The Analysis Of The Traffic Noise, In An Area Densely Populated, With Gis Software Used In The Educational Process (original) (raw)
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The Use of GIS in Studying and Modeling Traffic Noise and its Relationship to Land Uses in Riyadh
This study aims to monitor, analyze and model spatial relationships of traffic noise and its intensity in major streets of Riyadh and surrounding residential areas. We shall adopt a mathematical model to obtain noise intensity level from the average number of passing vehicles in the road, their average speed and the percentage of trucks. By using methods of spatial data insertion in GIS system, it was possible to prepare noise maps (continuous area) which shows the nature and pattern of noise distribution in roads and surrounding areas, one set throughout the day and another through peak hours. These maps are useful for delineating areas with high noise level and areas of low noise levels. This information, in turn, is useful for selection of sites for land uses that require low level of noise, such as health facilities, schools, public libraries, etc. By analyzing the relationship between noise and land use of areas surrounding roads, it was possible to know the relationship between the activities and land uses of areas adjoining road, and the level of noise in the roads. The spatial analysis was also useful in understanding the factors that lead to the high noise levels in some roads. The conclusion contains recommendations and planning criteria that may help planners and decision makers to reduce noise levels down to allowable levels, to preserve people's health and comfort and conserve the environment.
2001
Traffic noise is a significant effect of transport in urban areas and a priority issue in the EU. Noise as an environmental factor needs to be considered more closely when transport policies and relevant measures are examined and planned to tackle transport related problems. There is a need for including impacts on noise both at the macro and the micro level. Existing official traffic noise calculation methods mainly focus on the former. By using suitable methods for both these levels in combination with transport simulation models and GIS technology, it is possible to approach the whole issue in a more comprehensive way. Visualisation of problem areas and spots with extreme effects as well as other traffic parameters is easily achieved with the use of GIS functionality.
Study of the Noise Generated by a Major Road in a City
ANNALS OF THE ORADEA UNIVERSITY. Fascicle of Management and Technological Engineering., 2015
The paper presents a case study regarding a the noise generated by the road traffic on a main road that traverse a city. Since no input data was available, all data was produced using free available sources for the base map and data collected on site for the traffic volumes and speed. The methods and tools used to process the outputs are also presented. Beside the noise mapping software, are used GPS, GIS and CAD techniques.
IRJET- ANALYSIS OF NOISE POLLUTION USING GIS IN TRICHY DISTRICT
IRJET, 2020
In developing country like India with the vehicle population increasing at a rapid rate, the residents of cities are experiencing severe environmental problems that results from road traffic in particular from automobiles. Fast growing vehicle population in town in the recent years, has resulted in considerable increase in traffic on roads causing alarming noise pollution. The spatial analysis and geo statistical methods of GIS can play an important role to control noise pollution. This paper describes a study that aimed at measuring the noise levels at selected points in Trichy district to generate a noise map over the study area.
Evaluation of traffic noise pollution in a central area of Tehran through noise mapping in GIS
Advances in Environmental Biology, 2012
Although development in transportation system in economic-social fields is considered very useful for societies but nowadays noise pollution is known as one of the main environmental problems while it is the most important sources of pollution in crowded urban districts. Exposing with high noise level in capital cities may be resulted in disorder in daily activities in work place, school, and home because of reducing hearing, social behavior disorders, disorder in sleep, and cardiovascular diseases during a long time. The purpose of the study is going to analyze spatial characteristics of traffic noise in the urban district through measuring sound at 41 stations with residential, medical, educational, commercial-residential, and commercial uses in area 3 of district 6 of Tehran. Parameters including SPL, Lmin, Lmax, Leqav were measured during three intervals ranged from 7-9 am (peak traffic hours), 11-13 (non-peak traffic hours) and 57 pm (peak traffic hours) in fall,2010. Desired l...
Environmental Modelling and Software, 2003
This paper describes a road traffic noise calculation and visualization package TNoiseGIS. It is implemented by utilizing the inbuilt database and spatial routines of a popular commercial Geographical Information System (GIS). The noise calculations can be made according to either of two alternative noise calculation models: the UK CORTN and US FHWA models. These models are applicable for calculating noise levels along highways with free flowing traffic. By applying the inbuilt spatial operations to the geographically located information, noise emission values can automatically be provided for any number of receptor points using either algorithm. The graphical user interface of the GIS simplifies the input of the attributes of the different receptor points and road links. Line and block barriers can be defined and applied with the interpolation technique for calculating traffic noise on receiver points along the back edge of barrier parallel to roadway. As a result, all noise levels behind the barrier can be efficiently estimated. In addition to the calculation of noise emission values for a specified set of receptor points, the variation in the noise levels along the highway can be visualized in the form of noise contours. Such contours provide a visual description of the soundscape and also information on the importance of different factors for soundscape quality. By changing traffic flow parameters such as the localization of planned roads, dwellings, and barriers with different size and location, TNoiseGIS functions as a road traffic noise prediction tool and a tool for planning environmentally friendly road and road traffic noise solutions. The noise calculations and visualization algorithms are implemented by means of scripts that will be made available at a lower cost and also user modifiable.
The important problem is protection of population from high noise. This problem was discussed in the article. Also in the article was showed the necessity of the noise maps of the city for making correct management decisions is proved. There are presented data on the change in the number of vehicles on the territory of the European Union and Russia, information about noise levels in the territories along the roads in the cities of Russia, the algorithm for generating noise maps of the city. There were estimated noise levels generated by vehicles, in the Central part of the city of St. Petersburg for two scenarios: first on the basis of field studies on the composition and intensity traffic, second – on forecast of limiting vehicle traffic. Conclusion: restriction of movement of vehicles can reduce impact, noise, and values of the maximum concentrations near streets with restricted movement, but at the same time can increase the negative impact of the near streets, where will be redistributed transport stream. The decrease in the maximum ground level concentrations and levels of noise for such a big city like St. Petersburg will contribute to complex of environmental measures: improving fuel, classes environmental performance of vehicles, the development of the road network with traffic organization based estimate of environmental consequences of the proposed activities.
Development of Noise Prediction Models Using GIS for Chennai City
– Noise pollution is a problem increasingly acknowledged by authorities and governments around the globe. Geographical Information Systems (GIS) can conveniently be adapted together, analyze and present noise information. GIS provide framework to integrate noise calculation models with spatial data that can be used for building noise maps. Noise maps can be used to assess and monitor the influence of noise effects. In the reality, noise travels in all directions. Residents living in high rise buildings are also severely affected by traffic noise. It is therefore important to develop noise maps that can show influence of noise in all direction. A case study was illustrated using noise maps for Chennai city. The quality of the results of noise effect studies depends on the quality of the data and models used. The integration of GIS and noise maps makes it possible to increase the quality of noise effect studies by automating the modeling process, by dealing with uncertainties and by applying standardized methods to study and quantify noise effects. It is found that the noise level in most places are above standard levels.
IRJET- MAPPING AND ASSESSMENT OF NOISE POLLUTION USING GIS IN CALICUT CITY
IRJET, 2020
paper deals with the study of noise pollution scenario of this city, a GIS based noise assessment was carried out at various zones viz.. residential zone, industrial zone, silent zones, commercial zones along with major traffic intersections within the city. The main objective of this paper is to get public awareness about the noisy environment with which we lives today due to the increased urbanization and increased traffic intensity. Using QGIS Software, noise maps are generated to make the awareness more accurately. Key Words: QGIS-Quantum geographic information system, GIS-Geographic information system, SLM-Sound level meter, L10: A weighted noise level exceeding 10% of time, Leq-equivalent noise level, dB-decibel, L50-A weighted noise level exceeding 50% of time, L90-A weighted noise level exceeding 90% of time.