MONITORING AND MAPPING OF ENVIRONMENTAL NOISE
CHAPTER FOUR GOOD PRACTICE AND PROCEDURES AND ISSUES SURROUNDING MAPPING
GOOD PRACTICES AND PROCEDURES
4.1 Chapter 2 described the accepted UK parameter for each noise source to be considered and the methodologies applicable for their prediction. Also identified were the organisations and agencies from which data that should be requested.
4.2 There is currently no single method of assessing 'industrial' noise sources as per the draft Directive definition. It will be necessary to develop a protocol for measurement of industrial noise to be incorporated in a mapping exercise.
4.3 In order to ensure good practice and procedure for the collection of noise data in Scotland the steps presented in flow diagram presented as Figure 4.1 should be adopted.
Figure 4.1: Flow Diagram for Data Collection to Ensure Good Practices and Procedures
ISSUES SURROUNDING THE COLLECTION AND AVAILABILITY OF DATA FOR MAPPING
4.4 The barriers to data collection identified were as follows:
- Confidential and commercially sensitive data, such as specialist freight information and who will have access to this information
- Time/cost implication of gathering missing data, such as road centre lines, road speed limits, building heights, industrial noise data, as this is either not available commercially or held by the agencies for their own purposes and therefore require 'cleaning' prior to use for mapping
- Conversion of UK parameters to L den and L night
- Licence issues relating to mapping products
- Compatibility of mapping products, and the ability to join attribute data to these products such as the adaptation of products such as Oscar to provide road ID's of relevance to the road sector and 'land use' files for the identification of soft and hard ground
4.5 Commercial sensitivity may be overcome by the attribute data provider providing prepared input sheets e.g. railway input proforma so that third parties are not privy to sensitive data.
4.6 Data such as building heights, which are currently unavailable commercially for the study, are being gathered gradually and so this situation will change.
4.7 Local authorities are currently undertaking manual counts of road traffic. It would be prudent to collect other information that could be collected at the same time, e.g. speed limit data, road surface texture.
4.8 For industrial noise sources and also for the Sea Ports, there is no useable data already held. The key contact organisation, SEPA is currently processing applications for Part A IPPC processes however there is only one permitted process on file at present (outwith the study area) which has noise data available. The issue of the assessment of 'industrial sources' such as mines, quarries, railway shunting yards and maintenance depots, motorway service areas, bus depots etc should be addressed. There is an opportunity for the Scottish Executive to liase with SEPA to collaborate on the development of their GIS system.
4.9 The maps will be produced in terms of the noise indicators L den and L night, the definition of these parameters is given in Annex 3. Therefore all predicted levels will require to be converted to these parameters. The noise software has functions to enable ease of conversion.
4.10 The areas undertaking mapping may already own mapping products which can be used for noise mapping. If however the Scottish Executive is supplying products under licence there may be an issue regarding licensing.
MAPPING USING GIS
4.11 Although noise models allow data to be imported and linked within project files, the scale of the assessments and system requirements may limit the amount of data handled at any one time by some software products. It is known that to facilitate managing data on the scale required by the directive two distinct data handling techniques have emerged in large scale noise mapping assessments. The first utilised a 'client-server' architecture, where the data is held on a server and the client (noise model) requests 'chunks' to model at a time. The second is a more manual method where the data model is built in a Geographical Information System (GIS) and exported to the noise modelling software in 'chunks'. Both techniques appear to be valid; the preferred method being defined by the software used, operator experience, the degree of data preparation required, the capital investment available and the objectives of the study. To undertake noise mapping databases relating to various acoustic features must be incorporated. Such databases include road centre lines, railway centre lines, building locations and heights and terrain data (DTM). These databases must comprise 2 fundamental types of information - 'where' and 'what'. The 'where' element provides information relating to the geographical or spatial location of a feature, the 'what' element provides information about the characteristics of a feature, also known as attributes.
4.12 These databases can be created in the noise software, or if already in existence, they can be imported or linked to the noise prediction software. If data already exists they are often held in a format compatible with GIS - ASCII, GML, .shp, TAB etc..
4.13 Where data already exists they are often created for another purpose e.g. land use data may be used in noise mapping to identify areas of acoustically absorbent ground, however these data may have been created for other land use or planning purposes. The concept of sharing data, which has a common value, necessitates a common storage and transfer format. GIS and compatible formats provide an obvious tool. This is especially true where road traffic managed by a central traffic management agency is concerned.
4.14 Map data, identifying the location of features, are held by a number of organisations. Principally, map data are provided by the OS, however other commercial organisations are increasingly making large-scale data available. Where data have not been 'acoustically attributed' e.g. road centre lines, a tool must be used to join relevant traffic information to the corresponding section of road. GIS provides advantages in undertaking this work, being readily scaleable to cope with large datasets including many objects. Many GIS packages have geoprocessing functions to automate the editing, manipulation and attribution of input data. The functions of an appropriate GIS may prove to be more efficient when attributing and cleaning data than particular noise prediction software.
4.15 GIS also facilitates the analysis of various datasets with the predicted noise 'output' data various forms of population analysis can be undertaken according to the specifications of the project, rather than being limited to the analysis options provided in noise prediction software. This is a particular issue as BS7666 2 compliant property gazetteers, joined to OS MasterMap TOIDs (Topographical Identifier), become the de facto standard for identifying individual receptor locations.
4.16 GIS will enable the noise results data to be presented in conjunction with other layers of geodata, such as land use, socio-economic indicators, crime etc. This presentation can take the form of hardcopy maps for consultation or as data for use by third parties with GIS (other SE departments) or as an information tool on the internet using a tool such as ArcIMS.
4.17 It can therefore be seen that GIS may potentially benefit four areas of noise mapping:
- Providing a common standard for databases already in use by other agencies to be included in noise mapping
- Providing an efficient means of editing and attributing and storing the model input data
- Undertaking analysis of results an conjunction with other geodatabases e.g. land use, population, and
- Presentation of results in hardcopy map or digital data formats
4.18 Limitations of the data supplied in relation to the prediction methodologies employed are discussed along with the implications of the accuracy of data on the validity and relevance of the model produced.
2 BS7666 Spatial-data-sets for geographical referencing. Specification for a street gazetteer