Special Issue "Applications of SAR Images for Urban Areas"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: 28 February 2021.

Special Issue Editors

Dr. Elise Colin-Koeniguer
Website
Guest Editor
Ingénieur de Recherche, Maître de Recherche Onera
Interests: radar; polarimetry; image processing; remote sensing
Dr. Flora Weissgerber
Website
Guest Editor
ONERA, the French Aerospace Lab, Palaiseau
Interests: SAR image; remote sensing

Special Issue Information

Dear Colleagues,

One of the most crucial problems in developed as well as developing countries is the management of urban and peri-urban areas, due to their very significant growth. In this context, remote sensing data represent an essential source of information. The emergence and recognition of urban remote sensing have benefited from the continual improvement in spatial resolution offered by successive generations of sensors.

Radar sensors are no exception to this development. Although they are less widely known about than optical (visible and infrared) sensors, SAR sensors constitute a valuable tool in urban remote sensing due to their ability to acquire images day and night, regardless of the weather conditions. Furthermore, the availability of the phase of the measured electric field allows for the implementation of specific techniques such as 3D interferometry (InSAR), differential interferometry (DInSAR), or tomography.

This Special Issue therefore proposes to address recent advances in the use of SAR images in urban areas from different points of view:

  • Spatial data processing methods: classification, learning methods, neural networks, feature extraction, pattern recognition, multitemporal analysis;
  • 3D methods: interferometry, tomography;
  • Multimodal methods involving SAR images;
  • Main applications: urban sprawl, planning, traffic, anthropic activities, materials, subsidence, natural risks, and disaster management;
  • The contribution of existing and future space missions and new means of observation (new generations of sensors) and the finest resolutions;
  • Understanding of urban and artificialized environments, their evolution, and monitoring indicators.

Dr. Elise Colin-Koeniguer
Dr. Flora Weissgerber
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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.

Keywords

  • Image processing methods
  • 3D methods
  • Multimodal
  • urban and artificialized environments
  • Interferometry, Differential Interferometry
  • Polarimetry
  • High resolution

Published Papers (2 papers)

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Open AccessFeature PaperArticle
Change Detection Based on the Coefficient of Variation in SAR Time-Series of Urban Areas
Remote Sens. 2020, 12(13), 2089; https://doi.org/10.3390/rs12132089 - 30 Jun 2020
Abstract
This paper discusses change detection in SAR time-series. First, several statistical properties of the coefficient of variation highlight its pertinence for change detection. Subsequently, several criteria are proposed. The coefficient of variation is suggested to detect any kind of change. Furthermore, several criteria [...] Read more.
This paper discusses change detection in SAR time-series. First, several statistical properties of the coefficient of variation highlight its pertinence for change detection. Subsequently, several criteria are proposed. The coefficient of variation is suggested to detect any kind of change. Furthermore, several criteria that are based on ratios of coefficients of variations are proposed to detect long events, such as construction test sites, or point-event, such as vehicles. These detection methods are first evaluated on theoretical statistical simulations to determine the scenarios where they can deliver the best results. The simulations demonstrate the greater sensitivity of the coefficient of variation to speckle mixtures, as in the case of agricultural plots. Conversely, they also demonstrate the greater specificity of the other criteria for the cases addressed: very short event or longer-term changes. Subsequently, detection performance is assessed on real data for different types of scenes and sensors (Sentinel-1, UAVSAR). In particular, a quantitative evaluation is performed with a comparison of our solutions with baseline methods. The proposed criteria achieve the best performance, with reduced computational complexity. On Sentinel-1 images containing mainly construction test sites, our best criterion reaches a probability of change detection of 90% for a false alarm rate that is equal to 5%. On UAVSAR images containing boats, the criteria proposed for short events achieve a probability of detection equal to 90% of all pixels belonging to the boats, for a false alarm rate that is equal to 2%. Full article
(This article belongs to the Special Issue Applications of SAR Images for Urban Areas)
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Open AccessLetter
The Combined Effect of Orientation Angle and Material on PolSAR Images of Urban Areas
Remote Sens. 2020, 12(10), 1632; https://doi.org/10.3390/rs12101632 - 20 May 2020
Abstract
Polarimetric Synthetic Aperture Radar (PolSAR) images containing cities may exhibit misclassified areas when using polarimetric decompositions. Several articles relate this problem to the effects of orientation between the facades of buildings and the acquisition trajectory. Materials also play a role in polarimetric behavior. [...] Read more.
Polarimetric Synthetic Aperture Radar (PolSAR) images containing cities may exhibit misclassified areas when using polarimetric decompositions. Several articles relate this problem to the effects of orientation between the facades of buildings and the acquisition trajectory. Materials also play a role in polarimetric behavior. This paper deals with this combined effect of material and orientation. It analyzes different sets of data, airborne or space-borne, at L-, C- and X-bands, and for different orientation angles. It shows that considering dielectric dihedral rather than metallic in the polarimetric mechanism of double-bounce has a very important impact on the differences of intensities between the channels HH and VV. This difference is very important for small angles of orientation, and then decreases for large angles. Furthermore, the curves of the ratios between polarimetric intensities as a function of the orientation angle vary little with the materials and the frequencies encountered in all the scenarios envisaged. The signal of the ratio VV/HH raises a plateau around −1 dB for orientations higher than 30°. We also observe a plateau for HV/HH, but with a value around −5 dB. Full article
(This article belongs to the Special Issue Applications of SAR Images for Urban Areas)
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