Mapping for Sustainability: Environmental noise and the City

Murphy, Enda; King, Eoin A.

doi:10.4135/9781526401748.n7

Cited by 5 publications

(3 citation statements)

References 40 publications

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“…For whichgeographic information system (GIS) is very effective and widely accepted as an "automated system for the capture, storage, retrieval, analysis, and display of spatial data" [11]. GIS allowsoverlaying different information in an integrated manner that is perceptive and communicable todifferent stakeholders [12]. Hence, GIS effectively integrates, represents, and communicates datato guide the planning process of UGS.…”

Section: IImentioning

confidence: 99%

Comprehensive Land Use and Land Cover Classification in Chhatrapati Sambhajinagar City, Maharashtra, India, Using Satellite Imagery and Machine Learning Techniques

Lahane,

Manza

2023

IJRASET

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In This research presents an extensive analysis of land use and land cover (LULC) classification in Chhatrapati Sambhajinagar City, a rapidly expanding urban centerin Maharashtra, India, highly susceptible to climate change. Using remote sensing and GIS techniques, the research evaluates the impact of LULC on ecosystem service values (ESV) over a nine- year period (2013-2021). Satellite-based data were utilized to quantify LULC changes, encompassing Green Area, Buildup Area, Road Area, WaterBodies, and Barren Land. The research employs five distinct classification methods and investigates the effectiveness of pre-processing techniques in improving classification accuracy during selected years (2013, 2016, 2019, and 2021). The performance of Mahalanobis Distance, Maximum Likelihood, Parallelepiped, and Support Vector Machine methods is assessed under both preprocessed and non-preprocessed conditions, using overall accuracy and Kappa accuracy as evaluation metrics. The results reveal consistent enhancements in overall accuracy, with Mahalanobis Distance, Maximum Likelihood, and Support Vector Machine methods demonstrating percentage improvements ranging from 0.43% to 5.08% after preprocessing. Particularly noteworthy are the substantial percentage increases in Parallelepiped Classification, ranging from 23.74% to 53.34%, highlighting the transformative impact of preprocessing on its accuracy. These findings emphasize the necessity for customized preprocessing strategies to refine the precision of LULC classification models, offering valuable contributions to the realms of remote sensing and geospatial analysis. Moreover, the insights gleaned from this research provide crucial guidance for urban growth management and climate resilience strategies in rapidly developing urban areas, making it a valuable resource for sustainable urban planning

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Section: IImentioning

confidence: 99%

Comprehensive Land Use and Land Cover Classification in Chhatrapati Sambhajinagar City, Maharashtra, India, Using Satellite Imagery and Machine Learning Techniques

Lahane,

Manza

2023

IJRASET

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“…In summary, the previous discussion points out the effects of environmental noise on the three dimensions of sustainable development: environmental, social, and economic. If the concept of sustainability outlined above is taken seriously, it is clear that the current level of exposure to environmental noise poses a considerable threat to the health and well-being of current and future generations in cities [29]. It is therefore important to consider noise pollution to achieve sustainable cities.…”

Section: Introductionmentioning

confidence: 99%

Noise Estimation Using Road and Urban Features

et al. 2020

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Noise pollution must be considered to achieve sustainable cities because current levels of exposure to environmental noise are a considerable risk to the health and quality of life of citizens. Urban features and sound levels were registered in 150 streets in the Chilean cities of Talca and Valdivia to analyze the relationship between both types of variables. Urban variables related to street location, urban land use, street geometry, road traffic control, and public and private transportation showed very significant correlations with the noise levels, and multiple regression models were developed from these variables for each city. Models using only urban variables in Valdivia and Talca explained 71% and 73%, respectively, of the variability of noise. The prediction error was similar in the different types of urban roads and did not exhibit significant differences between models developed in different cities. The urban models developed in one city could, therefore, be used in other similar cities. Considering the usefulness of these variables in urban planning, these models can be a useful tool for urban planners and decision-makers to implement action plans regarding noise pollution.

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“…The spatial dataset augmented with detailed landscape layers facilitates the effective communication and evaluation of service supply or the demand side of UGS [16], for which geographic information system (GIS) is very effective and widely accepted as an "automated systems for the capture, storage, retrieval, analysis, and display of spatial data" [17] (p. 13). GIS allows overlaying different information in an integrated manner that is perceptive and communicable to different stakeholders [18]. Hence, GIS effectively integrates, represents and communicates data to guide the planning process of UGS.…”

Section: Introductionmentioning

confidence: 99%

Mapping Methodology of Public Urban Green Spaces Using GIS: An Example of Nagpur City, India

Lahoti

Kefi

Lahoti³

et al. 2019

Sustainability

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Faced with a lack of fine grain data availability, in rapidly emerging urban centers of developing nations, the study explored a mapping methodology to create thematic map of public urban green space (UGS). Using GIS, a thematic map of Nagpur city, India was prepared. The objective was to prepare spatial data that are relevant for planners and policy makers, with detailed UGS typologies and to update the status of overall availability and distribution of hierarchical recreational green spaces in the city. The spatial and non-spatial data with added attributes gathered through fieldwork resulted in a holistic dataset, with high accuracy of thematic map (0.93 kappa coefficient). The recorded status of different typologies as well as the distribution of recreational UGS shows disparity in the distribution of UGS. The eastern part of the city grossly lacks UGS provisions, which is compensated by the western part with larger availability of natural green spaces. The mapping methodology is novel and effective for recording qualitative status, analyzing their spatial distribution and prioritizing the provisions of UGS. Future research integrating these spatial data with more qualitative research can provide a holistic view on benefits of UGS provisions and thus facilitate effective UGS governance aiming towards better green infrastructure and hence broader urban sustainability.

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Mapping for Sustainability: Environmental noise and the City

Cited by 5 publications

References 40 publications

Comprehensive Land Use and Land Cover Classification in Chhatrapati Sambhajinagar City, Maharashtra, India, Using Satellite Imagery and Machine Learning Techniques

Comprehensive Land Use and Land Cover Classification in Chhatrapati Sambhajinagar City, Maharashtra, India, Using Satellite Imagery and Machine Learning Techniques

Noise Estimation Using Road and Urban Features

Mapping Methodology of Public Urban Green Spaces Using GIS: An Example of Nagpur City, India

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