Utilising FME for Acoustic Modelling

Arup was engaged to build an evidence base, to assist and review the Environment Protection Policy (EPP) for noise pollution and present the information graphically and dynamically to make informed decisions based on the current scientific criteria and assessment requirements. The evidence base provided the government agencies with the information and data to ensure any updates to the existing noise EPPs will be based on the current data available. The industry standard practises for acoustic analysis are a combination of various manual processes being a mix of GIS and excel macros to derive exceeded decibel readings. This has typically been a time consuming labour intensive task with only individual locations of the acoustic readings to assess. As part of the project Arup completed a social survey and analysis to identify possible correlations between complaints that have surpassed acoustic regulations. Due to the large amount of Social survey data, combined with the complex acoustic testing the GIS software solution - FME (Feature Manipulation Engine) was selected to assist with the automation, analysis and streamlining of the process. As a result of some initial testing with FME a revolutionary process of producing a Digital Elevation Model (DEM) of the noise readings was produced and analysed. This process generated a large amount of data that was then graphically and clearly presented to allow the team to make informed decisions and explain the study results to stakeholders. The graphical outputs included noise DEM, acoustic buffers, imagery and web based collaborative map data from the public survey respondents linked directly. For the complex testing which was previously completed, intricate and involved macros were replaced with broken down transparent logic testing within FME that had a clear workflow. This ability to breakdown the testing into smaller calculations allowed for the use of dependent parameters to facilitate clear debugging and optimisation of the process. The use of FME provided a powerful and flexible solution for a complex procedure through the automation, breaking down into small logical tasks of a very large data collection and in the process has provided significant time and cost savings.