Landscape visual quality influence on noise pollution propagation in urban green areas

Oliveira, Jefferson Dias de; Biondi, Daniela; Reis, Allan Rodrigo Nunho dos; Viezzer, Jennifer

doi:10.15446/dyna.v88n219.94724

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…Finally, the exposed model is more efficient compared to other convolutional network architectures that have been implemented in the recognition of common environmental sounds [3,17] with parameters between 25'636.712 and 143'667.240. Since it reported satisfactory results in accuracy and prediction speed for the dimensions of the model presented with 54,000 parameters.…”

Section: Resultsmentioning

confidence: 99%

“…However, these applications initially developed for the military industry can be used in mining, surveillance of critical infrastructure, protection, and conservation of the environment [3,4]. Artificial intelligence provides solutions for the recognition of radio frequency [5] and audio signals at a very low cost, which have been developed with different objectives, such as the detection of drones [6] or the measurement of noise pollution [3]. The study of deep learning models in environmental settings is presented as a tool for monitoring infrastructures of environmental and material value.…”

Section: Introductionmentioning

confidence: 99%

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Military artificial intelligence applied to sustainable development projects: sound environmental scenarios

Corzo-Ussa,

Álvarez-Aros,

Mariño

et al. 2023

DYNA

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Artificial intelligence (AI) used in intelligence, surveillance, and reconnaissance (ISR) has a high application interest in project management. This article presents a result of military research on ISR applicable to monitoring and recognition of audio signals for environmental protection and critical infrastructure. Two databases with environmental sounds were built from open access platforms for training, validation, and testing. The identification characteristics for IA are extracted from the preprocessing of the sounds, obtaining the Mel Frequency Cepstral Coefficients (MFCC). As a result, model performance for more realistic soundstages shows higher accuracy compared to training categories in identifying signal frequency and duration settings. It is concluded that the model is applicable to various environmental scenarios as a low-cost alternative technology to be applied in sustainable project management.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Military artificial intelligence applied to sustainable development projects: sound environmental scenarios

Corzo-Ussa,

Álvarez-Aros,

Mariño

et al. 2023

DYNA

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“…Recent studies propose an alternative approach for calculating sound propagation in green areas. De Oliveira et al [75] found a highly significant relationship between the visual quality of the landscape and noise attenuation.…”

Section: Quiet Areas In Noisy Urban Environmentsmentioning

confidence: 98%

Influence of Green Areas on the Urban Sound Environment

Rey-Gozalo,

Barrigón Morillas,

Montes González

et al. 2023

Curr Pollution Rep

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Purpose of Review Urban green spaces provide benefits for human health and well-being, among other properties, thanks to their ability to attenuate environmental pollutants. The sound environment is not healthy in most cities, and this situation has not changed in recent decades. These green spaces are potential quiet areas with good acoustic quality if they are designed and planned properly from a multidisciplinary perspective. Although the mitigating effects of green infrastructure have been extensively studied, their application in green areas has been very limited. The objective of this study is to analyze those characteristics of green spaces that contribute to a healthy soundscape and, in turn, the benefits that this would give them to the characteristics of green areas, users, and their physical environment. Recent Findings Current studies show that to accurately determine the relationship between green spaces and health and well-being benefits, it is necessary to know the interaction with other environmental variables, including the soundscape. The development and application of ISO/TS 12913-2 have promoted the consideration of the soundscape and the use of appropriate procedures for its evaluation. Summary The inclusion of soundscape quality in epidemiological studies will improve the quantification of the effects of green spaces on the health and well-being of citizens. Only the consideration of global indicators, such as Lden (dB), show the importance of the sound environment in the interaction with other environmental variables and user activities for the determination of the effects of green spaces on health.

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“…Additionally, incorporating vegetation has proven to be effective in reducing noise in urban settings. Landscaped areas planted with more vegetation and more complex vegetation structure are often effective in reducing significant levels of attenuated noise (Oliveira et al, 2021a;Oliveira et al, 2021b). Vegetation landscaping tends to absorb more sound as the distance between them and the traffic sound source decreases (Akay & Önder 2022).…”

Section: Introductionmentioning

confidence: 99%

In-situ noise attenuation effect of urban vegetation landscaping in typical residential communities along the elevated Metro overpass

Wu,

Huang,

2023

Preprint

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Vegetation landscaping around the Metro overpass can impact the noise attenuation effect in surrounding residential areas. Six residential buildings with vegetation landscaping situated along the elevated Metro overpass of Hangzhou Metro Line 9 were chosen to assess their noise levels on sites at the 1st to 5th floors. Quantitative investigation of the vegetation landscaping condition and the noise loudness was conducted in-situ, and the greening conditions of the vegetation were investigated quantitatively, including canopy closure, greening rate, height under the lowest branch of the arbour, number of arbours, and the effective spatial occlusion coefficient (ESOC), etc. The in-situ noise loudness of each measurement site was also determined. A 3-D model of community was also created in Rhinoceros software and imported into Cadna/A software to calculate the simulated noise loudness of the scenario without vegetation. The net noise attenuation coefficient by vegetation (NACV) was calculated to quantify the noise reduction effect by vegetation landscaping. A Python statistical program is applied to perform a linear regression analysis and propose a mathematical model for describing noise attenuation effect. It indicated that the ESOC, canopy closure and the greening rate could jointly explain 71.6% of variations in mean NACV. The influence of factors was found in the following order: distance between the vegetation and the noise source > height of the noise source > greening rate > ESOC. This study reveals the characteristic factors and correlations of noise attenuation and explores the effect of vegetation landscaping on urban noise attenuation.

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Landscape visual quality influence on noise pollution propagation in urban green areas

Cited by 5 publications

References 18 publications

Military artificial intelligence applied to sustainable development projects: sound environmental scenarios

Military artificial intelligence applied to sustainable development projects: sound environmental scenarios

Influence of Green Areas on the Urban Sound Environment

In-situ noise attenuation effect of urban vegetation landscaping in typical residential communities along the elevated Metro overpass

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