Taking Advantage of the ESA G-POD Service to Study Ground Deformation Processes in High Mountain Areas: A Valle d’Aosta Case Study, Northern Italy

Shallow Landslides and Rockfalls Velocity Assessment at Regional Scale: A Methodology Based on a Morphometric Approach

Velocity is one of the most important parameters to evaluate the damaging potential of a mass movement, but its assessment, especially for extremely rapid landslides, is a complex task. In the literature, several models to assess mass movement velocity exist, but they usually require many detailed parameters, and therefore, they are applicable only to a single slope and not usable for regional-scale analyses. This study aims to propose a simple morphometric methodology, based on the spatialisation of the Energy Line method, to determine the velocity of shallow landslides and rockfalls at a regional scale. The proposed method requires a limited amount of input data (landslide perimeters and a digital elevation model), and its application can be carried out using GIS software and a Matlab code. The test area of this work is the Valle d’Aosta Region (Northern Italy), selected due to its peculiar geological and geomorphological setting that makes this region susceptible to the occurrence of both shallow landslides and rockfalls. Since measured velocity values for rockfalls and shallow landslides were not available, the results obtained with the proposed method have been validated through the implementation of a model in the literature, namely the Gravitational Process Path (GPP) model, for some selected landslides.

Sentinel-1 Big Data Processing with P-SBAS InSAR in the Geohazards Exploitation Platform: An Experiment on Coastal Land Subsidence and Landslides in Italy

The growing volume of synthetic aperture radar (SAR) imagery acquired by satellite constellations creates novel opportunities and opens new challenges for interferometric SAR (InSAR) applications to observe Earth’s surface processes and geohazards. In this paper, the Parallel Small BAseline Subset (P-SBAS) advanced InSAR processing chain running on the Geohazards Exploitation Platform (GEP) is trialed to process two unprecedentedly big stacks of Copernicus Sentinel-1 C-band SAR images acquired in 2014–2020 over a coastal study area in southern Italy, including 296 and 283 scenes in ascending and descending mode, respectively. Each stack was processed in the GEP in less than 3 days, from input SAR data retrieval via repositories, up to generation of the output P-SBAS datasets of coherent targets and their displacement histories. Use-cases of long-term monitoring of land subsidence at the Capo Colonna promontory (up −2.3 cm/year vertical and −1.0 cm/year east–west rate), slow-moving landslides and erosion landforms, and deformation at modern coastal protection infrastructure in the city of Crotone are used to: (i) showcase the type and precision of deformation products outputting from P-SBAS processing of big data, and the derivable key information to support value-adding and geological interpretation; and (ii) discuss potential and challenges of big data processing using cloud/grid infrastructure.

Comment on “Pre-Collapse Space Geodetic Observations of Critical Infrastructure: The Morandi Bridge, Genoa, Italy” by Milillo et al. (2019)

We present in this comment a Multi-Temporal SAR Interferometry (MT-InSAR) analysis showing that the results published by Milillo et al. (2019) in the Remote Sensing Journal, presenting the evidence of space geodetic observations relevant to displacements occurring before the collapse of the Morandi Bridge, happened in Genova (Italy) on the 14 August 2018, are questionable. In particular, we focus on the InSAR results obtained by Milillo et al. (2019) by processing the 3 m × 3 m resolution COSMO-SkyMed (CSK) data collected from ascending and descending orbits on the area of interest. These results, thanks to the high spatial resolution and the short revisit time characterizing this multi-orbit SAR dataset, represent the cornerstone of their analysis. The main findings of their study allow Milillo et al. to conclude that the InSAR processing of this COSMO-SkyMed dataset reveals the increased deformation magnitude over time of points located near the strands of the deck next to the collapsed pier, between 12 March 2017 and August 2018. In this comment, we show the results obtained by the IREA-CNR SAR team after processing the same ascending and descending CSK dataset, but by using two alternative and independent processing techniques: the Small BAseline Subset (SBAS) and the Advanced Tomographic SAR (TomoSAR) approaches, respectively. Our analysis shows that, although both the SBAS and the TomoSAR analyses allow achieving denser coherent pixel maps relevant to the Morandi bridge, nothing of the pre-collapse large displacements reported in Milillo et al. (2019) appears in our results, leading us to deeply disagree with the findings of their InSAR analysis.

Impact of Deep-seated Gravitational Slope Deformation on urban areas and large infrastructures in the Italian Western Alps

Deep-seated Gravitational Slope Deformations (DsGSDs) are huge ground-deformation slow evolving phenomena, highly widespread in alpine territory. Their long-lasting evolution, with continuous deformation rate, may represents a natural hazard, able to endanger various anthropic structures and infrastructures. Until today, the development of technical and regulatory tools, aimed to effectively manage the interactions between DsGSDs and anthropic elements, has been generally lightly considered in risk management and land use planning. The definition of the type and severity of impacts on the anthropic elements, becomes increasingly important in terms of urban planning and risk management, and deserve an update in the current adopted procedures. Focusing on the Western Italian Alps, we implemented an interdisciplinary analysis, based on multi-source data, by means of geoinformatics, remote sensing and archive consultation approaches. Intersecting DsGSDs available information with the urbanized territory in a Geographic Information System environment, we obtained, despite the high data heterogeneity, an overall framework of the existing interactions. Specifically, we defined the interactions between these large phenomena and buildings, roads and rail networks, and linear infrastructures, as penstocks, waterworks or dams, also highlighing the state of activity of the inventoried phenomena. Moreover, we analysed the degree of the DsGSD impacts on the anthropic elements, detecting and classifying all the documented damages within the Italian Western Alps territory. The obtained results highlight the need for an innovative approach in DsGSDs risk assessment, both in terms of the definition of their behavior over time and of their impacts on the anthropic elements, for a more effective land use planning and a proper handling of these phenomena in the legislation framework.

Landslide Characterization Applying Sentinel-1 Images and InSAR Technique: The Muyubao Landslide in the Three Gorges Reservoir Area, China

Landslides are a common natural hazard that causes casualties and unprecedented economic losses every year, especially in vulnerable developing countries. Considering the high cost of in-situ monitoring equipment and the sparse coverage of monitoring points, the Sentinel-1 images and Interferometric Synthetic Aperture Radar (InSAR) technique were used to conduct landslide monitoring and analysis. The Muyubao landslide in the Three Gorges Reservoir area in China was taken as a case study. A total of 37 images from March 2016 to September 2017 were collected, and the displacement time series were extracted using the Stanford Method for Persistent Scatterer (StaMPS) small baselines subset method. The comparison to global positioning system monitoring results indicated that the InSAR processing of the Muyubao landslide was accurate and reliable. Combined with the field investigation, the deformation evolution and its response to triggering factors were analyzed. During this monitoring period, the creeping process of the Muyubao landslide showed obvious spatiotemporal deformation differences. The changes in the reservoir water level were the trigger of the Muyubao landslide, and its deformation mainly occurred during the fluctuation period and high-water level period of the reservoir.

Advances on Measuring Deep-Seated Ground Deformations Using Robotized Inclinometer System

In the field of geo-hazards and geo-engineering, monitoring networks represent a key element for the geological risk assessment and the design and management of large infrastructures construction. In the last decade, we have observed a strong development on remote sensing techniques but just small changes in the subsoil observations. However, this type of measurement is very important to have a three-dimensional representation of the studied area, since the surface measurements often represent a sum of deformations that develop in a complex way in the subsoil. In this paper, we present a robotic inclinometer system developed to acquire deep-seated ground deformations in boreholes. This instrumentation combines advantages offered by manual inclinometer measurements with a robotized approach that improves the results in term of accuracy, revisiting time, and site accessibility. The Automated Inclinometer System (AIS) allows one to explore automatically all the length of the monitored borehole using just one inclinometer probe with a semi-wireless system. The paper presents the system and a detailed dataset of measurements acquired on three inclinometer tubes installed for the monitoring of the construction phase of the new Line C Metro of Rome. The dataset was acquired in real monitored site and undisturbed conditions and can represent a benchmark for modern inclinometer measurements.

Review of Satellite Interferometry for Landslide Detection in Italy

Landslides recurrently impact the Italian territory, producing huge economic losses and casualties. Because of this, there is a large demand for monitoring tools to support landslide management strategies. Among the variety of remote sensing techniques, Interferometric Synthetic Aperture Radar (InSAR) has become one of the most widely applied for landslide studies. This work reviews a variety of InSAR-related applications for landslide studies in Italy. More than 250 papers were analyzed in this review. The first application dates back to 1999. The average production of InSAR-related papers for landslide studies is around 12 per year, with a peak of 37 papers in 2015. Almost 70% of the papers are written by authors in academia. InSAR is used (i) for landslide back analysis (3% of the papers); (ii) for landslide characterization (40% of the papers); (iii) as input for landslide models (7% of the papers); (iv) to update landslide inventories (15% of the papers); (v) for landslide mapping (32% of the papers), and (vi) for monitoring (3% of the papers). Sixty-eight percent of the authors validated the satellite results with ground information or other remote sensing data. Although well-known limitations exist, this bibliographic overview confirms that InSAR is a consolidated tool for many landslide-related applications.

Sentinel-1 DInSAR for Monitoring Active Landslides in Critical Infrastructures: The Case of the Rules Reservoir (Southern Spain)

Landslides in reservoir contexts are a well-recognised hazard that may lead to dangerous situations regarding infrastructures and people’s safety. Satellite-based radar interferometry is proving to be a reliable method to monitor the activity of landslides in such contexts. Here, we present a DInSAR (Differential Interferometric Synthetic Aperture Radar) analysis of Sentinel-1 images that exemplifies the usefulness of the technique to recognize and monitor landslides in the Rules Reservoir (Southern Spain). The integration of DInSAR results with a comprehensive geomorphological study allowed us to understand the typology, evolution and triggering factors of three active landslides: Lorenzo-1, Rules Viaduct and El Arrecife. We could distinguish between rotational and translational landslides and, thus, we evaluated the potential hazards related to these typologies, i.e., retrogression (Lorenzo-1 and Rules Viaduct landslides) or catastrophic slope failure (El Arrecife Landslide), respectively. We also observed how changes in the water level of the reservoir influence the landslide’s behaviour. Additionally, we were able to monitor the stability of the Rules Dam as well as detect the deformation of a highway viaduct that crosses a branch of the reservoir. Overall, we consider that other techniques must be applied to continue monitoring the movements, especially in the El Arrecife Landslide, in order to avoid future structural damages and fatalities.

LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor

For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (~km) relative displacements with an accuracy of <1 cm/epoch and ~2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.

An Open-Source Web Platform to Share Multisource, Multisensor Geospatial Data and Measurements of Ground Deformation in Mountain Areas

Nowadays, the increasing demand to collect, manage and share archives of data supporting geo-hydrological processes investigations requires the development of spatial data infrastructure able to store geospatial data and ground deformation measurements, also considering multisource and heterogeneous data. We exploited the GeoNetwork open-source software to simultaneously organize in-situ measurements and radar sensor observations, collected in the framework of the HAMMER project study areas, all located in high mountain regions distributed in the Alpines, Apennines, Pyrenees and Andes mountain chains, mainly focusing on active landslides. Taking advantage of this free and internationally recognized platform based on standard protocols, we present a valuable instrument to manage data and metadata, both in-situ surface measurements, typically acquired at local scale for short periods (e.g., during emergency), and satellite observations, usually exploited for regional scale analysis of surface displacement. Using a dedicated web-interface, all the results derived by instrumental acquisitions and by processing of remote sensing images can be queried, analyzed and downloaded from both expert users and stakeholders. This leads to a useful instrument able to share various information within the scientific community, including the opportunity of reprocessing the raw data for other purposes and in other contexts.

Characterization of the Kinematics of Three Bears Landslide in Northern California Using L-band InSAR Observations

High-precision monitoring of landslides is essential for understanding their kinematics and reducing landslide induced damage. The spatiotemporal deformation variations of the Three Bears landslide in northern California have not been systematically monitored and interpreted. In this study, we applied advanced time-series InSAR analysis methods to characterize the kinematics of the landslide covering two periods (2007–2011 and 2015–2017) with multi-track synthetic aperture radar (SAR) images acquired from L-band ALOS PALSAR-1/2 satellites. Our results show that the Three Bears landslide has been moving consistently, with the Line of Sight (LOS) deformation rate exceeding 300 mm/yr from 2007 to 2011 and around 250 mm/yr from 2015 to 2017. The east–west and vertical deformation components were inverted by integrating ascending and descending ALOS PALSAR-2 interferograms during the 2015–2017 period, indicating that the landslide was dominated by eastward movement and in a continuous deformation stage. Down-slope landslide motions observed from adjacent satellite tracks with slightly different radar look vectors were used to verify the accuracy of InSAR-derived results. Comparison between linearly detrended InSAR displacements and precipitation records indicate that the landslide tends to accelerate during the wet seasons. The results could allow us to better understand the kinematics of the landslide and provide significant evidence for evaluating the potential for catastrophic failure and the threat posed by such failure to human life and property. Combined with a proper geotechnical/geomechanical model, the results would also facilitate the design and implementation of mitigation measures.

Wide-Area InSAR Survey of Surface Deformation in Urban Areas and Geothermal Fields in the Eastern Trans-Mexican Volcanic Belt, Mexico

This paper provides the first wide-area Interferometric Synthetic Aperture Radar (InSAR) survey of the whole eastern Trans-Mexican Volcanic Belt (42,200 km2). The aims are to identify ground deformation hotspots within major urbanized areas and rural valleys, establish baselines in geothermal exploration sites, and analyze deformation at geothermal exploitation sites and its relationship with energy production. The whole 2003–2010 ENVISAT C-band SAR archive available over the region was processed with the Small BAseline Subset (SBAS) InSAR method to retrieve over 840,000 coherent targets and estimate their ground displacement rates and time series. Land subsidence hotspots due to aquifer drawdown are found within the city of Puebla (up to −53 mm/year vertical rates, groundwater pumping for industrial use), Tlaxcala and Apizaco (−17 mm/year, industrial and public), the valley of Tecamachalco (−22 mm/year, agricultural), Tulancingo (−55 mm/year, public, industrial and agricultural), and in the eastern Mexico City metropolitan area (−44 mm/year, agricultural). The baseline for the Acoculco caldera complex shows widespread ground stability. Conversely, localized subsidence patterns of −5 to −10 mm/year exist around Las Derrumbadas and Cerro Pinto in the Serdán-Oriental basin, due to intense groundwater pumping for agriculture. A well-defined land subsidence area with −11 mm/year maximum rates is found at Los Humeros volcanic complex within Los Potreros collapse, correlating well with energy production infrastructure location and historical steam production rates. Field surveys carried out in Acoculco and Los Humeros in 2018 provide supporting evidence for the identification of hydrothermal manifestations, and understanding of the landscape and surface deformation patterns within the geothermal fields.

Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets

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 1:5,000). 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.

Potential and Limitations of Open Satellite Data for Flood Mapping

Satellite remote sensing is a powerful tool to map flooded areas. In recent years, the availability of free satellite data significantly increased in terms of type and frequency, allowing the production of flood maps at low cost around the world. In this work, we propose a semi-automatic method for flood mapping, based only on free satellite images and open-source software. The proposed methods are suitable to be applied by the community involved in flood hazard management, not necessarily experts in remote sensing processing. As case studies, we selected three flood events that recently occurred in Spain and Italy. Multispectral satellite data acquired by MODIS, Proba-V, Landsat, and Sentinel-2 and synthetic aperture radar (SAR) data collected by Sentinel-1 were used to detect flooded areas using different methodologies (e.g., Modified Normalized Difference Water Index, SAR backscattering variation, and supervised classification). Then, we improved and manually refined the automatic mapping using free ancillary data such as the digital elevation model-based water depth model and available ground truth data. We calculated flood detection performance (flood ratio) for the different datasets by comparing with flood maps made by official river authorities. The results show that it is necessary to consider different factors when selecting the best satellite data. Among these factors, the time of the satellite pass with respect to the flood peak is the most important. With co-flood multispectral images, more than 90% of the flooded area was detected in the 2015 Ebro flood (Spain) case study. With post-flood multispectral data, the flood ratio showed values under 50% a few weeks after the 2016 flood in Po and Tanaro plains (Italy), but it remained useful to map the inundated pattern. The SAR could detect flooding only at the co-flood stage, and the flood ratio showed values below 5% only a few days after the 2016 Po River inundation. Another result of the research was the creation of geomorphology-based inundation maps that matched up to 95% with official flood maps.