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Remote Sensing for Landslides Investigation: From Research into Practice
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Remote Sensing for Landslides Investigation: From Research into Practice

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (15 February 2013) | Viewed by 142115

Special Issue Editor

Prof. Dr. Marco Scaioni

E-Mail Website1 Website2
Guest Editor
Department of architecture, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133 Milano, Italy
Interests: photogrammetry; geomatics for geosciences; remote sensing of the built environment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years the use of remote sensing techniques has largely proved to support and improve the analyses of large mass movements like landslides and debris-flows. The capability of collecting multiple data source on very large areas and the development of processing techniques has resulted in an impressive growth of applications, in some cases already integrated into the routinely procedures of institutions focusing at hazard management. Application of remote sensing to landslide investigation can be categorized in three main aspects: 1) landslide recognition, inventory mapping, hazard zonation and susceptibility mapping; 2) landslide spatial analysis and prediction; and 3) landslide monitoring. This special issue would like to collect papers which highlight advancements in these topics, showing the state-of-the-art and some excellent research achievements.

Prof. Dr. Marco Scaioni
Guest Editor

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

The topics of the papers should focus on, but are not limited to:
  • accurate remote mapping of potential debris flow volumes
  • application of Digital Elevation Models and LiDAR sensors
  • application of high-resolution and short return-time SAR satellite systems (ALOS, TerraSat-X, Radarsat-2, Cosmo/SkyMed)
  • automated landslide inventory mapping
  • data assimilation
  • data cross-validation, including in situ assessment
  • data downstream services
  • follow-up of remote sensing techniques into current practices
  • ground-based remote sensing techniques
  • high-resolution satellite optical images for stereo-interpretation
  • motion mapping based on high-resolution imagery and integration with DInSAR techniques;
  • remote sensing and GIS for geospatial information systems
  • remote sensing techniques and sensor networks
  • thermal remote sensing
  • UAV remote sensing

Published Papers (15 papers)

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Editorial

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172 KiB  
Editorial
Remote Sensing for Landslide Investigations: From Research into Practice
by Marco Scaioni
Remote Sens. 2013, 5(11), 5488-5492; https://doi.org/10.3390/rs5115488 - 25 Oct 2013
Cited by 24 | Viewed by 5800
Abstract
The relevant impact [1] that landslide geo-hazards may have on society in terms of human lives and economic losses, has resulted in great efforts to develop sustainable solutions to deal with their prediction and mitigation. To date, several aspects have been investigated involving [...] Read more.
The relevant impact [1] that landslide geo-hazards may have on society in terms of human lives and economic losses, has resulted in great efforts to develop sustainable solutions to deal with their prediction and mitigation. To date, several aspects have been investigated involving geological and geo-statistical analysis, geotechnical modeling, design of effective mitigation and protection structures, and sensor development [2]. [...] Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)

Research

Jump to: Editorial

5476 KiB  
Article
Damage to Buildings in Large Slope Rock Instabilities Monitored with the PSInSAR™ Technique
by Paolo Frattini, Giovanni B. Crosta and Jacopo Allievi
Remote Sens. 2013, 5(10), 4753-4773; https://doi.org/10.3390/rs5104753 - 25 Sep 2013
Cited by 42 | Viewed by 8499
Abstract
The slow movement of active deep-seated slope gravitational deformations (DSGSDs) and deep-seated rockslides can cause damage to structures and infrastructures. We use Permanent Scatterers Synthetic Aperture Radar Interferometry (PSInSAR™) displacement rate data for the analysis of DSGSD/rockslide activity and kinematics and for the [...] Read more.
The slow movement of active deep-seated slope gravitational deformations (DSGSDs) and deep-seated rockslides can cause damage to structures and infrastructures. We use Permanent Scatterers Synthetic Aperture Radar Interferometry (PSInSAR™) displacement rate data for the analysis of DSGSD/rockslide activity and kinematics and for the analysis of damage to buildings. We surveyed the degree of damage to buildings directly in the field, and we tried to correlate it with the superficial displacement rate obtained by the PSInSAR™ technique at seven sites. Overall, we observe that the degree of damage increases with increasing displacement rate, but this trend shows a large dispersion that can be due to different causes, including: the uncertainty in the attribution of the degree of damage for buildings presenting wall coatings; the complexity of the deformation for large phenomena with different materials and subjected to differential behavior within the displaced mass; the absence of differential superficial movements in buildings, due to the large size of the investigated phenomena; and the different types of buildings and their position along the slope or relative to landslide portions. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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4897 KiB  
Article
Landslide Investigation with Remote Sensing and Sensor Network: From Susceptibility Mapping and Scaled-down Simulation towards in situ Sensor Network Design
by Gang Qiao, Ping Lu, Marco Scaioni, Shuying Xu, Xiaohua Tong, Tiantian Feng, Hangbin Wu, Wen Chen, Yixiang Tian, Weian Wang and Rongxing Li
Remote Sens. 2013, 5(9), 4319-4346; https://doi.org/10.3390/rs5094319 - 06 Sep 2013
Cited by 51 | Viewed by 11343
Abstract
This paper presents an integrated approach to landslide research based on remote sensing and sensor networks. This approach is composed of three important parts: (i) landslide susceptibility mapping using remote-sensing techniques for susceptible determination of landslide spots; (ii) scaled-down landslide simulation experiments for [...] Read more.
This paper presents an integrated approach to landslide research based on remote sensing and sensor networks. This approach is composed of three important parts: (i) landslide susceptibility mapping using remote-sensing techniques for susceptible determination of landslide spots; (ii) scaled-down landslide simulation experiments for validation of sensor network for landslide monitoring, and (iii) in situ sensor network deployment for intensified landslide monitoring. The study site is the Taziping landslide located in Hongkou Town (Sichuan, China). The landslide features generated by landslides triggered by the 2008 Wenchuan Earthquake were first extracted by means of object-oriented methods from the remote-sensing images before and after the landslides events. On the basis of correlations derived between spatial distribution of landslides and control factors, the landslide susceptibility mapping was carried out using the Artificial Neural Network (ANN) technique. Then the Taziping landslide, located in the above mentioned study area, was taken as an example to design and implement a scaled-down landslide simulation platform in Tongji University (Shanghai, China). The landslide monitoring sensors were carefully investigated and deployed for rainfall induced landslide simulation experiments. Finally, outcomes from the simulation experiments were adopted and employed to design the future in situ sensor network in Taziping landslide site where the sensor deployment is being implemented. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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2920 KiB  
Article
Exploitation of Large Archives of ERS and ENVISAT C-Band SAR Data to Characterize Ground Deformations
by Chiara Del Ventisette, Andrea Ciampalini, Michele Manunta, Fabiana Calò, Luca Paglia, Francesca Ardizzone, Alessandro Cesare Mondini, Paola Reichenbach, Rosa Maria Mateos, Silvia Bianchini, Immaculada Garcia, Balázs Füsi, Zsuzsa Villő Deák, Károly Rádi, Marek Graniczny, Zbigniew Kowalski, Anna Piatkowska, Maria Przylucka, Hugo Retzo, Tazio Strozzi, Davide Colombo, Oscar Mora, Francisco Sánchez, Gerardo Herrera, Sandro Moretti, Nicola Casagli and Fausto Guzzettiadd Show full author list remove Hide full author list
Remote Sens. 2013, 5(8), 3896-3917; https://doi.org/10.3390/rs5083896 - 08 Aug 2013
Cited by 51 | Viewed by 10453
Abstract
In the last few years, several advances have been made in the use of radar images to detect, map and monitor ground deformations. DInSAR (Differential Synthetic Aperture Radar Interferometry) and A-DInSAR/PSI (Advanced DInSAR/Persistent Scatterers Interferometry) technologies have been successfully applied in the study [...] Read more.
In the last few years, several advances have been made in the use of radar images to detect, map and monitor ground deformations. DInSAR (Differential Synthetic Aperture Radar Interferometry) and A-DInSAR/PSI (Advanced DInSAR/Persistent Scatterers Interferometry) technologies have been successfully applied in the study of deformation phenomena induced by, for example, active tectonics, volcanic activity, ground water exploitation, mining, and landslides, both at local and regional scales. In this paper, the existing European Space Agency (ESA) archives (acquired as part of the FP7-DORIS project), which were collected by the ERS-1/2 and ENVISAT satellites operating in the microwave C-band, were analyzed and exploited to understand the dynamics of landslide and subsidence phenomena. In particular, this paper presents the results obtained as part of the FP7-DORIS project to demonstrate that the full exploitation of very long deformation time series (more than 15 years) can play a key role in understanding the dynamics of natural and human-induced hazards. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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1920 KiB  
Article
Slope Stability Assessment of the Sarcheshmeh Landslide, Northeast Iran, Investigated Using InSAR and GPS Observations
by Mehrdad Akbarimehr, Mahdi Motagh and Mahmud Haghshenas-Haghighi
Remote Sens. 2013, 5(8), 3681-3700; https://doi.org/10.3390/rs5083681 - 25 Jul 2013
Cited by 52 | Viewed by 11216
Abstract
The detection and monitoring of mass movement of susceptible slopes plays a key role in mitigating hazards and potential damage associated with creeping slopes and landslides. In this paper, we use observations from both Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System [...] Read more.
The detection and monitoring of mass movement of susceptible slopes plays a key role in mitigating hazards and potential damage associated with creeping slopes and landslides. In this paper, we use observations from both Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS) to assess the slope stability of the Sarcheshmeh ancient landslide in the North Khorasan province of northeast Iran. InSAR observations were obtained by the time-series analysis of Envisat SAR images covering 2004–2006, whereas repeated GPS observations were conducted by campaign measurements during 2010–2012. Surface displacement maps of the Sarcheshmeh landslide obtained from InSAR and GPS are both indicative of slope stability. Hydrogeological analysis suggests that the multi-year drought and lower than average precipitation levels over the last decade might have contributed to the current dormancy of the Sarcheshmeh landslide. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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35996 KiB  
Article
Landslide Displacement Monitoring Using 3D Range Flow on Airborne and Terrestrial LiDAR Data
by Sajid Ghuffar, Balázs Székely, Andreas Roncat and Norbert Pfeifer
Remote Sens. 2013, 5(6), 2720-2745; https://doi.org/10.3390/rs5062720 - 29 May 2013
Cited by 62 | Viewed by 10877
Abstract
An active landslide in Doren, Austria, has been studied by multitemporal airborne and terrestrial laser scanning from 2003 to 2012. To evaluate the changes, we have determined the 3D motion using the range flow algorithm, an established method in computer vision, but not [...] Read more.
An active landslide in Doren, Austria, has been studied by multitemporal airborne and terrestrial laser scanning from 2003 to 2012. To evaluate the changes, we have determined the 3D motion using the range flow algorithm, an established method in computer vision, but not yet used for studying landslides. The generated digital terrain models are the input for motion estimation; the range flow algorithm has been combined with the coarse-to-fine resolution concept and robust adjustment to be able to determine the various motions over the landslide. The algorithm yields fully automatic dense 3D motion vectors for the whole time series of the available data. We present reliability measures for determining the accuracy of the estimated motion vectors, based on the standard deviation of components. The differential motion pattern is mapped by the algorithm: parts of the landslide show displacements up to 10 m, whereas some parts do not change for several years. The results have also been compared to pointwise reference data acquired by independent geodetic measurements; reference data are in good agreement in most of the cases with the results of range flow algorithm; only some special points (e.g., reflectors fixed on trees) show considerably differing motions. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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3303 KiB  
Article
Characterization of Landslide Deformations in Three Gorges Area Using Multiple InSAR Data Stacks
by Peraya Tantianuparp, Xuguo Shi, Lu Zhang, Timo Balz and Mingsheng Liao
Remote Sens. 2013, 5(6), 2704-2719; https://doi.org/10.3390/rs5062704 - 28 May 2013
Cited by 63 | Viewed by 9295
Abstract
In the areas with steep topography and vulnerable geological condition, landslide deformation monitoring is an important task for risk assessment and management. Differential Synthetic-Aperture Radar interferometry (D-InSAR) and Persistent Scatterer Interferometry (PS-InSAR) are two advanced SAR Interferometry techniques for detection, analysis and monitoring [...] Read more.
In the areas with steep topography and vulnerable geological condition, landslide deformation monitoring is an important task for risk assessment and management. Differential Synthetic-Aperture Radar interferometry (D-InSAR) and Persistent Scatterer Interferometry (PS-InSAR) are two advanced SAR Interferometry techniques for detection, analysis and monitoring of slow moving landslides. The techniques can be used to identify wide displacement areas and measure displacement rates over long time series with millimeter-level accuracy. In this paper, multiple SAR datasets of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) and Environmental Satellite (ENVISAT) C-band Advanced Synthetic Aperture Radar (ASAR) are used for landslide monitoring with both D-InSAR and PS-InSAR techniques in Badong at the Three Gorges area in China. Two areas of significant deformation along the southern riverbank of Yangtze River in Badong are identified by joint analyses of PS-InSAR results from different data stacks. Furthermore, both qualitative and quantitative evaluations of the PS-InSAR results are carried out together with preliminary correlation analysis between the time series deformation of a PS point in high risk location and the temporal variation of water level in the Three Gorges Reservoir. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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13944 KiB  
Article
Supervised Method of Landslide Inventory Using Panchromatic SPOT5 Images and Application to the Earthquake-Triggered Landslides of Pisco (Peru, 2007, Mw8.0)
by Pascal Lacroix, Bilberto Zavala, Etienne Berthier and Laurence Audin
Remote Sens. 2013, 5(6), 2590-2616; https://doi.org/10.3390/rs5062590 - 23 May 2013
Cited by 47 | Viewed by 8701
Abstract
Earthquake is one of the dominant triggering factors of landslides. Given the wide areas covered by mega earthquake-triggered landslides, their inventory requires development of automatic or semi-automatic methods applied to satellite imagery. A detection method is here proposed for this purpose, to fit [...] Read more.
Earthquake is one of the dominant triggering factors of landslides. Given the wide areas covered by mega earthquake-triggered landslides, their inventory requires development of automatic or semi-automatic methods applied to satellite imagery. A detection method is here proposed for this purpose, to fit with simple datasets; SPOT5 panchromatic images of 5 m resolution coupled with a freely and globally available DEM. The method takes advantage of multi-temporal images to detect changes based on radiometric variations after precise coregistration/orthorectification. Removal of false alarms is then undertaken using shape, orientation and radiometric properties of connected pixels defining objects. 80% of the landslides and 93% of the landslide area are detected indicating small omission errors but 50% of false alarms remain. They are removed using expert based analysis of the inventory. The method is applied to realize the first comprehensive inventory of landslides triggered by the Pisco earthquake (Peru, 15/08/2007, Mw 8.0) over an area of 27,000 km2. 866 landslides larger than 100 m2 are detected covering a total area of 1.29 km2. The area/number distribution follows a power-law with an exponent of 1.63, showing a very particular regime of triggering in this arid environment compared to other areas in the world. This specific triggering can be explained by the little soil cover in the coastal and forearc regions of Peru. Analysis of this database finally shows a major control of the topography (both orientation and inclination) on the repartition of the Pisco-triggered landslides. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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1695 KiB  
Article
Topographic Correction of Wind-Driven Rainfall for Landslide Analysis in Central Taiwan with Validation from Aerial and Satellite Optical Images
by Jin-King Liu and Peter T.Y. Shih
Remote Sens. 2013, 5(6), 2571-2589; https://doi.org/10.3390/rs5062571 - 23 May 2013
Cited by 30 | Viewed by 7186
Abstract
Rainfall intensity plays an important role in landslide prediction especially in mountain areas. However, the rainfall intensity of a location is usually interpolated from rainfall recorded at nearby gauges without considering any possible effects of topographic slopes. In order to obtain reliable rainfall [...] Read more.
Rainfall intensity plays an important role in landslide prediction especially in mountain areas. However, the rainfall intensity of a location is usually interpolated from rainfall recorded at nearby gauges without considering any possible effects of topographic slopes. In order to obtain reliable rainfall intensity for disaster mitigation, this study proposes a rainfall-vector projection method for topographic-corrected rainfall. The topographic-corrected rainfall is derived from wind speed, terminal velocity of raindrops, and topographical factors from digital terrain model. In addition, scatter plot was used to present landslide distribution with two triggering factors and kernel density analysis is adopted to enhance the perception of the distribution. Numerical analysis is conducted for a historic event, typhoon Mindulle, which occurred in 2004, in a location in central Taiwan. The largest correction reaches 11%, which indicates that topographic correction is significant. The corrected rainfall distribution is then applied to the analysis of landslide triggering factors. The result with corrected rainfall distribution provides better agreement with the actual landslide occurrence than the result without correction. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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1473 KiB  
Article
Interpretation of Aerial Photographs and Satellite SAR Interferometry for the Inventory of Landslides
by Tazio Strozzi, Christian Ambrosi and Hugo Raetzo
Remote Sens. 2013, 5(5), 2554-2570; https://doi.org/10.3390/rs5052554 - 22 May 2013
Cited by 57 | Viewed by 8659
Abstract
An inventory of landslides with an indication of the state of activity is necessary in order to establish hazard maps. We combine interpretation of aerial photographs and information on surface displacement from satellite Synthetic Aperture Radar (SAR) interferometry for mapping landslides and intensity [...] Read more.
An inventory of landslides with an indication of the state of activity is necessary in order to establish hazard maps. We combine interpretation of aerial photographs and information on surface displacement from satellite Synthetic Aperture Radar (SAR) interferometry for mapping landslides and intensity classification. Sketch maps of landslides distinguished by typology and depth, including geomorphological features, are compiled by stereoscopic photo-interpretation. Results achieved with differential SAR interferometry (InSAR) and Persistent Scatterer Interferometry (PSI) are used to estimate the state of activity of landslides around villages and in sparsely vegetated areas with numerous exposed rocks. For validation and possible extension of the inventory around vegetated areas, where InSAR and PSI failed to retrieve displacement information, traditional monitoring data such as topographic measurements and GPS are considered. Our results, covering extensive areas, are a valuable contribution towards the analysis of landslide hazards in areas where traditional monitoring techniques are sparse or unavailable. In this contribution we discuss our methodology for a study area around the deep-seated landslide in Osco in southern Switzerland. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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1522 KiB  
Article
Automated Extraction of Shallow Erosion Areas Based on Multi-Temporal Ortho-Imagery
by Christoph Wiegand, Martin Rutzinger, Kati Heinrich and Clemens Geitner
Remote Sens. 2013, 5(5), 2292-2307; https://doi.org/10.3390/rs5052292 - 13 May 2013
Cited by 12 | Viewed by 6709
Abstract
In several areas of the Alps, steep grassland is characterized by shallow erosions. These erosions represent a hazard through the increased availability of unconsolidated material in steep locations, loss of soil and impaired landscape aesthetics. Generally, the erosions concern only small areas but [...] Read more.
In several areas of the Alps, steep grassland is characterized by shallow erosions. These erosions represent a hazard through the increased availability of unconsolidated material in steep locations, loss of soil and impaired landscape aesthetics. Generally, the erosions concern only small areas but sometimes occur in large numbers. Remote sensing technologies have emerged as suitable tools to study the spatio-temporal changes of these eroded areas. The detection of such eroded areas is often done by manual digitalization of aerial photographs, which is labour-intensive and includes a certain risk of subjectivity. In this study we present a methodological tool that allows the automatic classification of shallow erosions on the basis of orthophoto series. The approach was carried out within a test site in the inner Schmirn Valley, Austria. The study covers both the detection of erosion areas and a multi-temporal analysis of the geomorphological changes. The presented approach is an appropriate tool for detecting shallow erosions and for analysing them in multi-temporal terms. The multi-temporal analysis revealed one period of higher increases in eroded areas compared to shrinking during the other periods. However, the analysis of the change of all single erosions indicates that in each study period there was both increase and decrease of erosion areas. The differences in the rates of increase between the observation years are most likely due to the irregular occurrence of events that encourage erosion. In contrast, the rates of decrease are almost constant and suggest a continuous rate of recovery. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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1179 KiB  
Article
Remote Sensing and Geodetic Measurements for Volcanic Slope Monitoring: Surface Variations Measured at Northern Flank of La Fossa Cone (Vulcano Island, Italy)
by Arianna Pesci, Giordano Teza, Giuseppe Casula, Massimo Fabris and Alessandro Bonforte
Remote Sens. 2013, 5(5), 2238-2256; https://doi.org/10.3390/rs5052238 - 13 May 2013
Cited by 21 | Viewed by 7287
Abstract
Results of recent monitoring activities on potentially unstable areas of the NW volcano flank of La Fossa cone (Vulcano Island, Italy) are shown here. They are obtained by integration of data by aerial photogrammetry, terrestrial laser scanning (TLS) and GPS taken in the [...] Read more.
Results of recent monitoring activities on potentially unstable areas of the NW volcano flank of La Fossa cone (Vulcano Island, Italy) are shown here. They are obtained by integration of data by aerial photogrammetry, terrestrial laser scanning (TLS) and GPS taken in the 1996–2011 time span. A comparison between multi-temporal models built from remote sensing data (photogrammetry and TLS) highlights areas characterized by ~7–10 cm/y positive differences (i.e., elevation increase) in the upper crown of the slope. The GPS measurements confirm these results. Areas characterized by negative differences, related to both mass collapses or small surface lowering, also exist. The higher differences, positive and negative, are always observed in zones affected by higher fumarolic activity. In the 2010–2012 time span, ground motions in the northern part of the crater rim, immediately above the upper part of observed area, are also observed. The results show different trends for both vertical and horizontal displacements of points distributed along the rim, with a magnitude of some centimeters, thus revealing a complex kinematics. A slope stability analysis shows that the safety factors estimated from these data do not indicate evidence of possible imminent failures. Nevertheless, new time series are needed to detect possible changes with the time of the stability conditions, and the monitoring has to go on. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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2736 KiB  
Article
Combining Spatial Models for Shallow Landslides and Debris-Flows Prediction
by Roberto Arnaldo Trancoso Gomes, Renato Fontes Guimarães, Osmar Abílio De Carvalho, Júnior, Nelson Ferreira Fernandes and Eurípedes Vargas Do Amaral Júnior
Remote Sens. 2013, 5(5), 2219-2237; https://doi.org/10.3390/rs5052219 - 10 May 2013
Cited by 52 | Viewed by 10539
Abstract
Mass movements in Brazil are common phenomena, especially during strong rainfall events that occur frequently in the summer season. These phenomena cause losses of lives and serious damage to roads, bridges, and properties. Moreover, the illegal occupation by slums on the slopes around [...] Read more.
Mass movements in Brazil are common phenomena, especially during strong rainfall events that occur frequently in the summer season. These phenomena cause losses of lives and serious damage to roads, bridges, and properties. Moreover, the illegal occupation by slums on the slopes around the cities intensifies the effect of the mass movement. This study aimed to develop a methodology that combines models of shallow landslides and debris-flows in order to create a map with landslides initiation and debris-flows volume and runout distance. The study area comprised of two catchments in Rio de Janeiro city: Quitite and Papagaio that drained side by side the west flank of the Maciço da Tijuca, with an area of 5 km2. The method included the following steps: (a) location of the susceptible areas to landslides using SHALSTAB model; (b) determination of rheological parameters of debris-flow from the back-analysis technique; and (c) combination of SHALSTAB and FLO-2D models to delineate the areas more susceptible to mass movements. These scenarios were compared with the landslide and debris-flow event of February 1996. Many FLO-2D simulations were exhaustively made to estimate the rheological parameters from the back-analysis technique. Those rheological coefficients of single simulation were back-calculated by adjusting with area and depth of the debris-flow obtained from field data. The initial material volume in the FLO-2D simulations was estimated from SHALSTAB model. The combination of these two mathematical models, SHALSTAB and FLO-2D, was able to predict both landslides and debris-flow events. Such procedures can reduce the casualties and property damage, delineating hazard areas, to estimate hazard intensities for input into risk studies providing information for public policy and planning. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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1863 KiB  
Article
Persistent Scatterer Interferometry (PSI) Technique for Landslide Characterization and Monitoring
by Veronica Tofani, Federico Raspini, Filippo Catani and Nicola Casagli
Remote Sens. 2013, 5(3), 1045-1065; https://doi.org/10.3390/rs5031045 - 01 Mar 2013
Cited by 230 | Viewed by 14653
Abstract
: The measurement of landslide superficial displacement often represents the most effective method for defining its behavior, allowing one to observe the relationship with triggering factors and to assess the effectiveness of the mitigation measures. Persistent Scatterer Interferometry (PSI) represents a powerful tool [...] Read more.
: The measurement of landslide superficial displacement often represents the most effective method for defining its behavior, allowing one to observe the relationship with triggering factors and to assess the effectiveness of the mitigation measures. Persistent Scatterer Interferometry (PSI) represents a powerful tool to measure landslide displacement, as it offers a synoptic view that can be repeated at different time intervals and at various scales. In many cases, PSI data are integrated with in situ monitoring instrumentation, since the joint use of satellite and ground-based data facilitates the geological interpretation of a landslide and allows a better understanding of landslide geometry and kinematics. In this work, PSI interferometry and conventional ground-based monitoring techniques have been used to characterize and to monitor the Santo Stefano d’Aveto landslide located in the Northern Apennines, Italy. This landslide can be defined as an earth rotational slide. PSI analysis has contributed to a more in-depth investigation of the phenomenon. In particular, PSI measurements have allowed better redefining of the boundaries of the landslide and the state of activity, while the time series analysis has permitted better understanding of the deformation pattern and its relation with the causes of the landslide itself. The integration of ground-based monitoring data and PSI data have provided sound results for landslide characterization. The punctual information deriving from inclinometers can help in defining the actual location of the sliding surface and the involved volumes, while the measuring of pore water pressure conditions or water table level can suggest a correlation between the deformation patterns and the triggering factors. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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2477 KiB  
Article
River Courses Affected by Landslides and Implications for Hazard Assessment: A High Resolution Remote Sensing Case Study in NE Iraq–W Iran
by Arsalan A. Othman and Richard Gloaguen
Remote Sens. 2013, 5(3), 1024-1044; https://doi.org/10.3390/rs5031024 - 01 Mar 2013
Cited by 34 | Viewed by 9719
Abstract
The objective of this study is to understand the effect of landslides on the drainage network within the area of interest. We thus test the potential of rivers to record the intensity of landslides that affected their courses. The study area is located [...] Read more.
The objective of this study is to understand the effect of landslides on the drainage network within the area of interest. We thus test the potential of rivers to record the intensity of landslides that affected their courses. The study area is located within the Zagros orogenic belt along the border between Iraq and Iran. We identified 280 landslides through nine QuickBird scenes using visual photo-interpretation. The total landslide area of 40.05 km2 and their distribution follows a NW–SE trend due to the tectonic control of main thrust faults. We observe a strong control of the landslides on the river course. We quantify the relationship between riverbed displacement and mass wasting occurrences using landslide sizes versus river offset and hypsometric integrals. Many valleys and river channels are curved around the toe of landslides, thus producing an offset of the stream which increases with the landslide area. The river offsets were quantified using two geomorphic indices: the river with respect to the basin midline (Fb); and the offset from the main river direction (Fd). Hypsometry and stream offset seem to be correlated. In addition; the analysis of selected river courses may give some information on the sizes of the past landslide events and therefore contribute to the hazard assessment. Full article
(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)
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