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PAZ Ciencia: Review of the Scientific Results from Radar PAZ Mission Data

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: 30 March 2025 | Viewed by 2786

Special Issue Editors

Prof. Dr. José Fernández

E-Mail Website
Guest Editor
Instituto de Geociencias IGEO (CSIC-UCM), Madrid, Spain
Interests: geodesy; InSAR; GNSS; deformation modeling; natural and anthropogenic hazards
Special Issues, Collections and Topics in MDPI journals
Dr. Antonio Turiel

E-Mail Website
Guest Editor
Instituto de Ciencias Marinas de Barcelona (CSIC) Passeig Marítim de la Barceloneta, 37-49, 08003 Barcelona, Spain
Interests: geophysical turbulence to physical oceanography; from image and signal processing to satellite remote sensing; from nonlinear physics to natural resources physical oceanography; image processing
Special Issues, Collections and Topics in MDPI journals
María José González Bonilla

E-Mail
Guest Editor Assistant
Centro Espacial INTA Torrejón, Instituto Nacional de Técnica Aeroespacial (INTA) Cª de Ajalvir, km 4, 28850 Torrejón de Ardoz, Madrid, Spain
Interests: SAR; remote sensing; satellite remote sensing; space missions; ground segment
Juan Manuel Cuerda Muñoz

E-Mail Website
Guest Editor Assistant
Centro Espacial INTA Torrejón, Instituto Nacional de Técnica Aeroespacial (INTA) Cª de Ajalvir, km 4, 28850 Torrejón de Ardoz, Madrid, Spain
Interests: remote sensing; satellite remote sensing; space missions; ground segment; SAR performances; SAR calibration; SAR image formation
Nuria Casal Vázquez

E-Mail Website
Guest Editor Assistant
Centro Espacial INTA Torrejón, Instituto Nacional de Técnica Aeroespacial (INTA) Cª de Ajalvir, km 4, 28850 Torrejón de Ardoz, Madrid, Spain
Interests: SAR; remote sensing; satellite imagery; geodesy; GNSS; maps and cartography

Special Issue Information

Dear Colleagues,

PAZ is the Spanish X-Band SAR mission, launched in 2018, that provides image products for commercial, security, defence and scientific purposes. The PAZ satellite was launched on February 22nd, 2018. After a successful LEOP and Commissioning Phase, the system was declared operational in September 2018; it is currently in the Routine Operations Phase with excellent radiometric and geometric performances. The PAZ mission is operated by HISDESAT, and its scientific use is managed by INTA (Spanish National Institute of Aerospace Technology) in the framework of PAZ Science Activities (PAZ Ciencia).

PAZ Science Activities fulfil INTA’s interest in fostering SAR science and technology, promoting the use of PAZ products for research purposes, including the development of new applications, methods or algorithms. By means of specific calls, INTA provides PAZ L1B products to research teams to be used for scientific research projects.

The aim of this Special Issue is to provide selected contributions that collect the first results obtained by PAZ Science research teams in the framework of the different PAZ Announcement of Opportunity.

Potential topics related to PAZ satellites include, but are not limited to: calibration; ground motion detection and monitoring with satellites; interferometry applications; soil surface moisture estimation; and the study of the unrest and eruption of La Palma.

SAR missions provide high-resolution, day and night and weather-independent images that are widely used for a multitude of applications covering change detection, monitoring, mapping, surveillance, geosciences, marine sciences, among others. Although SAR data and applications have been extensively used in recent decades, the scientific exploitation of SAR missions in general and of PAZ in particular allow research groups to expand the range of applications based on the use of products and to improve algorithms and methods.

Prof. Dr. José Fernández
Dr. Antonio Turiel
Guest Editors

María José González Bonilla
Juan Manuel Cuerda Muñoz
Nuria Casal Vázquez
Guest Editor Assistants

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 submissions that pass pre-check are 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 2700 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

  • synthetic aperture radar
  • SAR interferometry
  • SAR polarimetry
  • ground deformation
  • land cover
  • geo-hazards
  • hidrology

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Published Papers (2 papers)

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Research

28 pages, 27581 KiB  
Article
Analysis of Urbanization-Induced Land Subsidence in the City of Recife (Brazil) Using Persistent Scatterer SAR Interferometry
by Wendson de Oliveira Souza, Luis Gustavo de Moura Reis, Jaime Joaquim da Silva Pereira Cabral, Antonio Miguel Ruiz-Armenteros, Roberto Quental Coutinho, Admilson da Penha Pacheco and Wilson Ramos Aragão Junior
Remote Sens. 2024, 16(14), 2592; https://doi.org/10.3390/rs16142592 - 15 Jul 2024
Viewed by 916
Abstract
The article addresses anthropogenic and geological conditions related to the development of soil subsidence in the western zone of Recife (Brazil). Over the past 50 years, human activity has intensified in areas previously affected by soft soils (clay, silt, and sandstone) resulting in [...] Read more.
The article addresses anthropogenic and geological conditions related to the development of soil subsidence in the western zone of Recife (Brazil). Over the past 50 years, human activity has intensified in areas previously affected by soft soils (clay, silt, and sandstone) resulting in subsidence due to additional loads (landfills and constructions). The duration of the settlement process can be significantly influenced by the specific characteristics of the soil composition and geological conditions of the location. This work presents, for the first time, accurate InSAR time series maps that describe the spatial pattern and temporal evolution of the settlement, as well as the correlation with the geological profile, and validation with Global Navigation Satellite System (GNSS) data. Persistent Scatterer Interferometry (PS-InSAR) was employed in the analysis of Single Look Complex (SLC) images generated by 100 ascending COSMO-SkyMed (CSK) and 65 PAZ (32 ascending, and 33 descending) from the X-band, along with 135 descending Sentinel-1 (S1) acquisitions from the C-band. These data were acquired over the period from 2011 to 2023. The occurrence of subsidence was identified in several locations within the western region, with the most significant displacement rates observed in the northern, central, and southern areas. In the northern region, the displacement rates were estimated to be approximately −20 mm/year, with the Várzea and Caxangá neighborhoods exhibiting the highest rates. In the central region, the displacement rates were estimated to be approximately −15 mm/year, with the Engenho do Meio, Cordeiro, Torrões, and San Martin neighborhoods exhibiting the highest rates. Finally, in the southern region, the displacement rates were estimated to be up to −25 mm/year, with the Caçote, Ibura, and Ipsep neighborhoods exhibiting the highest rates. Additionally, east–west movements were observed, with velocities reaching up to −7 mm/year toward the west. These movements are related to the lowering of the land. The study highlights that anthropogenic effects in the western zone of Recife contribute to the region’s vulnerability to soil subsidence. Full article
(This article belongs to the Special Issue PAZ Ciencia: Review of the Scientific Results from Radar PAZ Mission Data)
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20 pages, 7776 KiB  
Article
Oil Tank Detection and Recognition via Monogenic Signal
by Yunqing Fan, Junjun Yin and Jian Yang
Remote Sens. 2024, 16(4), 676; https://doi.org/10.3390/rs16040676 - 14 Feb 2024
Cited by 1 | Viewed by 912
Abstract
With the rapid development of synthetic aperture radar (SAR) techniques, satellite systems’ capabilities to acquire information are continually improving. The PAZ satellite, with its high resolution and wide scanning swath, can provide high-quality data support for SAR applications. Oil tanks serve as energy [...] Read more.
With the rapid development of synthetic aperture radar (SAR) techniques, satellite systems’ capabilities to acquire information are continually improving. The PAZ satellite, with its high resolution and wide scanning swath, can provide high-quality data support for SAR applications. Oil tanks serve as energy storage devices, and their identification holds significant value in both military and civilian fields. Challenges in the detection and recognition of oil tanks using classical methods include poor detection, slow computation speed, and multiple windows of correct recognition. This paper centers on the analysis of oil tanks using PAZ data. We employ a sliding-window approach to acquire candidate target windows, process the windows through Weibull distribution modeling and hole filling, and extract target features using the monogenic signal based on regional L2 norm. The results demonstrate that the proposed method effectively improves the accuracy, and the model exhibits strong generalization ability and robustness. Full article
(This article belongs to the Special Issue PAZ Ciencia: Review of the Scientific Results from Radar PAZ Mission Data)
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