PolInSAR analysis of X-band data over vegetated and urban areas

Garestier, Franck; Dubois-Fernandez, Pascale; Dupuis, Xavier; Paillou, Philippe; Hajnsek, Irena

doi:10.1109/tgrs.2005.862525

Cited by 39 publications

(30 citation statements)

References 16 publications

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“…The final stage was the application of a mean filter to smooth the DTM. To identify the most appropriate mean filter size a series of filters with windows of 5,15,25,35,45,55 and 65 pixels diameter were tested. To determine the optimum threshold level for each of the ancillary data sets a range of thresholds were also tested, which in conjunction with the 6 InSAR DSM's available and the number of mean filtering options applied led to 1428 DTM being created overall (see Table I).…”

Section: Dtm Generationmentioning

confidence: 99%

“…Incorporating polarimetric data into SAR interferometry enables information on the scattering processes and their height to be determined. Applications of polarimetric SAR interferometry (PolInSAR) have focused on forested areas, but have also explored the potential for PolInSAR analysis over agricultural and urban areas [5], [6] and snow [7]. Forest height mapping is the most developed PolInSAR application area with work focusing primarily on model development and model inversion to yield canopy height, topography and canopy extinction rates [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

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Data Fusion for Reconstruction of a DTM, Under a Woodland Canopy, From Airborne L-band InSAR

Rowland

Balzter

2007

IEEE Trans. Geosci. Remote Sensing

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Abstract-This paper investigates the utility of different parameters from polarimetric interferometric SAR data for the identification of ground pixels in a woodland area to enable accurate digital terrain model (DTM) generation from the InSAR height of the selected ground hit pixels. The parameters assessed include radar backscatter, interferometric coherence, surface scattering proportion (based on Freeman-Durden decomposition) and standard deviation of the interferometric height. The method is applied to Monks Wood, a small semi-natural deciduous woodland in Cambridgeshire, UK, using airborne E-SAR data collected in June 2000. The 1428 variations of SAR-derived terrain models are validated with theodolite data and a LiDARderived DTM. The results show that increasing the amount of data used in the DTM creation does not necessarily increase the accuracy of the final DTM. The most accurate method, for the whole wood, was a fixed window minimum filtering algorithm, followed by a mean filter. However, for a spatial subset of the area using the υ 3 backscattering coefficient to identify ground pixels out-performs the minimum filtering method. The findings suggest that backscatter information may often be undervalued in estimating terrain height under forest canopies.Index Terms-polarimetric interferometric synthetic aperture radar (PolInSAR), vegetation, digital terrain model (DTM), ancillary data, interferometry, polarimetry

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Section: Dtm Generationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data Fusion for Reconstruction of a DTM, Under a Woodland Canopy, From Airborne L-band InSAR

Rowland

Balzter

2007

IEEE Trans. Geosci. Remote Sensing

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“…T HE ESTIMATION of biophysical parameters of vegetation cover from radar remote sensors with interferometric and polarimetric capabilities [polarimetric interferometric synthetic aperture radar (PolInSAR)] has been demonstrated recently at different frequencies: P-band [1], L-band [2], [3], and even X-band [4]. In the case of forest cover, the random volume over ground (RVoG) model proposed in [5] and [6] has been successfully inverted for forest height and biomass [3], [7].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the model is also very simple from the electromagnetic point of view since the interaction between the vegetation elements is simplified in the formulation. (4) according to the framework proposed in [3]. z denotes the vertical coordinate, hv is the vegetation height (i.e., the depth of the layer), and θ 0 is the mean incidence angle.…”

Section: Introductionmentioning

confidence: 99%

Model Limitations and Parameter-Estimation Methods for Agricultural Applications of Polarimetric SAR Interferometry

López-Sánchez

Ballester-Berman

Márquez-Moreno

2007

IEEE Trans. Geosci. Remote Sensing

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Abstract-Application of polarimetric synthetic aperture radar interferometry to the retrieval of geophysical parameters from vegetated scenes is based on simple direct models of such scenes. The first part of this paper presents an analysis of the correspondence between these simple models, namely, the random volume over ground and the oriented volume over ground (OVoG), and experimental data from samples of two agricultural crops (maize and rice) acquired in controlled conditions. Although an overall agreement between model and data is clear, some discrepancies have been found as a consequence of two assumptions in the model formulation: vertical homogeneity of the vegetation volume and absence of multiple scattering effects inside the volume. This paper presents the shape and location of the visible region of the experimental coherences on the complex plane and compares it with the feasible region predicted by the model. This comparison has also pointed out the low sensitivity of the direct model to extinction coefficients. In the second part, two different strategies for a complete inversion (i.e., estimation of all model parameters) of the OVoG model are proposed and compared, using the same data set. The first one is based on a combination of geometrical and numerical approaches (genetic algorithms) and the second one on a dual-baseline configuration. In all cases, ground topography is accurately estimated, with a maximum error of 10 cm. Vegetation height estimates are accurate up to 30 cm, with some bands and baseline configurations providing errors below 15 cm. However, results obtained for the extinction coefficients are not stable with frequency and exhibit high variability.Index Terms-Agriculture, dual baseline, genetic algorithms, parameter retrieval, polarimetric synthetic aperture radar interferometry, vegetation.

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“…Synthetic Aperture Radar (SAR) imaging of urban areas has received much interest in recent years with some promising applications [1][2][3]. A major challenge is to give a fast and accurate ElectroMagnetic (EM) model in order to provide synthetic data for imaging algorithms.…”

Section: Introductionmentioning

confidence: 99%

A 3d Model to Characterize High-Frequency Scattering by Urban Areas for Monostatic and Bistatic Radar Configurations

Nguyen¹,

Lautru²,

Roussel³

2011

PIER B

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Abstract-In this paper, we propose a 3D model to characterize the field scattered by an urban area, which is composed of a group of buildings, for both monostatic and bistatic radar configurations. This model is based on a ray-tracing technique combined with the Uniform Theory of Diffraction (UTD). It is useful not only in elucidating mechanisms of ray propagation through the observed area, but also in evaluating the amplitude and the phase of any point in the far-zone scattered field above the ground. In order to validate the model, some comparisons with the commercial software XGTD R are presented. In addition, our model is tested against 33-37 GHz indoor measurements conducted in the anechoic chamber of the "ElectroMagnetic Effects Research Lab" (EMERL) in Singapore. These latter comparisons have shown that the model can predict precisely the location of a target placed between two metallic plates representing walls.

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PolInSAR analysis of X-band data over vegetated and urban areas

Cited by 39 publications

References 16 publications

Data Fusion for Reconstruction of a DTM, Under a Woodland Canopy, From Airborne L-band InSAR

Data Fusion for Reconstruction of a DTM, Under a Woodland Canopy, From Airborne L-band InSAR

Model Limitations and Parameter-Estimation Methods for Agricultural Applications of Polarimetric SAR Interferometry

A 3d Model to Characterize High-Frequency Scattering by Urban Areas for Monostatic and Bistatic Radar Configurations

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