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Abstract:The urbanisation phenomenon and related cities expansion and transport networks entail preventing the increase of population exposed to environmental pollution. Regarding noise exposure, the Environmental Noise Directive demands on main metropolis to produce noise maps. While based on standard methods, these latter are usually generated by proprietary software and require numerous input data concerning, for example, the buildings, land use, transportation network and traffic. The present work describes an open source implementation of a noise mapping tool fully implemented in a Geographic Information System compliant with the Open Geospatial Consortium standards. This integration makes easier at once the formatting and harvesting of noise model input data, cartographic rendering and output data linkage with population data. An application is given for a French city, which consists in estimating the impact of road traffic-related scenarios in terms of population exposure to noise levels in relation to both a threshold value and level classes.Keywords: noise mapping; END directive; GIS; open source; standards; road traffic; population exposure
Site map showing (a) bathymetry derived from multibeam echosounder (MBES) data, (b) acoustic backscatter derived from MBES data, (c) sediment classification with test locations, and (d) schematic view of deployment methodology overlaid on high resolution sparker reflection data (Not To Scale). MBES and sediment classification data is Irish Public Sector Data (INFOMAR) licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence and accessed through The maps were generated using ArcGIS Desktop v10.7 (www.arcgis.com).
The real time depiction of the DAS data, known as a Frequency Bandwidth Extracted (FBE) waterfall plot, was monitored to assess noise and data quality (Fig. 2). The FBE plot is generated by applying a Fast Fourier Transform to full bandwidth data and displaying the summed energy as a colour intensity plot. Figure 2a (frequency band 5 to 55 Hz) represents a 2-h 45 min portion of the recorded DAS data showing approximately the same duration of passive (upper) and active (lower) acquisition. The section of passive data highlighted in Fig. 2b shows 2 directions of ocean pressure waves travelling with apparent group velocities of c. 5.5 and 9 m/s. These pressure waves are also seen as steeply dipping, low velocity noise on the active shot records (Fig. 2c,d). Processing flows for data acquired at Sites 1 and 2 in the Dundalk Bay area are provided in Fig. 3. The multichannel shot gathers were muted (Fig. 3a,e) before being converted to a dispersion image using a 2D wave field-transformation method27,28. Dispersion curves were picked from the resulting frequency-phase velocity images (Fig. 3b,f) and extracted for inversion to produce a 1D Vs-depth profile using a Monte-Carlo approach29,30 (Fig. 3c,g).
Due to the expected harsh environment associated with deployment and retrieval of cables in a marine environment, an armoured Corrugated Steel Tape (CST) loose tube cable was used for the majority of testing. In order to assess whether the reduced sensitivity of this cable had a meaningful affect on the dispersive properties of the Scholte wave, a comparison between different commercially available fibre cable variants was made. This involved the construction of a combined 300 m long hybrid cable consisting of the CST armoured loose tube, unarmoured loose tube and unarmoured tight buffered cable. The different fibre types were fastened together along their length with spliced returns at the distal end, resulted in a c. 1800 m continuous sensing element with 1 m channel spacing. The cables were carefully deployed on the seabed to avoid damaging the unarmoured variants. With this setup it was possible to carry out a direct comparison of the ground response from a single shot record (Fig. 4).
Distributed sensing of fibre optic cables has been shown to enable continuous, real-time measurements along the full length of a fibre optic cable. Using this approach, standard telecommunication optical fibres are interrogated by transmitting a temporally short light pulse and analysing the backscatter from microstructural variations naturally present within the fibre. In this study, we presented an approach for rapid acquisition of near-surface seismic data based on distributed acoustic sensing of fibre optic cables laid on the seabed. DAS has recently been successfully applied to passively monitor seismic events and the ambient noise wavefield from existing seafloor telecommunications cables for a number of applications34,35,36. Some studies have also indicated that passively generated Sholte waves from structures founded on the seabed may be of comparable frequencies to those measured actively in this study37,38. However, many of the areas where windfarms are planned, for example in the Irish Sea, are not located close to existing structures and the expected relatively low frequency nature of passively acquired Scholte wave data in these areas may not be suited for characterising the geophysical and geotechnical properties of the near surface, associated with the design of renewable energy infrastructure on the seabed. Conversely, the potential application of DAS, when combined with active seismic sources, is more suitable for high-resolution near surface offshore investigations39,40.
The fibre optic cable used was a Fibre Fox Uni-Tube Corrugated Steel Tape (CST) armoured loose tube variant with 4 individual single mode fibres. An OTDR was used prior to data collection to evaluate the fibre condition and check for any potentially damaging reflections at connections and spliced joints. Each pair of fibres had a spliced return at the distal end to give 2000 m of active sensing element. The cable was housed on a mechanical winch on the back deck of the Celtic Voyager. The Fionn MacCumhaill collected the distal end of the cable from the back deck and towed the cable along a predefined transect orientated to intersect the existing geotechnical data points. Once the full length of the cable was in position, the end was lowered along with a weight to fix to the seabed along with a second weight to mechanically isolate the retrieval buoy from the cable, preventing tugging noise from the buoy being transmitted along the fibre. The near end of the cable was then lowered with the same weight arrangement from the back deck of the Celtic Voyager. USBL transponders were also attached to the second weights to give real time positions of the cable ends and aid in the positioning of the gun boat in close proximity to the cable on the seabed.
Initially shot gather data were extracted from the DAS data using the T0 trigger files. End shot records with 100 and 200 traces and 5 s data length were selected to capture the Scholte wave offset data. This significantly reduced the file sizes improving data management and computation efficiency. A total of 35 shot gathers were extracted along the full length of the fibre sensing cable with an approximate shot spacing of 25 m. The data were temporally resampled to reduce the file size further and also filtered with a 2 Hz low cut filter to remove the low frequency strain component. Processing of the Scholte wave data was performed by selecting dispersion curves from a phase velocity-frequency spectra, generated using a wavefield transformation method27,28,41,42,43 in Surfseis (Kansas Geological Survey). For the purpose of this study the fundamental mode Scholte Wave dispersion data were used to generate the dispersion curves which were then converted into target files for input to the inversion stage of the process. 153554b96e
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