1,535 research outputs found

    Landslide Detection Using Remote Sensing Methods A Review of Current Techniques

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    Landslides are among the most dangerous natural disasters, as they generally follow other major disasters thereby causing significant damage to already weakened systems. In the U.S. alone they cause an excess of 1 billion in damages and an average 25-50 deaths annually(USGC). Remote sensing techniques for landslide monitoring and prediction has gained popularity in recent years since it enables hazard mitigation. Synthetic Aperture Radar (SAR) interferometry is among the remote sensing techniques used. DInSAR is an advanced interferometric technique which uses radar sensors to estimate the phase of a given area from which the landslide activity can be predicted. The analysis has been performed in 3 test areas each having unique conditions. These areas have been chosen to assess the effectiveness of the analysis in their respective conditions. The data for this analysis is obtained using Sentinel-1 satellite which is a C-band SAR sensor. The 3 locations have been analyzed for a period of 36 days with sensor taking acquisitions every 12 days. From this analysis, we have found in the case of Etna slope instability due to volcanic action has been observed. In the case of California highway-1 a unique phase activity was observed in the landslide region which suggest additional analysis to be performed in similar conditions to validate the findings. Finally, in the case of Anargyroi Greece bad phase readings in the region resulted in uncertain analysis prompting for longer time series analysis to mitigate these problems. Additional subsidence maps were also generated from the phase, but these results could not be calibrated and correlated with in situ readings. To assess the effectiveness of this method to quantify subsidence monitoring additional analysis must be done which take in to consideration old phase values for accurate results

    Basin scale assessment of landslides geomorphological setting by advanced InSAR analysis

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    An extensive investigation of more than 90 landslides affecting a small river basin in Central Italy was performed by combining field surveys and remote sensing techniques. We thus defined the geomorphological setting of slope instability processes. Basic information, such as landslides mapping and landslides type definition, have been acquired thanks to geomorphological field investigations and multi-temporal aerial photos interpretation, while satellite SAR archive data (acquired by ERS and Envisat from 1992 to 2010) have been analyzed by means of A-DInSAR (Advanced Differential Interferometric Synthetic Aperture Radar) techniques to evaluate landslides past displacements patterns. Multi-temporal assessment of landslides state of activity has been performed basing on geomorphological evidence criteria and past ground displacement measurements obtained by A-DInSAR. This step has been performed by means of an activity matrix derived from information achieved thanks to double orbital geometry. Thanks to this approach we also achieved more detailed knowledge about the landslides kinematics in time and space

    Mapping ground instability in areas of geotechnical infrastructure using satellite InSAR and Small UAV Surveying: a case study in Northern Ireland

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    Satellite Interferometric Synthetic Aperture Radar (InSAR), geological data and Small Unmanned Aerial Vehicle (SUAV) surveying was used to enhance our understanding of ground movement at five areas of interest in Northern Ireland. In total 68 ERS-1/2 images 1992–2000 were processed with the Small Baseline Subset (SBAS) InSAR technique to derive the baseline ground instability scenario of key areas of interest for five stakeholders: TransportNI, Northern Ireland Railways, Department for the Economy, Arup, and Belfast City Council. These stakeholders require monitoring of ground deformation across either their geotechnical infrastructure (i.e., embankments, cuttings, engineered fills and earth retaining structures) or assessment of subsidence risk as a result of abandoned mine workings, using the most efficient, cost-effective methods, with a view to minimising and managing risk to their businesses. The InSAR results provided an overview of the extent and magnitude of ground deformation for a 3000 km2 region, including the key sites of the disused salt mines in Carrickfergus, the Belfast–Bangor railway line, Throne Bend and Ligoniel Park in Belfast, Straidkilly and Garron Point along the Antrim Coast Road, plus other urbanised areas in and around Belfast. Tailored SUAV campaigns with a X8 airframe and generation of very high resolution ortho-photographs and a 3D surface model via the Structure from Motion (SfM) approach at Maiden Mount salt mine collapse in Carrickfergus in 2016 and 2017 also demonstrate the benefits of very high resolution surveying technologies to detect localised deformation and indicators of ground instabilit

    Využití družicové SAR interferometrie pro identifikaci a mapování sesuvů ve městě Sánchez, Dominikánské republice

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    The landscapes we see today are the result of constant changes during millions of years. Mass movement is one of the principal geomorphology process responsible for these changes and occurs in different scales around the world, causing disaster in populated areas. Sánchez is a municipality located in Samaná province, Dominican Republic, where continuous motion had created an atmosphere of uncertainness among the inhabitants, that observed day after day the deterioration of infrastructures, loss of agricultural capability and potential life-threatening situations. Slope instability has been increased by anthropogenic activity and triggers factors as: elimination of forest for coconut plantation, lack of proper wasted drainage and drinking water supply system, growth of community, change of construction material, meteorological phenomena and seismic events. This investigation aims to identify slope movement and map it, using SENTINEL-1 satellite SAR interferometry (InSAR). By applying multi-temporal techniques to a series of SENTINEL-1 scenes, it is possible to recognize a continuous surface deformation in the area. The results will help authorities to develop short and long-term risk management plans.Zeměpisy, které dnes vidíme, jsou výsledkem neustálých změn v průběhu několika miliónů let. Masový pohyb je jedním z hlavních geomorfologických procesů zodpovědných za tyto změny a probíhá v různých měřítkách po celém světě a způsobuje katastrofu v osídlených oblastech. Sánchez je obec ležící v provincii Samaná, Dominikánská republika, kde neustálý pohyb vytvářel atmosféru nejistoty mezi obyvateli, která každodenně pozorovala zhoršování infrastruktury, ztrátu zemědělské kapacity a potenciální život ohrožující situace. Nestabilita svahu byla zvýšena antropogenní aktivitou a spouští faktory jako: odstranění lesů pro kokosové plantáže, nedostatek správného odpadního kanalizace a zásobování pitnou vodou, růst obce, změna stavebního materiálu, meteorologické jevy a seismické události. Cílem tohoto šetření je identifikovat pohyb svahu a mapovat ho pomocí SARINEL-1 satelitní SAR interferometrie (InSAR). Aplikací multičasových technik na řadu scén SENTINEL-1 je možné rozpoznat kontinuální povrchovou deformaci v oblasti. Výsledky pomohou orgánům vypracovat krátkodobé a dlouhodobé plány řízení rizik.548 - Katedra geoinformatikyvýborn

    Satellite Monitoring of Railways using Interferometric Synthetic Aperture Radar (InSAR)

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    There is over 15,600 km of track in the Swedish railroad network. This network is vital for the transportation of people and goods across the country. It is important that this network is monitored and maintained to ensure good function and safety. A tool for monitoring and measuring ground deformation over a large area remotely with high frequency and accuracy was developed in recent decades. This tool is known as Interferometric Synthetic Aperture Radar (InSAR), and is used by researchers, geo-technicians, and engineers. The purpose of this study has been to evaluate the use and feasibility of the InSAR technique for track condition monitoring and compare it to conventional track condition monitoring techniques. Malmbanan, which is primarily used to transport iron-ore from mines in Sweden to the ports of Luleå, Sweden and Narvik, Norway, is used as a case study for this project; specifically, the section between Kiruna and Riksgränsen. Coordinate matching of measurements from the provided Persistent Scatterer Interferometry (PSI) InSAR data and Optram data from survey trains were performed. Then measured changes over different time spans within the two systems were overlapped and classified with different thresholds to see if there is correlation between the two systems. An extensive literature review was also conducted in order to gain an understanding of InSAR technologies and uses.The literature review showed that there is a large potential and a quickly growing number of applications of InSAR to monitor railways and other types of infrastructure, and that the tools and algorithms for this are being improved. The case study, on the other hand, shows that it can be difficult to directly compare measurement series from different tools, each working on different resolutions in terms of both time and space. InSAR is thus not about to replace techniques such as those behind Optram (using measurement trains). Instead, the approaches offer complementary perspectives, each highlighting different types of issues. We find that InSAR offers a good way to identify locations with settlements or other types of ground motions. Especially transition zones between settlements and more stable ground can be challenging from a maintenance point of view and can clearly be identified and monitored using InSAR. With the rollout of national InSAR-data, and the large increase in data accessibility, we see a considerable potential for future studies that apply the technique to the railway area

    ANALYZING THE LIFE-CYCLE OF UNSTABLE SLOPES USING APPLIED REMOTE SENSING WITHIN AN ASSET MANAGEMENT FRAMEWORK

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    An asset management framework provides a methodology for monitoring and maintaining assets, which include anthropogenic infrastructure (e.g., dams, embankments, and retaining structures) and natural geological features (e.g., soil and rock slopes). It is imperative that these assets operate efficiently, effectively, safely, and at a high standard since many assets are located along transportation corridors (highways, railways, and waterways) and can cause severe damage if compromised. Assets built on or around regions prone to natural hazards are at an increased risk of deterioration and failure. The objective of this study is to utilize remote sensing techniques such as InSAR, LiDAR, and optical photogrammetry to identify assets, assess past and current conditions, and perform long-term monitoring in transportation corridors and urbanized areas prone to natural hazards. Provided are examples of remote sensing techniques successfully applied to various asset management procedures: the characterization of rock slopes (Chapter 2), identification of potentially hazardous slopes along a railroad corridor (Chapter 3), monitoring subsidence rates of buildings in San Pedro, California (Chapter 4), and mapping displacement rates on dams in India (Chapter 5) and California (Chapter 6). A demonstration of how InSAR can be used to map slow landslides (those with a displacement rate \u3c 16 mm/year and may be undetectable without sensitive instrumentation) and update the California Landslide Inventory on the Palos Verdes Peninsula is provided in Chapter 7. Long-term landslide monitoring using optical photogrammetry, GPS, and InSAR measurements is also used to map landslide activity at three orders of magnitude (meter to millimeter scales) in Chapter 8. Remote sensing has proven to be an effective tool at measuring ground deformation, which is an implicit indicator of how geotechnical asset condition changes (e.g., deteriorates) over time. Incorporating these techniques into a geotechnical asset management framework will provide greater spatial and temporal data for preventative approaches towards natural hazards
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