulate representative bio-optical data to improve our understanding of the optical complexity and variability of inland waters.

关键词： Inland water quality optical remote sensing inversion algorithms global datasets

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