A Modified H−α Classification Method for DCP Compact Polarimetric Mode by Reconstructing Quad H and α Parameters From Dual Ones

Ghods, Sara; Shojaedini, Seyed Vahab; Maghsoudi, Yasser

doi:10.1109/jstars.2016.2570427

Cited by 9 publications

(3 citation statements)

References 14 publications

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“…Each C 2 element (C 11 , C 22 , (C 12 ), and (C 12 )) is stored individually and successively refined by Lee filtering (5 × 5 kernel size) to minimize speckle-related noise. H-α-A polarimetric decomposition was obtained by eigenvector computation as proposed by different authors [57,62,63]. The modified formula for dual-pol data, as proposed by [66], is reported in Equations ( 2) and (3).…”

Section: Data Processing 231 Polarimetric Decompositionmentioning

confidence: 99%

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Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm

Petris

Sarvia

Gullino³

et al. 2021

Remote Sensing

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Climate change increases extreme whether events such as floods, hailstorms, or storms, which can affect agriculture, causing damages and economic loss within the agro-food sector. Optical remote sensing data have been successfully used in damage detections. Cloud conditions limit their potential, especially while monitoring floods or storms that are usually related to cloudy situations. Conversely, data from the Polarimetric Synthetic Aperture Radar (PolSAR) are operational in all-weather conditions and are sensitive to the geometrical properties of crops. Apple orchards play a key role in the Italian agriculture sector, presenting a cultivation system that is very sensitive to high-wind events. In this work, the H-α-A polarimetric decomposition technique was adopted to map damaged apple orchards with reference to a stormy event that had occurred in the study area (NW Italy) on 12 August 2020. The results showed that damaged orchards have higher H (entropy) and α (alpha angle) values compared with undamaged ones taken as reference (Mann–Whitney one-tailed test U = 14,514, p < 0.001; U = 16604, p < 0.001 for H and α, respectively). By contrast, A (anisotropy) values were significantly lower for damaged orchards (Mann–Whitney one-tailed test U = 8616, p < 0.001). Based on this evidence, the authors generated a map of potentially storm-damaged orchards, assigning a probability value to each of them. This map is intended to support local funding restoration policies by insurance companies and local administrations.

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Section: Data Processing 231 Polarimetric Decompositionmentioning

confidence: 99%

“…The method was originally developed for quadpolarization data. Nevertheless, it was also adapted to work with dual-pol data [57,62,63], and consequently, it can be successfully used to retrieve polarimetric information also from S1 data that are unable to collect quad-pol data.…”

Section: Introductionmentioning

confidence: 99%

Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm

Petris

Sarvia

Gullino³

et al. 2021

Remote Sensing

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“…The eigenvector polarimetric decomposition is an eigenvalue analysis of the coherency matrix originally developed by Cloude and Pottier [42] to handle quad-polarisation data. This polarimetric decomposition technique has since evolved to utilise dual-polarisation data [43][44][45] such as the S1. In applying eigenvector decomposition to dual-polarisation data, the original formulation has been modified [46] and, as a result, a 2 × 2 coherency matrix [C coh ] is expressed as…”

Section: Theory Of Eigenvector Scattering Mechanismmentioning

confidence: 99%

A Preliminary Investigation of the Potential of Sentinel-1 Radar to Estimate Pasture Biomass in a Grazed Pasture Landscape

et al. 2019

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Knowledge of the aboveground biomass (AGB) of large pasture fields is invaluable as it assists graziers to set stocking rate. In this preliminary evaluation, we investigated the response of Sentinel-1 (S1) Synthetic Aperture Radar (SAR) data to biophysical variables (leaf area index, height and AGB) for native pasture grasses on a hilly, pastoral farm. The S1 polarimetric parameters such as backscattering coefficients, scattering entropy, scattering anisotropy, and mean scattering angle were regressed against the widely used morphological parameters of leaf area index (LAI) and height, as well as AGB of pasture grasses. We found S1 data to be more responsive to the pasture parameters when using a 1 m digital elevation model (DEM) to orthorectify the SAR image than when we employed the often-used Shuttle Radar Topography 30 m and 90 m Missions. With the 1m DEM analysis, a significant quadratic relationship was observed between AGB and VH cross-polarisation (R2 = 0.71), and significant exponential relationships between polarimetric entropy and LAI and AGB (R2 = 0.53 and 0.45, respectively). Similarly, the mean scattering angle showed a significant exponential relationship with LAI and AGB (R2 = 0.58 and R2 = 0.83, respectively). The study also found a significant quadratic relationship between the mean scattering angle and pasture height (R2 = 0.72). Despite a relatively small dataset and single season, the mean scattering angle in conjunction with a generalised additive model (GAM) explained 73% of variance in the AGB estimates. The GAM model estimated AGB with a root mean square error of 392 kg/ha over a range in pasture AGB of 443 kg/ha to 2642 kg/ha with pasture LAI ranging from 0.27 to 1.87 and height 3.25 cm to 13.75 cm. These performance metrics, while indicative at best owing to the limited datasets used, are nonetheless encouraging in terms of the application of S1 data to evaluating pasture parameters under conditions which may preclude use of traditional optical remote sensing systems.

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Application of H/ᾱ Decomposition to Limited and Dual-Polarimetric 3D SAR Data of Civilian Vehicles

Demirci

Izumi

2023

IEEE Access

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A Modified H−α Classification Method for DCP Compact Polarimetric Mode by Reconstructing Quad H and α Parameters From Dual Ones

Cited by 9 publications

References 14 publications

Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm

Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm

A Preliminary Investigation of the Potential of Sentinel-1 Radar to Estimate Pasture Biomass in a Grazed Pasture Landscape

Application of H/ᾱ Decomposition to Limited and Dual-Polarimetric 3D SAR Data of Civilian Vehicles

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