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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: 31 July 2024 | Viewed by 9820

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Special Issue Editors

Prof. Dr. Lisa Borgatti

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Department of Civil, Chemical, Environmental, and Material Engineering, Alma Mater Studiorum—University of Bologna, 40136 Bologna, Italy
Interests: geotechnics; natural hazards; remote sensing; landslide hazard
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Prof. Dr. Enrico Corrado Borgogno Mondino

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Department of Agricultural, Forest and Food Sciences, University of Turin, L.go Braccini 2, 10095 Grugliasco, Italy
Interests: remote sensing; spatial analysis and landscape planning; GIS; digital photogrammetry; precision farming; lidar
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Prof. Dr. Alessandro Corsini

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DSCG, University of Modena and Reggio Emilia, Modena, Italy
Interests: engineering geology; landslides; mapping; site investigation; multi-method monitoring; GIS and FE modeling; hazard and risk mitigation
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Dr. Daniele Giordan

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CNR IRPI, Turin, Italy
Interests: unmanned aerial vehicles; natural hazards; engineering geology
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Prof. Dr. Stefano Gandolfi

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Scool of Enginering and Architecture, DICAM - University of Bologna Viale Risorgimento 2, 40136, Bologna, Italy
Interests: GNSS; In-SAR; land subsidence; ground deformation control; monitoring
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Prof. Dr. Mauro Soldati

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DSCG, University of Modena and Reggio Emilia, Modena, Italy
Interests: geomorphology; geohazards; mapping
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Special Issue Information

Dear Colleagues,

Nowadays scientists and practitioners have an unprecedented access to a broad range of extremely powerful and diffuse tools to observe, characterize and monitor unstable slopes at various temporal and spatial scales and with different sensors. To interpret huge amounts of data and exploit results in the assessment of structural and non-structural landslide risk mitigation measures, an even deeper understanding of geological and geomorphological processes acting in mountain environments is essential. Therefore, Geoscientists should work closely together to gather, store, process, deliver and elaborate robust information with the final aim to allow the stakeholders to tackle with emerging sustainable development issues in fragile mountain areas under a changing climate.

This Special Issue aims to collect relevant and original papers regarding both innovative methods and case studies in which remote sensing and in situ techniques are integrated for landslide hazard and risk management.

Works dealing with the experimental use of novel sensors and data processing techniques are expected, along with examples integrating remote sensing data in numerical modelling exercises. For example, we elicit papers describing slope characterization and displacement monitoring, acquisition and processing of high-resolution point clouds for the detection of rock mass discontinuities and related properties, estimation of landslide movement, accumulation and depletion, volume, depth, runout prior, during and after failure.

Prof. Dr. Lisa Borgatti
Prof. Dr. Enrico Borgogno Mondino
Prof. Dr. Alessandro Corsini
Dr. Daniele Giordan
Prof. Dr. Stefano Gandolfi
Prof. Dr. Mauro Soldati
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.

Keywords

slopes
landslides
monitoring
modelling
mitigation
hazard and risk
mountain environment
remote sensing techniques
geomatics
statistical analysis

Published Papers (7 papers)

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Research

20 pages, 9183 KiB

Open AccessArticle

Rapid Assessment of Landslide Dynamics by UAV-RTK Repeated Surveys Using Ground Targets: The Ca’ Lita Landslide (Northern Apennines, Italy)

by Giuseppe Ciccarese, Melissa Tondo, Marco Mulas, Giovanni Bertolini and Alessandro Corsini

Remote Sens. 2024, 16(6), 1032; https://doi.org/10.3390/rs16061032 - 14 Mar 2024

Viewed by 492

Abstract

The combined use of Uncrewed Aerial Vehicles (UAVs) with an integrated Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) module and an external GNSS base station allows photogrammetric surveys with centimeter accuracy to be obtained without the use of ground control points. This greatly reduces acquisition and processing time, making it possible to perform rapid monitoring of landslides by installing permanent and clearly recognizable optical targets on the ground. In this contribution, we show the results obtained in the Ca’ Lita landslide (Northern Apennines, Italy) by performing multi-temporal RTK-aided UAV surveys. The landslide is a large-scale roto-translational rockslide evolving downslope into an earthslide–earthflow. The test area extends 60 × 10³ m² in the upper track zone, which has recently experienced two major reactivations in May 2022 and March 2023. A catastrophic event took place in May 2023, but it goes beyond the purpose of the present study. A total of eight UAV surveys were carried out from October 2020 to March 2023. A total of eight targets were installed transversally to the movement direction. The results, in the active portion of the landslide, show that between October 2020 and March 2023, the planimetric displacement of targets ranged from 0.09 m (in the lateral zone) to 71.61 m (in the central zone). The vertical displacement values ranged from −2.05 to 5.94 m, respectively. The estimated positioning errors are 0.01 (planimetric) and 0.03 m (vertical). The validation, performed by using data from a permanent GNSS receiver, shows maximum differences of 0.18 m (planimetric) and 0.21 m (vertical). These results, together with the rapidity of image acquisition and data processing, highlight the advantages of using this rapid method to follow the evolution of relatively rapid landslides such as the Ca’ Lita landslide. Full article

(This article belongs to the Special Issue Geomatics and Natural Hazards)

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21 pages, 6753 KiB

Open AccessArticle

Deciphering Complex Morphology and Structural Connectivity of High-Magnitude Deep-Seated Landslides via Airborne Laser Scanning: A Case Study in the Vrancea Seismic Region, Romanian Carpathians

by Mihai Micu, Mirela Vasile, Florin Miron, Alexandru Onaca, Flavius Sîrbu and Skyline Drones Team

Remote Sens. 2023, 15(22), 5286; https://doi.org/10.3390/rs15225286 - 08 Nov 2023

Viewed by 1016

Abstract

In the Vrancea seismic region (Romanian Carpathians; the most important intermediate-depth seismic source of Europe), the morphology of the slopes is often marked by the existence of numerous high-magnitude, deep-seated active, dormant or relict landslides, which are the subjects of many cases of functional and structural connectivity. Due to the compact and extensive (coniferous and broad leaved) forest coverage and because of the lack of publicly available regional high-resolution DEMs, it is usually difficult to fully understand the morphogenetic framework of such large, deep-seated landslides in order to assess their frequency–magnitude relationship, a key issue in hazard quantification. However, the high impact of such landslides on river networks requires an in-depth understanding of the multi-hazard framework, as cascading effects are likely to affect the presently growing human activities developing along the valleys. Within a case study represented by a 2.5 km long deep-seated landslide, that caused a 500 m lateral occlusion of Buzău River, we used integrated remote sensing technologies (UAV laser scanning) and in situ (geomorphic mapping and ERT investigations) techniques, which allowed us to better understand the structural connectivity which conditions the landslide hazard in such complex morphogenetic conditions, outlining the present potential of the regional seismo-climatic context to trigger potential high-magnitude chain effects. Full article

(This article belongs to the Special Issue Geomatics and Natural Hazards)

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19 pages, 11429 KiB

Open AccessEditor’s ChoiceArticle

A Laboratory for the Integration of Geomatic and Geomechanical Data: The Rock Pinnacle “Campanile di Val Montanaia”

by Luca Tavasci, Alessandro Lambertini, Davide Donati, Valentina Alena Girelli, Giovanni Lattanzi, Silvia Castellaro, Stefano Gandolfi and Lisa Borgatti

Remote Sens. 2023, 15(19), 4854; https://doi.org/10.3390/rs15194854 - 07 Oct 2023

Cited by 1 | Viewed by 1054

Abstract

This work describes a procedure for building a high-quality 3D model of a rocky pinnacle in the Dolomites, Italy, using Structure from Motion (SfM) techniques. The pinnacle, known as “Campanile di Val Montanaia”, is challenging to survey due to its high elevation and sub-vertical cliffs. The construction of the 3D model is the first step in a multi-disciplinary approach to characterize the rock mass and understand its behavior and evolution. This paper discusses the surveying operations, which involved climbing the pinnacle to collect Ground Control Points (GCPs) and using a UAV to capture aerial imagery. The photographs were processed using SfM software to generate point clouds, mesh, and texture, which were then used for rock mass discontinuity mapping. The study compares models of different qualities and point densities to determine the optimal trade-off between processing time and accuracy in terms of discontinuity mapping. The results show that higher quality models allow for more detailed mapping of discontinuities, with some drawbacks due to noise in the case of the densest solution (e.g., increase in frequency of outliers across the point cloud). These pros and cons are also discussed in relation to the computational cost necessary to build the models. The study also examines the limitations and challenges of performing discontinuity mapping in the different models, including subjectivity in interpretation. A further element of interest is the publication of a high-quality 3D georeferenced model of the “Campanile di Val Montanaia” to be used for several potential further applications, such as stability analyses and numerical modeling. Full article

(This article belongs to the Special Issue Geomatics and Natural Hazards)

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22 pages, 12397 KiB

Open AccessArticle

LiDAR Data and HRSI to Evaluate the Mitigating Effect of Forests into Rockfall Risk Analysis Using SOM: Mt San Liberatore Case Study

by Antonella Ambrosino, Alessandro Di Benedetto and Margherita Fiani

Remote Sens. 2023, 15(18), 4523; https://doi.org/10.3390/rs15184523 - 14 Sep 2023

Viewed by 783

Abstract

The aim of our work is to develop a methodology to identify the areas most prone to natural rockfall retention through the integrated use of remote sensing data. The area chosen as a case study is located in Campania (Italy) nearby Mount San Liberatore. In this area, which is itself geomorphologically predisposed to landslide risk, there are several rockfall risk hotspots, so defined because of the high exposed value constituted by an articulated infrastructure network located along the northwest slope of the mountain. The area is largely covered by dense vegetation, of which holm oak is the most representative type, characterized by a taproot apparatus that, giving it strength and stability, makes it an ideal tree for slope protection. Based on high-resolution multispectral satellite images, vegetation indices (VIs) were calculated to estimate health status, approximate age, average height, robustness, and vigor. Morphometric parameters suitable for describing slope dynamics were also calculated, derived from LiDAR data. The classification of areas with similar characteristics was carried out using Self-Organizing Maps. The results made it possible to identify all those areas where there is a greater contribution of protective forests in the mitigation of rockfall risk and, consequently, to identify areas to carry out a combined strengthening of protective actions. Full article

(This article belongs to the Special Issue Geomatics and Natural Hazards)

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23 pages, 28502 KiB

Open AccessArticle

Multitemporal Analysis of Slow-Moving Landslides and Channel Dynamics through Integrated Remote Sensing and In Situ Techniques

by Carlotta Parenti, Paolo Rossi, Francesco Mancini, Vittoria Scorpio, Francesca Grassi, Giuseppe Ciccarese, Francesca Lugli and Mauro Soldati

Remote Sens. 2023, 15(14), 3563; https://doi.org/10.3390/rs15143563 - 15 Jul 2023

Cited by 2 | Viewed by 2041

Abstract

The relationships between hillslope and fluvial processes were studied in a mountainous area of the Northern Apennines (Italy) where intermittent landslide activity has interacted for a long time with river morphodynamics. The aim of the study was to analyse such relationships in two study sites of the Scoltenna catchment. The sites were analysed in detail and monitored through time. A long-term analysis was carried out based on multitemporal photointerpretation of aerial photos. Slope morphological changes and land use modifications since 1954 were detected and compared with the evolution of the channel morphology. A short-term analysis was also performed based on two monitoring campaigns accomplished in 2021 and 2022 in order to detect possible slope displacements and channel-bed-level changes. The techniques used are global navigation satellite systems and drone photogrammetry accompanied by geomorphological surveys and mapping. The multitemporal data collected allowed us to characterise slope surface deformations and quantify morphological changes. The combination of various techniques of remote and proximal sensing proved to be a useful tool for the analysis of the surface deformations and for the investigation of the interaction between slope and fluvial dynamics, showing the important role of fluvial processes in the remobilisation of the landslide toe causing the displacement of a significant volume of sediment into the stream. Full article

(This article belongs to the Special Issue Geomatics and Natural Hazards)

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21 pages, 12031 KiB

Open AccessArticle

Detecting Recent Dynamics in Large-Scale Landslides via the Digital Image Correlation of Airborne Optic and LiDAR Datasets: Test Sites in South Tyrol (Italy)

by Melissa Tondo, Marco Mulas, Giuseppe Ciccarese, Gianluca Marcato, Giulia Bossi, David Tonidandel, Volkmar Mair and Alessandro Corsini

Remote Sens. 2023, 15(12), 2971; https://doi.org/10.3390/rs15122971 - 07 Jun 2023

Cited by 3 | Viewed by 1369

Abstract

Large-scale slow-moving deep-seated landslides are complex and potentially highly damaging phenomena. The detection of their dynamics in terms of displacement rate distribution is therefore a key point to achieve a better understanding of their behavior and support risk management. Due to their large dimensions, ranging from 1.5 to almost 4 km², in situ monitoring is generally integrated using satellite and airborne remote sensing techniques. In the framework of the EFRE-FESR SoLoMon project, three test-sites located in the Autonomous Province of Bolzano (Italy) were selected for testing the possibility of retrieving significant slope displacement data from the analysis of multi-temporal airborne optic and light detection and ranging (LiDAR) surveys with digital image correlation (DIC) algorithms such as normalized cross-correlation (NCC) and phase correlation (PC). The test-sites were selected for a number of reasons: they are relevant in terms of hazard and risk; they are representative of different type of slope movements (earth-slides, deep seated gravitational slope Deformation and rockslides), and different rates of displacement (from few cm/years to some m/years); and they have been mapped and monitored with ground-based systems for many years (DIC results can be validated both qualitatively and quantitatively). Specifically, NCC and PC algorithms were applied to high-resolution (5 to 25 cm/px) airborne optic and LiDAR-derived datasets (such as hillshade and slope maps computed from digital terrain models) acquired during the 2019–2021 period. Qualitative and quantitative validation was performed based on periodic GNSS surveys as well as on manual homologous point tracking. The displacement maps highlight that both DIC algorithms succeed in identifying and quantifying slope movements of multi-pixel magnitude in non-densely vegetated areas, while they struggle to quantify displacement patterns in areas characterized by movements of sub-pixel magnitude, especially if densely vegetated. Nonetheless, in all three landslides, they proved to be able to differentiate stable and active parts at the slope scale, thus representing a useful integration of punctual ground-based monitoring systems. Full article

(This article belongs to the Special Issue Geomatics and Natural Hazards)

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18 pages, 22455 KiB

Open AccessArticle

Integrated Approaches for Field Mapping by Traditional Investigation and Satellite PSInSAR Data: Results from the Montemartano Landslide (Central Italy)

by Lucio Di Matteo, Riccardo Cardinali, Valentina Cerboni, Fabio Guadagnano, Giorgio Piagnani, Claudia Ribaldi, Biagio Marco Sotera and Corrado Cencetti

Remote Sens. 2023, 15(5), 1221; https://doi.org/10.3390/rs15051221 - 22 Feb 2023

Cited by 1 | Viewed by 1450

Abstract

The study presents an integrated investigation of a complex landslide based on multitemporal stereo aerial photographic interpretations, existing geotechnical monitoring data, and different PSInSAR datasets. The available information allowed for the quantification of the deformation history, also in periods with no monitoring in the field, making it possible to revise the geometry of the landslide compared to the official landslide mapping. Data from sparse inclinometers are compared with more spatially continuous satellite measurements, showing that the two monitoring techniques are consistent in terms of cumulative deformation trend and in terms of response to prolonged drought and wet periods. Therefore, reliable landslide mass displacements can be monitored using satellite products when ground instrumentations are no longer operating. Understanding the landslide behavior to rainfall conditions offers an important insight into the velocities and cumulative displacements expected during similar stages of enhanced landslide activity. The findings can be helpful to support urban planners in re-evaluating hazard and risk classification and implementing efficient mitigation techniques to reduce landslide damage. Full article

(This article belongs to the Special Issue Geomatics and Natural Hazards)

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