Identification of Soil Freezing and Thawing States Using SAR Polarimetry at C-Band

Jagdhuber, Thomas; Stockamp, Julia; Hajnsek, Irena; Ludwig, Ralf

doi:10.3390/rs6032008

Cited by 38 publications

(31 citation statements)

References 21 publications

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“…High α values represent domination of double bounce scattering, which indicates either urban area or tree trunks. α values in between the aforementioned extremes (i.e., around 45°) show domination of volume scattering, caused by dense vegetation, e.g., multiple scattering inside a volume such as the crown of a tree [18]. αm represents the mean of α1 and α2, with the former describing the backscattering type of the dominant scatterer and the latter the backscattering type of the second dominant one (Equation (8)):…”

Section: Polarimetric Decompositionmentioning

confidence: 99%

Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

2014

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Abstract:In developing countries, there is a high correlation between the dependence of oil exports and violent conflicts. Furthermore, even in countries which experienced a peaceful development of their oil industry, land use and environmental issues occur. Therefore, independent monitoring of oil field infrastructure may support problem solving. Earth observation data enables fast monitoring of large areas which allows comparing the real amount of land used by the oil exploitation and the companies' contractual obligations. The target feature of this monitoring is the infrastructure of the oil exploitation, oil well pads-rectangular features of bare land covering an area of approximately 50-60 m × 100 m. This article presents an automated feature extraction procedure based on the combination of a pixel-based unsupervised classification of polarimetric synthetic aperture radar data (PolSAR) and an object-based post-classification. The method is developed and tested using dual-polarimetric TerraSAR-X imagery acquired over the Doba basin in south Chad. The advantages of PolSAR are independence of the cloud coverage (vs. optical imagery) and the possibility of detailed land use classification (vs. single-pol SAR). The PolSAR classification uses the polarimetric Wishart probability density function based on the anisotropy/entropy/alpha decomposition. The object-based post-classification refinement, based on properties of the feature targets such as shape and area, increases the user's accuracy of the methodology by an order of a magnitude. The final achieved user's and OPEN ACCESSRemote Sens. 2014, 6 11978 producer's accuracy is 59%-71% in each case (area based accuracy assessment). Considering only the numbers of correctly/falsely detected oil well pads, the user's and producer's accuracies increase to even 74%-89%. In an iterative training procedure the best suited polarimetric speckle filter and processing parameters of the developed feature extraction procedure are determined. The high transferability of the methodology is proved by an application to a second SAR acquisition.

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Section: Polarimetric Decompositionmentioning

confidence: 99%

Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

2014

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“…α values close to zero indicate domination of surface scattering (single bounce scattering). α values around 45˝show domination of volume scattering, caused by multiple scattering inside a volume, such as the crown of a tree or dense vegetation [56]. High α values (up to 90˝) represent domination of double-bounce scattering (e.g., in urban area).…”

Section: Polarimetric Decompositionmentioning

confidence: 99%

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

2016

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Abstract:Mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response, i.e., to support rescue and humanitarian operations. Most synthetic aperture radar (SAR) data-based landslide detection approaches reported in the literature use change detection techniques, requiring very high resolution (VHR) SAR imagery acquired shortly before the landslide event, which is commonly not available. Modern VHR SAR missions, e.g., Radarsat-2, TerraSAR-X, or COSMO-SkyMed, do not systematically cover the entire world, due to limitations in onboard disk space and downlink transmission rates. Here, we present a fast and transferable procedure for mapping of landslides, based on change detection between pre-event optical imagery and the polarimetric entropy derived from post-event VHR polarimetric SAR data. Pre-event information is derived from high resolution optical imagery of Landsat-8 or Sentinel-2, which are freely available and systematically acquired over the entire Earth's landmass. The landslide mapping is refined by slope information from a digital elevation model generated from bi-static TanDEM-X imagery. The methodology was successfully applied to two landslide events of different characteristics: A rotational slide near Charleston, West Virginia, USA and a mining waste earthflow near Bolshaya Talda, Russia.

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“…Cloude and Pottier calculated an entropy H and an angle α and then linearly separated the H-α plane into nine zones within a feasible region to determine the basic scattering mechanisms. In recent years, Cloude-Pottier decomposition has been analyzed, improved, and widely applied in segmentation, classification, and detection applications [17][18][19][20][21][22][23][24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Scattering Mechanism Extraction by a Modified Cloude-Pottier Decomposition for Dual Polarization SAR

Wu²

2015

Remote Sensing

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Dual polarization is a typical operational mode of polarimetric synthetic aperture radar (SAR). However, few studies have considered the scattering mechanism extraction of dual-polarization SARs. A modified Cloude-Pottier decomposition is proposed to investigate the performance of the scattering mechanism extraction of dual-polarization SARs. It is theoretically demonstrated that only HH-VV SAR can discriminate the three canonical scattering mechanisms from an isotropic surface, horizontal dipole, and isotropic dihedral. Various experiments are conducted using 21 scenes from real datasets acquired by AIRSAR, Convair-580 SAR, EMISAR, E-SAR, Pi-SAR, and RADARSAT-2. Division of the dual-polarization H-α plane is experimentally obtained. The lack of cross-polarization induces the diffusion of scattering mechanisms and their overlap in the HH-VV H-α plane. However, the performance of HH-VV SAR for extracting scattering mechanisms is acceptable. Thus, HH-VV SAR is a suitable alternative to full-polarization SAR in certain cases. Meanwhile, the extraction performance of the other two dual-polarization SARs is badly degraded due to the lack of co-polarization. Therefore, HH-HV and HV-VV SARs cannot effectively extract the scattering mechanisms in the H-α plane.

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Identification of Soil Freezing and Thawing States Using SAR Polarimetry at C-Band

Cited by 38 publications

References 21 publications

Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

Scattering Mechanism Extraction by a Modified Cloude-Pottier Decomposition for Dual Polarization SAR

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