Nonlinear inversion of subsidence signatures induced by tunnels detected with surface and remote sensing measurements

The state of the art in predicting tunnel-induced subsidence settlements is based on empirical and analytical methods. Empirical methods are useful when the equations are implemented with host medium properties where tunnels have been excavated. Analytical solutions can predict tunneling-induced ground movements, with the predictions accounting for tunnel radius and depth as well as ground-loss parameters in soft soils. The drawback is that these methods require human intervention, as each model must be adjusted manually by the interpreter until the model signature fits the observed data. It would take tremendous effort to evaluate displacement anomalies detected by remote sensing methods using such forward-modeling methods. Therefore, we present a method based on an inversion algorithm that automatically inverts subsidence signatures for tunnel radius, depth, Poisson's ratio, and the gap parameter. It is an advancement over conventional methods because it does not require a first guess, and it can invert several subsidence signatures in a matter of minutes. The algorithm, coupled with remote sensing-based displacement maps, is a cost-effective solution in operational characterization of displacement anomalies. We demonstrate that observed and predicted subsidence signatures are in good agreement with existing tunnel data in uniform clay and that the inversion parameters correspond to those predicted with forward modeling alone.

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State of the art on remote sensing methods for suspended sediment concentration in inland and coastal waters

River Sedimentation ◽

10.1201/9781315623207-48 ◽

2016 ◽

pp. 224-231

Author(s):

A.E. Holdefer ◽

K. Formiga

Keyword(s):

Remote Sensing ◽

Suspended Sediment ◽

Coastal Waters ◽

Suspended Sediment Concentration ◽

State Of The Art ◽

Sediment Concentration ◽

Remote Sensing Methods

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Comparison of Above-Water Seabird and TriOS Radiometers along an Atlantic Meridional Transect

Remote Sensing ◽

10.3390/rs12101669 ◽

2020 ◽

Vol 12 (10) ◽

pp. 1669

Author(s):

Krista Alikas ◽

Viktor Vabson ◽

Ilmar Ansko ◽

Gavin H. Tilstone ◽

Giorgio Dall’Olmo ◽

...

Keyword(s):

State Of The Art ◽

Ocean Color ◽

Percentage Difference ◽

Wide Range ◽

Before And After ◽

Reference Measurements ◽

Satellite Ocean Color ◽

Good Agreement

The Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) project has carried out a range of activities to evaluate and improve the state-of-the-art in ocean color radiometry. This paper described the results from a ship-based intercomparison conducted on the Atlantic Meridional Transect 27 from 23rd September to 5th November 2017. Two different radiometric systems, TriOS-Radiation Measurement Sensor with Enhanced Spectral resolution (RAMSES) and Seabird-Hyperspectral Surface Acquisition System (HyperSAS), were compared and operated side-by-side over a wide range of Atlantic provinces and environmental conditions. Both systems were calibrated for traceability to SI (Système international) units at the same optical laboratory under uniform conditions before and after the field campaign. The in situ results and their accompanying uncertainties were evaluated using the same data handling protocols. The field data revealed variability in the responsivity between TRiOS and Seabird sensors, which is dependent on the ambient environmental and illumination conditions. The straylight effects for individual sensors were mostly within ±3%. A near infra-red (NIR) similarity correction changed the water-leaving reflectance (ρw) and water-leaving radiance (Lw) spectra significantly, bringing also a convergence in outliers. For improving the estimates of in situ uncertainty, it is recommended that additional characterization of radiometers and environmental ancillary measurements are undertaken. In general, the comparison of radiometric systems showed agreement within the evaluated uncertainty limits. Consistency of in situ results with the available Sentinel-3A Ocean and Land Color Instrument (OLCI) data in the range from (400…560) nm was also satisfactory (−8% < Mean Percentage Difference (MPD) < 15%) and showed good agreement in terms of the shape of the spectra and absolute values.

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Application of Remote Sensing to the Investigation of Rock Slopes: Experience Gained and Lessons Learned

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8070296 ◽

2019 ◽

Vol 8 (7) ◽

pp. 296 ◽

Cited By ~ 4

Author(s):

Doug Stead ◽

Davide Donati ◽

Andrea Wolter ◽

Matthieu Sturzenegger

Keyword(s):

Remote Sensing ◽

Lessons Learned ◽

Rock Slopes ◽

Field Methods ◽

Potential Applications ◽

Remote Sensing Techniques ◽

The Stability ◽

Difficult Terrain ◽

Remote Sensing Methods

The stability and deformation behavior of high rock slopes depends on many factors, including geological structures, lithology, geomorphic processes, stress distribution, and groundwater regime. A comprehensive mapping program is, therefore, required to investigate and assess the stability of high rock slopes. However, slope steepness, rockfalls and ongoing instability, difficult terrain, and other safety concerns may prevent the collection of data by means of traditional field techniques. Therefore, remote sensing methods are often critical to perform an effective investigation. In this paper, we describe the application of field and remote sensing approaches for the characterization of rock slopes at various scale and distances. Based on over 15 years of the experience gained by the Engineering Geology and Resource Geotechnics Research Group at Simon Fraser University (Vancouver, Canada), we provide a summary of the potential applications, advantages, and limitations of varied remote sensing techniques for comprehensive characterization of rock slopes. We illustrate how remote sensing methods have been critical in performing rock slope investigations. However, we observe that traditional field methods still remain indispensable to collect important intact rock and discontinuity condition data.

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Forward modeling for marine sediment characterization using chirp sonars

Geophysics ◽

10.1190/1.3590717 ◽

2011 ◽

Vol 76 (4) ◽

pp. T91-T99 ◽

Cited By ~ 7

Author(s):

Sandrine Rakotonarivo ◽

Michel Legris ◽

Rozenn Desmare ◽

Jean-Pierre Sessarégo ◽

Jean-François Bourillet

Keyword(s):

Layer Thickness ◽

Forward Modeling ◽

Forward Model ◽

Central Frequency ◽

Transitional Layer ◽

Quantitative Characterization ◽

Buried Layers ◽

Chirp Sonar ◽

Good Agreement

This paper investigates the forward modeling of chirp-sonar data for the quantitative characterization of marine subbottom sediment between 1 and 10 kHz. The forward modeling, based on a transfer function approach, included impacts of layering or impedance mismatch, attenuation, roughness, and transitional layers, i.e., continuous impedance variations. The presented approach provided the best compromise between the number of available geoacoustic parameters from chirp-sonar data and the subbottom modeling accuracy. The forward model was tested on deep-sea chirp-sonar data acquired at a central frequency of 3.5 kHz. Comparisons between synthetic and experimental seismograms showed good agreement for the first 15 m of buried layers. Performance of the inversion using this forward model was also examined through sensitivity analysis. The results suggested that estimations of layer thickness, impedance, and transitional layer thickness were robust, whereas roughness and attenuation estimations were subject to wavelength and layer thickness conditions.

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SPECTRAL IMAGING AND CLAY DETECTION IN LATGALE LAKES

Environment Technology Resources Proceedings of the International Scientific and Practical Conference ◽

10.17770/etr2019vol1.4189 ◽

2019 ◽

Vol 1 ◽

pp. 307

Author(s):

Rasma Tretjakova ◽

Sergejs Kodors ◽

Juris Soms

Keyword(s):

Remote Sensing ◽

Incomplete Data ◽

Spectral Imaging ◽

Cost Effective ◽

Indirect Methods ◽

Sediment Samples ◽

Pilot Experiment ◽

Pearson Coefficient ◽

Remote Sensing Methods ◽

Sentinel 2

The survey of lake sediments is complex, time consuming and costly process with risks to human health. Additionally, manually obtained sediment samples provide incomplete data about a survey region. In turn, remote sensing methods are cost-effective and can provide continuous data about a survey region. Therefore, authors decided to perform a pilot experiment with a remote sensing method in order to detect clay sediments deposited in lakebeds. The evaluated method is the analysis of spectral images of Sentinel-2. Pearson coefficient and C4.5 datamining methods were applied for data analysis. Survey objects are Latgale lakes with and without clay sediments. The pilot experiment showed, that spectral imaging of lake water is not applicable method to detect definitely clay sediments in lakes, however, research results provide ideas about indirect methods, which must be studied in the future.

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Recent developments in estimating land surface biogeophysical variables from optical remote sensing

Progress in Physical Geography Earth and Environment ◽

10.1177/0309133307084626 ◽

2007 ◽

Vol 31 (5) ◽

pp. 501-516 ◽

Cited By ~ 104

Author(s):

Shunlin Liang

Keyword(s):

Remote Sensing ◽

Land Surface ◽

State Of The Art ◽

Optical Remote Sensing ◽

Nonlinear Inversion ◽

Spatial And Temporal Scales ◽

Recent Developments ◽

Ill Posed ◽

Earth System Models ◽

New Algorithms

Earth system models and many other applications require biogeophysical variables, and remote sensing is the only means by which to estimate them at the appropriate spatial and temporal scales. Developing advanced inversion methods to solve ill-posed multidimensional nonlinear inversion problems is critical and very challenging. This article reviews state-of-the-art algorithms for estimating land surface biogeophysical variables in optical remote sensing (from the visible to the thermal infrared spectrum) to stimulate the development of new algorithms and to utilize existing ones.

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Bathymetric mapping by means of remote sensing: methods, accuracy and limitations

Progress in Physical Geography Earth and Environment ◽

10.1177/0309133309105657 ◽

2009 ◽

Vol 33 (1) ◽

pp. 103-116 ◽

Cited By ~ 144

Author(s):

Jay Gao

Keyword(s):

Remote Sensing ◽

Light Transmission ◽

Effective Means ◽

Operating Cost ◽

Cost Effective ◽

Sampling Interval ◽

Influential Factors ◽

Imaging Method ◽

Cost Inefficiency ◽

Remote Sensing Methods

Bathymetry has been traditionally charted via shipboard echo sounding. Alhough able to generate accurate depth measurements at points or along transects, this method is constrained by its high operating cost, inefficiency, and inapplicability to shallow waters. By comparison, remote sensing methods offer more flexible, efficient and cost-effective means of mapping bathymetry over broad areas. Remote sensing of bathymetry falls into two broad categories: non-imaging and imaging methods. The non-imaging method (as typified by LiDAR) is able to produce accurate bathymetric information over clear waters at a depth up to 70 m. However, this method is limited by the coarse bathymetric sampling interval and high cost. The imaging method can be implemented either analytically or empirically, or by a combination of both. Analytical or semi-analytical implementation is based on the manner of light transmission in water. It requires inputs of a number of parameters related to the properties of the atmosphere, water column, and bottom material. Thus, it is rather complex and difficult to use. By comparison, empirical implementation is much simpler and requires the input of fewer parameters. Both implementations can produce fine-detailed bathymetric maps over extensive turbid coastal and inland lake waters quickly, even though concurrent depth samples are essential. The detectable depth is usually limited to 20 m. The accuracy of the retrieved bathymetry varies with water depth, with the accuracy substantially lower at a depth beyond 12 m. Other influential factors include water turbidity and bottom materials, as well as image properties.

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Aerial Crack View: Crack monitoring in concrete bridges through image processing acquired by UAV

IABSE Congress, New York, New York 2019: The Evolving Metropolis ◽

10.2749/newyork.2019.2458 ◽

2019 ◽

Author(s):

Jónatas Valença ◽

Bruno Santos ◽

André Araújo ◽

Eduardo Júlio

Keyword(s):

Unmanned Aerial Vehicles ◽

Human Error ◽

State Of The Art ◽

Minimum Cost ◽

Cost Effective ◽

Concrete Bridges ◽

Crack Monitoring ◽

Automatic Methods ◽

Existing Bridges

The development of methods aiming at assuring the maintenance of existing bridges and at minimum cost is a priority. Inspection and diagnosis methods are usually planned based on periodic visual inspections. In the case of concrete bridges, the characterization of cracking plays an extremely important role to monitor their structural health. However, current inspections are rudimentary and work intensive (inspectors take hand notes and pictures that later upload to reports and management software), prone to human error (since cracks are detected by inspectors onsite) and expensive (‘underbridge’ trucks are required). Therefore, alternative automatic methods will represent a breakthrough regarding the state-of-the-art.In this paper the method Aerial Crack View (ACV) is presented. ACV is a semi-automatic method to detect cracks in concrete bridges, based on processing images acquired by terrestrial working-station (TWS) and unmanned aerial vehicles (UAVs). The method was applied in Rainha Santa Isabel Bridge, in Coimbra, Portugal, for validation. ACV revels advantages such as, fastness because the detection of cracks is automatically conducted and cost-effective since UAVs can provide information on less accessible elements dismissing expensive access means..

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