A 3D GIS tool for the detection of noise hot-spots from major roads

Puyana‐Romero, Virginia; Cueto, Jose Luis; Gey, Ricardo

doi:10.1016/j.trd.2020.102376

Cited by 12 publications

(3 citation statements)

References 17 publications

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“…The 3D city noise model can be used to display the intensity of noise levels in a particular area. However, several studies have been conducted for 3D road traffic noise visualization, and two-dimensional (2D) visualization was widely used [27]. NOPs are used to measure the noise level in a specific location, and interpolation is used to predict the noise level in the surrounding areas [24].…”

Section: Noise Observation Points (Nops)mentioning

confidence: 99%

Calculation of Road Traffic Noise, Development of Data, and Spatial Interpolations for Traffic Noise Visualization in Three-dimensional Space

Wickramathilaka,

Ujang,

Azri

et al. 2023

GaEE

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Road traffic noise visualization is vital in three-dimensional (3D) space. Designing noise observation points (NOPs) and the developments of spatial interpolations are key elements for the visualization of traffic noise in 3D. Moreover, calculating road traffic noise levels by means of a standard noise model is vital. This study elaborates on the developments of data and spatial interpolations in 3D noise visualization. In 3D spatial interpolation, the value is interpolated in both horizontal and vertical directions. Eliminating flat triangles is vital in the vertical direction. Inverse distance weighted (IDW), kriging, and triangular irregular network (TIN) are widely used to interpolate noise levels. Because these interpolations directly support the interpolation of three parameters, the developments of spatial interpolations should be applied to interpolate noise levels in 3D. The TIN noise contours are primed to visualize traffic noise levels while IDW and kriging provide irregular contours. Further, this study has identified that the TIN noise contours fit exactly with NOPs in 3D. Moreover, advanced kriging interpolation such as empirical Bayesian kriging (EBK) also provides irregular shape contours and this study develops a comparison for such contours. The 3D kriging in EBK provides a significant approach to interpolate noise in 3D. The 3D kriging voxels show a higher accurate visualization than TIN noise contours.

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Section: Noise Observation Points (Nops)mentioning

confidence: 99%

Calculation of Road Traffic Noise, Development of Data, and Spatial Interpolations for Traffic Noise Visualization in Three-dimensional Space

Wickramathilaka,

Ujang,

Azri

et al. 2023

GaEE

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“…The present research uses a 3D GIS-based tool for the identification and prioritization of the hot-spots on major roads (HSIP 3D-tool for short). An extensive description of the tool applied is discussed in the research article [38] and the Supplementary Material File S3.…”

Section: Comparison Of the Hot-spot Of The Study Area Calculated With...mentioning

confidence: 99%

Community Response to Noise from Hot-Spots at a Major Road in Quito (Ecuador) and Its Application for Identification and Ranking These Areas

Puyana‐Romero

Cueto

Ciaburro

et al. 2022

IJERPH

Self Cite

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Environmental legislation in Ecuador is advancing with the legitimate aspiration of providing citizens with new standards of quality and environmental health. In the context of environmental noise, these legislative advances are based on the experience accumulated in other countries, which is an advantage that must be managed with caution by incorporating local factors into noise management procedures. This study advances two lines of work. The first is to survey the population about their attitude towards noise from a major road to try to detect local factors in the annoyance and sleep disturbances. The second uses this information to compare noise indicators for the detection and ranking of hot-spots from major roads. The interviewees exhibited a high level of annoyance and sleep disturbance due to noise compared with the results of other studies. Results show that there are small differences in the definition of hot-spots when using WHO’s dose–response curves for Lden ≥ 68 dB for and for Lnight ≥ 58 dB, in comparison with the curves generated in this study (CS). Regarding the application of both dose–response curves (WHO vs. CS) to the estimation of the population at risk of the harmful effect of nighttime traffic noise (HSD), small oscillations are also observed even when Lnight ≥ 58 dB and Lnoche ≥ 60 dB are used.

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“…Gutierrez‐Osorio and Pedraza 27 reviewed the state‐of‐the‐art methods that assist practitioners to forecast road accidents, which are derived from various means such as neural network, data analysis, and deep learning methods. Puyana‐Romero et al 28 . developed a technique to identify the noisiest spot on the roads, they used 3‐D making devices to provide information and brush up the data to allocate the noise hotspot in different parts of thoroughfare.…”

Section: Introductionmentioning

confidence: 99%

A hybrid method based on P and P′ control chart for identifying hotspots

Jahan

Abbaspour

Safakhah

2021

Quality & Reliability Eng

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The terms “hotspots,” “blackspot,” or “high‐risk” are normally used for an area on a road where the number of car accidents are far beyond the normal level and, more importantly, the causes of the incident always link to one or many specific reasons. Identifying these spots is helpful and may assist people in authority to implement corrective actions. To do the aforementioned, some decision‐support tools could be useful since they enable us to monitor the indicators that may lead to a car accident, same as the procedure engineers use to control production lines in factories. In this regard, control charts are utilized to identify blackspots. Although the method is low cost, and provides quick detection and statistical reliability level and, more importantly, uses online applications; however, it advised that the rate quality control method could be used on roads with the same geometry and traffic conditions. This research develops a hybrid method, based on accident type, for improving rate quality control method to overcome the shortcomings. Furthermore, the suggested framework considers crash severity and traffic volume that have not been taken into account in the rate quality control method yet. The case study evaluates how this framework is successful to identify blackspots, and based on the result in the real environment, it reveals that the proposed method could detect and identify the hotspots.

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A 3D GIS tool for the detection of noise hot-spots from major roads

Cited by 12 publications

References 17 publications

Calculation of Road Traffic Noise, Development of Data, and Spatial Interpolations for Traffic Noise Visualization in Three-dimensional Space

Calculation of Road Traffic Noise, Development of Data, and Spatial Interpolations for Traffic Noise Visualization in Three-dimensional Space

Community Response to Noise from Hot-Spots at a Major Road in Quito (Ecuador) and Its Application for Identification and Ranking These Areas

A hybrid method based on P and P′ control chart for identifying hotspots

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