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Special Issue "Earth Observation for Geohazards in the Era of Big Data and Cloud Computing"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: 31 March 2020.

Special Issue Editors

Guest Editor
Dr. Matteo Del Soldato

Department of Earth Sciences, University of Florence, Via La Pira, 4 - 50121 Firenze, Italy
E-Mail
Interests: landslide mapping and monitoring; land subsidence; remote sensing data interpretation; geohazard monitoring; EO techniques
Guest Editor
Dr. Federico Raspini

Department of Earth Sciences, University of Florence, Via La Pira, 4 - 50121 Firenze, Italy
E-Mail
Interests: landslide mapping and monitoring; subsidence analysis; remote sensing data interpretation; geohazard monitoring
Guest Editor
Assoc. Prof. Constantinos Loupasakis

Department of Geological Sciences, School of Mining and Metallurgical Engineering, National Technical University of Athens, Zographou Campus, GR-157 80 Athens, Greece
Website | E-Mail
Interests: geohazard study, monitoring and modeling; computational geotechnical engineering; remote sensing data interpretation
Guest Editor
Prof. Roberto Tomás

Department of Civil Engineering, University of Alicante, Campus de San Vicente del Raspeig s/n, 03080 Alicante, Spain
Website | E-Mail
Interests: landslides; land subsidence; geohazards; infrastructures; remote sensing; EO techniques

Special Issue Information

Dear Colleagues,

Every day, dozens of Earth Observation (EO) spaceborne and airborne sensors, encompassing different spectral, spatial, radiometric and temporal resolutions, provide a massive amount of remotely-sensed data. EO plays a key role in the identification, investigation and monitoring of natural phenomena, e.g., land subsidence, landslides, volcanic events or floods, as well as impacts of human activities. EO techniques become established thanks to their cost-effectiveness with respect to their high accuracy, large spatial coverage and temporal repetitiveness.

The Sentinel missions, developed within the Copernicus programme, started a process to place a constellation of at least 20 satellites in orbit before 2030 and focused on several aspects of EO, such as atmospheric, oceanic, or land monitoring, and infinite possibilities of applications for the scientific community. To date, approximatively 13 million images have been published and 200 k people have registered on the Copernicus Open Access Hub, which provides complete, free and open access to Sentinel products. So far, more than 100 k PB (Petabyte) of Sentinel data have been downloaded. The advent of Sentinel opened new opportunities for many applications, providing, on a regional scale, timely information suitable for monitoring and response for geological processes.

On the other hand, managing and computing the huge amount of data require adequate processing and storage machine. For this reason, the European Space Agency promotes different platforms (e.g., G-POD, GEP, EO browser, the DIAS platforms) for both storage and on-demand processing of satellite data, in order to create opportunities and address complex logistical challenges. Cloud-based workspaces can provide the required flexibility to manage such huge amounts of data, thus making possible analyses that were previously unfeasible, due to large data volumes and computational limitations.

The increase of the availability of the platform that implemented the cloud computing (CC) environment has encouraged companies and the scientific community operating in EO observation to take advantage of them, also due to their relative simplicity of use.

For this Special Issue, submissions are encouraged that cover a broad range of topics on the various applications of remote sensing techniques, which may include, but are not limited to, the following topics:

  • innovative applications and methods in remote sensing, significant case studies, applications and models conducted using on-demand platforms;
  • Remote sensing big data analysis for geohazard investigation and integration or fusion with other-source geospatial data (i.e., GNSS, in situ observation);
  • novel data analytics for post-processing and applications at different geographic scales;
  • multi-sensor and multi-resolution data analysis.

Dr. Matteo Del Soldato
Dr. Federico Raspini
Assoc. Prof. Constantinos Loupasakis
Prof. Roberto Tomás
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 1800 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

  • Earth Observation
  • Remote sensing
  • Geohazard investigations
  • On-demand platforms
  • Cloud computing platforms
  • Copernicus programme
  • Big data analysis

Published Papers (1 paper)

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Research

Open AccessArticle
Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets
Remote Sens. 2019, 11(14), 1675; https://doi.org/10.3390/rs11141675
Received: 24 May 2019 / Revised: 4 July 2019 / Accepted: 12 July 2019 / Published: 14 July 2019
PDF Full-text (11788 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This work describes a new procedure aimed to semi-automatically identify clusters of active persistent scatterers and preliminarily associate them with different potential types of deformational processes over wide areas. This procedure consists of three main modules: (i) ADAfinder, aimed at the detection of [...] Read more.
This work describes a new procedure aimed to semi-automatically identify clusters of active persistent scatterers and preliminarily associate them with different potential types of deformational processes over wide areas. This procedure consists of three main modules: (i) ADAfinder, aimed at the detection of Active Deformation Areas (ADA) using Persistent Scatterer Interferometry (PSI) data; (ii) LOS2HV, focused on the decomposition of Line Of Sight (LOS) displacements from ascending and descending PSI datasets into vertical and east-west components; iii) ADAclassifier, that semi-automatically categorizes each ADA into potential deformational processes using the outputs derived from (i) and (ii), as well as ancillary external information. The proposed procedure enables infrastructures management authorities to identify, classify, monitor and categorize the most critical deformations measured by PSI techniques in order to provide the capacity for implementing prevention and mitigation actions over wide areas against geological threats. Zeri, Campiglia Marittima–Suvereto and Abbadia San Salvatore (Tuscany, central Italy) are used as case studies for illustrating the developed methodology. Three PSI datasets derived from the Sentinel-1 constellation have been used, jointly with the geological map of Italy (scale 1:50,000), the updated Italian landslide and land subsidence maps (scale 1:25,000), a 25 m grid Digital Elevation Model, and a cadastral vector map (scale 1:5000). The application to these cases of the proposed workflow demonstrates its capability to quickly process wide areas in very short times and a high compatibility with Geographical Information System (GIS) environments for data visualization and representation. The derived products are of key interest for infrastructures and land management as well as decision-making at a regional scale. Full article
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