Special Issue "Selected Papers from the Polarimetric Interferometric SAR Workshop 2019"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 October 2019).

Special Issue Editors

Dr. Klaus Scipal
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Guest Editor
European Space Agency, Earth Observation Mission Mission Management Division, ESRIN, Largo Galileo Galilei 1, IT-00044 Frascati, Italy
Interests: SAR; Forest Structure; Biomass
Special Issues and Collections in MDPI journals
Prof. Dr. Irena Hajnsek
Website1 Website2
Guest Editor
1. Swiss Federal Institute of Technology Zurich (ETH), Institute of Environmental Engineering, HIF D28.1, Stefano-Franscini Platz 3, CH-8093 Zurich, Switzerland
2. German Aerospace Center, Microwaves and Radar Institute, Department: Radar Concepts, Research Group: Pol-InSAR, P.O. Box 1116, D-82234 Wessling, Germany
Interests: radar remote sensing of the Earth’s surface; polarimetric and interferometric data processing and analysis for different environmental applications
Special Issues and Collections in MDPI journals
Prof. Juanma Lopez Sanchez
Website
Guest Editor
DFISTS – IUII, Universidad de Alicante, P.O. Box 99, E-03080 Alicante, Spain
Interests: radar polarimetry; interferometry; polarimetric SAR interferometry; agriculture; geophysics
Special Issues and Collections in MDPI journals
Prof. Y S Rao
Website
Guest Editor
Centre of Studies in Resources Engineering (CSRE), Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India
Interests: hybrid polarimetry; calibration; Polar SAR data inversion for soil moisture; biomass; LAI; classification
Dr. Scott Hensley

Guest Editor
Jet Propulsion Lab, 4800 Oak Grove Dr., Pasadena, CA 91109, USA
Prof. Yoshio Yamaguchi
Website
Guest Editor
Dept. of Information Engineering, Niigata University, Ikarashi 2-8050, Nishi-ku, Niigata 950-2181, Japan
Interests: polarimetric SAR data utilization and decomposition; polarimetric radar sensing of the Earth’s surface with environmental applications
Prof. Eric Pottier

Guest Editor
Université de Rennes 1, 263 Avenue du Général Leclerc, 35042 Rennes, France
Interests: radar polarimetry

Special Issue Information

Dear Colleagues,

The introduction of polarimetric SAR interferometry (Pol-InSAR) at the end of the 1990s was a decisive step towards developing remote sensing applications relevant to forestry. Pol-InSAR is based on the coherent combination of SAR interferograms for different polarizations. SAR interferograms are sensitive to the spatial diversity of the vegetation’s vertical structure and allow precise measurement of the scattering center. The polarimetric radar signature is also sensitive to the shape, orientation and dielectric properties of the scatterers and facilitates the identification and/or separation of scattering mechanisms in natural materials. With polarimetric SAR interferometry, the complementary sensitivities of these two measurements are combined coherently, allowing the quantitative determination of relevant (structure) parameters from SAR measurements. Today, Pol-InSAR is an established technique, allowing investigation of the 3-D structure of natural volume scatterers and is applied to a broad range of applications (forestry, agriculture, cryosphere, etc.). Several new techniques have been developed in this domain for data processing and model inversions, and extensions have been considered to multi-baseline modes providing an increased observation space. In this Special Issue we would like to collect contributions on advances in this domain

We would like to invite you to submit articles about your recent research with respect to the following topics.

  • Polarimetric SAR: Methods, Models and Inversion
  • Polarimetric SAR applied to different applications
  • Polarimetric SAR Interferometry: Methods, Models and Inversion
  • Polarimetric SAR Inteferometry applied to different applications
  • Multi-baseline polarimeric SAR interferometry (Polarimetric Tomography)
  • Satellite Missions employing polarimetric SAR interferometry
  • Review articles covering one or more of these topics are also welcome.

Dr. Klaus Scipal
Prof. Dr. Irena Hajnsek
Prof. Juanma Lopez Sanchez
Prof. Y S Rao
Dr. Scott Hensley
Prof. Yoshio Yamaguchi
Prof. Eric Pottier
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (6 papers)

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Research

Open AccessArticle
Effects on the Double Bounce Detection in Urban Areas Based on SAR Polarimetric Characteristics
Remote Sens. 2020, 12(7), 1187; https://doi.org/10.3390/rs12071187 - 07 Apr 2020
Cited by 1
Abstract
Synthetic Aperture Radar (SAR) polarimetric datasets are widely used in the detection and classification of urban areas. Most methods used today are based on the decomposition of fully polarimetric SAR data, which allows for the extraction of physical information about the nature of [...] Read more.
Synthetic Aperture Radar (SAR) polarimetric datasets are widely used in the detection and classification of urban areas. Most methods used today are based on the decomposition of fully polarimetric SAR data, which allows for the extraction of physical information about the nature of the medium and the application of proper classification methods. According to the theory, the main and predominant backscattering mechanism for buildings is double bounce. However, when analyzing urban environments, the observed predominant backscatter may differ from theory depending on many aspects. In this paper, we analyze fully polarimetric ALOS PALSAR data for various cities located on different continents, proving that the theory does not hold for most cases. There are many factors that have an impact on the detected backscatter mechanism, and the theoretical principle of predominant double bounce in urban areas can be met only under specific conditions. These factors are, among others, the orientation of the buildings, the dimensions of the streets, the type of construction (i.e., numerous planes on the roof), etc. This paper also mentions the canonical example of San Francisco, widely analyzed in the literature, as a case showing the impact of building deorientation on double bounce scattering. This area of interest is also discussed in terms of the impact of SAR data resolution on the detection of specific backscatter mechanisms. The findings of this work are very useful for increasing the awareness of the utilization of classification approaches where only pixels with double bounce backscatter mechanisms are classified as urban areas. Moreover, the article lists factors that should be taken into consideration when performing urban area detection based only on polarimetric data and standard algorithms, such as street and building orientation, building heights, and structures. Full article
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Open AccessArticle
Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data
Remote Sens. 2020, 12(2), 240; https://doi.org/10.3390/rs12020240 - 10 Jan 2020
Cited by 2
Abstract
In this work, the role of volume scattering obtained from ground and volume decomposition of P-band synthetic aperture radar (SAR) data as a proxy for biomass is investigated. The analysis here presented originates from the BIOMASS L2 activities, part of which were focused [...] Read more.
In this work, the role of volume scattering obtained from ground and volume decomposition of P-band synthetic aperture radar (SAR) data as a proxy for biomass is investigated. The analysis here presented originates from the BIOMASS L2 activities, part of which were focused on strengthening the physical foundations of the SAR-based retrieval of forest above-ground biomass (AGB). A critical analysis of the observed strong correlation between tomographic intensity and AGB is done in order to propose simplified AGB proxies to be used during the interferometric phase of BIOMASS. In particular, the aim is to discuss whether, and to what extent, volume scattering obtained from ground/volume decomposition can provide a reasonable alternative to tomography. To do this, both are tested on P-band data collected at Paracou during the TropiSAR campaign and cross-validated against in-situ AGB measurements. Results indicate that volume backscattered power as obtained by ground/volume decomposition is weakly correlated to AGB, notwithstanding different solutions for volume scattering are tested, and support the conclusion that forest structure actually plays a non-negligible role in AGB retrieval in dense tropical forests. Full article
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Open AccessArticle
Monitoring and Detecting Archaeological Features with Multi-Frequency Polarimetric Analysis
Remote Sens. 2020, 12(1), 1; https://doi.org/10.3390/rs12010001 - 18 Dec 2019
Cited by 3
Abstract
In remote sensing for archaeology, an unequivocal method capable of automatic detection of archaeological features still does not exists. Applications of Synthetic Aperture Radar (SAR) remote sensing for archaeology mainly focus on high spatial resolution SAR sensors, which allow the recognition of structures [...] Read more.
In remote sensing for archaeology, an unequivocal method capable of automatic detection of archaeological features still does not exists. Applications of Synthetic Aperture Radar (SAR) remote sensing for archaeology mainly focus on high spatial resolution SAR sensors, which allow the recognition of structures of small dimension and give information of the surface topography of sites. In this study we investigated the potential of combined dual and fully polarized SAR data and performed polarimetric multi-frequency and multi-incidence angle analysis of C-band Sentinel-1, L-band Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) and of C-band Radar Satellite-2 (RADARSAT-2) datasets for the detection of surface and subsurface archaeological structures over the United Nations Educational, Scientific and Cultural Organization (UNESCO) site of Gebel Barkal (Sudan). While PALSAR offers a good historical reference, Sentinel-1 time series provide recent and systematic monitoring opportunities. RADARSAT-2 polarimetric data have been specifically acquired in 2012/2013, and have been scheduled to achieve a multi-temporal observation of the archaeological area under study. This work demonstrated how to exploit a complex but significant dataset composed of SAR full polarimetric and dual polarimetric acquisitions, with the purpose of identifying the most suitable earth observation technique for the preservation and identification of archaeological features. The scientific potential of the illustrated analysis fits perfectly with the current delicate needs of cultural heritage; such analysis demonstrates how multi-temporal and multi-data cultural heritage monitoring can be applied not only for documentation purposes, but can be addressed especially to those areas exposed to threats of different nature that require a constant and prompt intervention plans. Full article
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Open AccessArticle
Analysis of Stochastic Distances and Wishart Mixture Models Applied on PolSAR Images
Remote Sens. 2019, 11(24), 2994; https://doi.org/10.3390/rs11242994 - 12 Dec 2019
Cited by 1
Abstract
This paper address unsupervised classification strategies applied to Polarimetric Synthetic Aperture Radar (PolSAR) images. We analyze the performance of complex Wishart distribution, which is a widely used model for multi-look PolSAR images, and the robustness of five stochastic distances (Bhattacharyya, Kullback-Leibler, Rényi, Hellinger [...] Read more.
This paper address unsupervised classification strategies applied to Polarimetric Synthetic Aperture Radar (PolSAR) images. We analyze the performance of complex Wishart distribution, which is a widely used model for multi-look PolSAR images, and the robustness of five stochastic distances (Bhattacharyya, Kullback-Leibler, Rényi, Hellinger and Chi-square) between Wishart distributions. Two unsupervised classification strategies were chosen: the Stochastic Clustering (SC) algorithm, which is based on the K-means algorithm but uses stochastic distance as the similarity metric, and the Expectation-Maximization (EM) algorithm for Wishart Mixture Model. With the aim of assessing the performance of all algorithms presented here, we performed a Monte Carlo simulation over a set of simulated PolSAR images. A second experiment was conducted using the study area of Tapajós National Forest and the surrounding area, in Brazilian Amazon Forest. The PolSAR images were obtained by the satellite PALSAR. The results, in both experiments, suggest that the EM algorithm and the SC with Hellinger and the SC with Bhattacharyya distance provide a better classification performance. We also analyze the initialization problem for SC and EM algorithms, and we demonstrate how the initial centroid choice influences the final classification result. Full article
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Open AccessArticle
Applicability of the MultiTemporal Coherence Approach to Sentinel-1 for the Detection and Delineation of Burnt Areas in the Context of the Copernicus Emergency Management Service
Remote Sens. 2019, 11(22), 2607; https://doi.org/10.3390/rs11222607 - 07 Nov 2019
Abstract
In the framework of the Copernicus Emergency Management Service (EMS) Mapping Validation, the applicability of the MultiTemporal Coherence (MTC) technique using Sentinel-1 data and the software made available by the European Space Agency (ESA), the Sentinel Application Platform (SNAP), for the detection and [...] Read more.
In the framework of the Copernicus Emergency Management Service (EMS) Mapping Validation, the applicability of the MultiTemporal Coherence (MTC) technique using Sentinel-1 data and the software made available by the European Space Agency (ESA), the Sentinel Application Platform (SNAP), for the detection and delineation of burnt areas was tested. The main purpose of the study was to test a methodology that would benefit from the advantages of delineating burnt areas based on radar data with respect to optical data due to its capacity to acquire data both night and day and to avoid the interference of clouds and/or smoke. Moreover, the study aimed to acheive the delineation of the burnt areas using Sentinel-1 and SNAP in the frame of an emergency mapping where processing time is constrained due to the necessity of giving a quick response to the emergency. Four Sentinel-1 images were acquired over a mountainous area mainly covered by Mediterranean vegetation that suffered from massive forest fires in the summer of 2016. The burnt area delineation was obtained by an object-based image analysis (OBIA) of the resulting MTC image followed by a visual inspection. The effects of the polarization, the acquisition mode, and the incidence angle of the synthetic aperture radar (SAR) imagery were studied in order to assess the contribution of these sensor varaibles on the results. Results of the Sentinel-1 based delineation were compared to those using optical imagery, which is traditionally used for this application. Therefore, the fire delineation that was derived was compared to that derived using three optical images: pre- and post-event Sentinel-2 images and a post-event SPOT 6 image. The first two were used to calculate the differences of the burnt area index (dBAI), used to derive the burnt area delineation by OBIA and photo interpretation with the help of the SPOT 6 image. Results of the comparison showed the feasibility of using the MTC technique for burnt area delineation, as high overall accuracy values were observed when compared to the burnt area delineation derived from optical imagery. The importance of the incidence angle of the Sentinel-1 images was assessed as well, with lower angles resulting in higher overall accuracies. In addition, the availability of double polarization of the Sentinel-1 images, allowed us to give recommendations regarding which polarization gave the best results. The potential for the use of SAR data, obtaining equivalent results to those obtained from optical imagery, is significant in an emergency context given that radar sensors acquire images continuosly and in all weather conditions. Full article
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Open AccessArticle
Wind Speed Retrieval from Simulated RADARSAT Constellation Mission Compact Polarimetry SAR Data for Marine Application
Remote Sens. 2019, 11(14), 1682; https://doi.org/10.3390/rs11141682 - 16 Jul 2019
Cited by 1
Abstract
RADARSAT Constellation Mission (RCM) compact polarimetry (CP) data were simulated using 504 RADARSAT-2 quad-pol SAR images. These images were used to samples CP data in three RCM modes to build a data set with co-located ocean wind vector observations from in situ buoys [...] Read more.
RADARSAT Constellation Mission (RCM) compact polarimetry (CP) data were simulated using 504 RADARSAT-2 quad-pol SAR images. These images were used to samples CP data in three RCM modes to build a data set with co-located ocean wind vector observations from in situ buoys on the West and East coasts of Canada. Wind speeds up to 18 m/s were included. CP and linear polarization parameters were related to the C-band model (CMOD) geophysical model functions CMOD-IFR2 and CMOD5n. These were evaluated for their wind retrieval potential in each RCM mode. The CP parameter Conformity was investigated to establish a data-quality threshold (>0.2), to ensure high-quality data for model validation. An accuracy analysis shows that the first Stokes vector (SV0) and the right-transmit vertical-receive backscatter (RV) parameters were as good as the VV backscatter with CMOD inversion. SV0 produced wind speed retrieval accuracies between 2.13 m/s and 2.22 m/s, depending on the RCM mode. The RCM Medium Resolution 50 m mode produced the best results. The Low Resolution 100 m and Low Noise modes provided similar results. The efficacy of SV0 and RV imparts confidence in the continuity of robust wind speed retrieval with RCM CP data. Three image-based case studies illustrate the potential for the application of CP parameters and RCM modes in operational wind retrieval systems. The results of this study provide guidance to direct research objectives once RCM is launched. The results also provide guidance for operational RCM data implementation in Canada’s National SAR winds system, which provides near-real-time wind speed estimates to operational marine forecasters and meteorologists within Environment and Climate Change Canada. Full article
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