{"title":"带有噪声建模功能的 H-RISK:用于预测环境噪声和估算健康风险的 QGIS 插件","authors":"Junta Tagusari","doi":"10.21105/joss.06023","DOIUrl":null,"url":null,"abstract":"Exposure to environmental noise can have significant health effects, including environmental sleep disorders, hypertension, ischemic heart disease, and stroke. Accurately predicting sound levels and estimating health risks is critical to studying the exposure-response relationships and formulating effective policies at the local community level. However, such predictions typically require specialized knowledge, expensive commercial software, and extensive computational resources. To address this issue, the author has developed a solution that integrates publicly available vector tile maps, open source environmental noise modeling modules called “Noise-Modelling”, and user interfaces implemented in QGIS through a dedicated QGIS plugin. This plugin allows for direct execution of the calculation modules implemented in NoiseModelling, ensuring compatibility with future updates to NoiseModelling. Users can easily access and manipulate geographic features, define receiver points, predict sound levels, and estimate health risks for any desired area using the plugin. For a relatively small computational domain, such as 1 km2, the volume of calculations is manageable and can be performed on a local computer. This plugin is invaluable for conducting epidemiological research on the health effects of environmental noise and for noise policy planning. It facilitates the maintenance of a quiet environment, helps to mitigate noise problems, and aids in estimating the noise generated by new sources.","PeriodicalId":16635,"journal":{"name":"Journal of open source software","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"H-RISK with NoiseModelling: a QGIS plugin to predict\\nenvironmental noise and estimate health risks\",\"authors\":\"Junta Tagusari\",\"doi\":\"10.21105/joss.06023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Exposure to environmental noise can have significant health effects, including environmental sleep disorders, hypertension, ischemic heart disease, and stroke. Accurately predicting sound levels and estimating health risks is critical to studying the exposure-response relationships and formulating effective policies at the local community level. However, such predictions typically require specialized knowledge, expensive commercial software, and extensive computational resources. To address this issue, the author has developed a solution that integrates publicly available vector tile maps, open source environmental noise modeling modules called “Noise-Modelling”, and user interfaces implemented in QGIS through a dedicated QGIS plugin. This plugin allows for direct execution of the calculation modules implemented in NoiseModelling, ensuring compatibility with future updates to NoiseModelling. Users can easily access and manipulate geographic features, define receiver points, predict sound levels, and estimate health risks for any desired area using the plugin. For a relatively small computational domain, such as 1 km2, the volume of calculations is manageable and can be performed on a local computer. This plugin is invaluable for conducting epidemiological research on the health effects of environmental noise and for noise policy planning. It facilitates the maintenance of a quiet environment, helps to mitigate noise problems, and aids in estimating the noise generated by new sources.\",\"PeriodicalId\":16635,\"journal\":{\"name\":\"Journal of open source software\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of open source software\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21105/joss.06023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of open source software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21105/joss.06023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
H-RISK with NoiseModelling: a QGIS plugin to predict
environmental noise and estimate health risks
Exposure to environmental noise can have significant health effects, including environmental sleep disorders, hypertension, ischemic heart disease, and stroke. Accurately predicting sound levels and estimating health risks is critical to studying the exposure-response relationships and formulating effective policies at the local community level. However, such predictions typically require specialized knowledge, expensive commercial software, and extensive computational resources. To address this issue, the author has developed a solution that integrates publicly available vector tile maps, open source environmental noise modeling modules called “Noise-Modelling”, and user interfaces implemented in QGIS through a dedicated QGIS plugin. This plugin allows for direct execution of the calculation modules implemented in NoiseModelling, ensuring compatibility with future updates to NoiseModelling. Users can easily access and manipulate geographic features, define receiver points, predict sound levels, and estimate health risks for any desired area using the plugin. For a relatively small computational domain, such as 1 km2, the volume of calculations is manageable and can be performed on a local computer. This plugin is invaluable for conducting epidemiological research on the health effects of environmental noise and for noise policy planning. It facilitates the maintenance of a quiet environment, helps to mitigate noise problems, and aids in estimating the noise generated by new sources.