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Multitemporal Remote Sensing: Methods and Applications for Geomorphology and Engineering Geology

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

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 9405

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Special Issue Editors

Prof. Alessandro Corsini

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Guest Editor

Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Modena, Italy
Interests: engineering geology; landslides; mapping; site investigation; multi-methods monitoring; GIS and FE modeling; hazard and risk mitigation; Alps; Apennines

Dr. Marco Mulas

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Guest Editor

Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Modena, Italy
Interests: engineering geology; landslides; remote sensing; multitemporal InSAR; total station; GNSS; data analysis; early warning systems

Special Issue Information

Dear Colleagues,

In the recent decades, remote sensing has been proven to be a powerful tool in many scientific branches. The fact that sessions dealing with remote sensing applications are present at almost all international scientific conferences of the Geomorphology and Engineering Geology communities confirms its important role in understanding earth surface processes and for hazard and risk assessment.

Remotely sensed multitemporal datasets can be populated by stacks acquired using satellites (passive or active sensors), proximal sensors carried on airplanes and unmanned aerial vehicles (UAV), or by ground-based sensors (i.e., laser scanners and thermal cameras). Remote sensing applications and analysis are increasingly being carried out using available open source or freely distributed software or packages.

This Special Issue of Remote Sensing aims to collect relevant and original papers regarding methods and applications of multitemporal remote sensing in the fields of Geomorphology and Engineering Geology. More specifically, manuscripts dealing with novel applications, case studies, and new methodologies for remotely sensed data analysis or data validation are welcome.

Prof. Alessandro Corsini
Dr. Marco Mulas
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 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.

Published Papers (3 papers)

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17 pages, 8232 KiB

Open AccessArticle

Integration of Satellite InSAR with a Wireless Network of Geotechnical Sensors for Slope Monitoring in Urban Areas: The Pariana Landslide Case (Massa, Italy)

by Andrea Ciampalini, Paolo Farina, Luca Lombardi, Massimiliano Nocentini, Veronica Taurino, Roberto Guidi, Fernando della Pina and Davide Tavarini

Remote Sens. 2021, 13(13), 2534; https://doi.org/10.3390/rs13132534 - 29 Jun 2021

Cited by 6 | Viewed by 2392

Abstract

Slow to extremely slow landslides in urban areas may cause severe damage to buildings and infrastructure that can lead to the evacuation of local populations in case of slope accelerations. Monitoring the spatial and temporal evolution of this type of natural hazard represents a major concern for the public authorities in charge of risk management. Pariana, a village with 400 residents located in the Apuan Alps (Massa, Tuscany, Italy), is an example of urban settlement where the population has long been forced to live with considerable slope instability. In the last 30 years, due to the slope movements associated with a slow-moving landslide that has affected a significant portion of the built-up area, several buildings have been damaged, including a school and the provincial road crossing the unstable area, leading to the need for an installation of a slope monitoring system with early warning capabilities, in parallel with the implementation of mitigation works. In this paper, we show how satellite multi-temporal interferometric synthetic aperture radar (MT-InSAR) data can be effectively used when coupled with a wireless sensor network made of several bar extensometers and a borehole inclinometer. In fact, thanks to their wide area coverage and opportunistic nature, satellite InSAR data allow one to clearly identify the spatial distribution of surface movements and their long-term temporal evolution. On the other hand, geotechnical sensors installed on specific elements at risk (e.g., private buildings, retaining walls, etc.), and collected through Wi-Fi dataloggers, provide near real-time data that can be used to identify sudden accelerations in slope movements, subsequently triggering alarms. The integration of those two-monitoring systems has been tested and assessed in Pariana. Results show how a hybrid slope monitoring program based on the two different technologies can be used to effectively monitor slow-moving landslides and to identify sudden accelerations and activate a response plan. Full article

(This article belongs to the Special Issue Multitemporal Remote Sensing: Methods and Applications for Geomorphology and Engineering Geology)

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25 pages, 69215 KiB

Open AccessArticle

Debris Flow and Rockslide Analysis with Advanced Photogrammetry Techniques Based on High-Resolution RPAS Data. Ponte Formazza Case Study (NW Alps)

by Davide Notti, Daniele Giordan, Alberto Cina, Ambrogio Manzino, Paolo Maschio and Iosif Horea Bendea

Remote Sens. 2021, 13(9), 1797; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13091797 - 05 May 2021

Cited by 9 | Viewed by 3418

Abstract

The use of a Remotely Piloted Aircraft System (RPAS) for the characterization and monitoring of landslides has been widely improved in the last decade. In particular, the use of this system is particularly effective for the study of areas prone to geohazards. Zones affected by landslides, such as rock slides and debris flows, are often quite critical in terms of accessibility due to unstable blocs that can strongly limit the direct access to the studied area. In this paper, we present the case study of Ponte Formazza in NW Italian Alps. In June 2019, a massive and complex debris flow re-mobilized about 300,000 m³ of a rockslide deposit that occurred in 2009. In this particular environment, we tested traditional, direct and mixed photogrammetric approaches using various configurations of Ground Control Points (GCPs) of the photogrammetric block and by calculating the relative errors. The minimum configuration of GCPs was established to reduce in situ measurements without degrading the accuracy of the cartographic products. The images of three RPAS campaigns (2017, 2018 and 2019), processed with a Structure from Motion (SfM) technique, allowed us to obtain very high-resolution orthophoto and digital surface models (DSMs) before and after the 2019 event. A few GCPs, geolocated with a Global Navigation Satellite System (GNSS), improved the orthophoto and DSM quality (Root Mean Squared Error RMSE 5 cm) even in the areas far from the drone deployment. The availability of high-resolution models has been fundamental for the identification of the volume changes. Furthermore, the 3D view supported and completed the geomorphological mapping of affected areas, particularly in the areas where the field survey is dangerous. The use of ancillary meteorological data and Sentinel-2 satellite images allows for a better definition of the kinematics and the predisposal and triggering factors of the 2019 debris flow. Full article

(This article belongs to the Special Issue Multitemporal Remote Sensing: Methods and Applications for Geomorphology and Engineering Geology)

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24 pages, 14419 KiB

Open AccessArticle

Increasing Spatio-Temporal Resolution for Monitoring Alpine Solifluction Using Terrestrial Laser Scanners and 3D Vector Fields

by Christoph Holst, Jannik Janßen, Berit Schmitz, Martin Blome, Malte Dercks, Anna Schoch-Baumann, Jan Blöthe, Lothar Schrott, Heiner Kuhlmann and Tomislav Medic

Remote Sens. 2021, 13(6), 1192; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13061192 - 20 Mar 2021

Cited by 14 | Viewed by 2795

Abstract

This article investigates the usage of terrestrial laser scanner (TLS) point clouds for monitoring the gradual movements of soil masses due to freeze–thaw activity and water saturation, commonly referred to as solifluction. Solifluction is a geomorphic process which is characteristic for hillslopes in (high-)mountain areas, primarily alpine periglacial areas and the arctic. The movement can reach millimetre-to-centimetre per year velocities, remaining well below the typical displacement mangitudes of other frequently monitored natural objects, such as landslides and glaciers. Hence, a better understanding of solifluction processes requires increased spatial and temporal resolution with relatively high measurement accuracy. To that end, we developed a workflow for TLS point cloud processing, providing a 3D vector field that can capture soil mass displacement due to solifluction with high fidelity. This is based on the common image-processing techniques of feature detection and tracking. The developed workflow is tested on a study area placed in Hohe Tauern range of the Austrian Alps with a prominent assemblage of solifluction lobes. The derived displacements were compared with the established geomonitoring approach with total station and signalized markers and point cloud deformation monitoring approaches. The comparison indicated that the achieved results were in the same accuracy range as the established methods, with an advantage of notably higher spatial resolution. This improvement allowed for new insights considering the solifluction processes. Full article

(This article belongs to the Special Issue Multitemporal Remote Sensing: Methods and Applications for Geomorphology and Engineering Geology)

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