Dataset Name: END Noise Data Round 3 - 2017Data Owner: DAERAContact: Air and Environmental Quality Unit amy.holmes@daera-ni.gov.ukSource URL: https://gis.daera-ni.gov.uk/arcgis/apps/MapSeries/index.html?appid=0bf4f42018224494b071b5dcd0ce4e56Uploaded to SPACE Hub: 12/06/23Update Frequency: Every 5 yearsScale Threshold: N/AProjection : Irish GridFormat: Esri Feature Layer (Hosted) Vector PolygonNotes: This data is a product of the strategic noise mapping analysis undertaken by DAERA Northern Ireland in 2017 to meet the requirements of the EU Environmental Noise Directive (Directive 2002/49/EC) and Environmental Noise Regulations (Northern Ireland) 2006. NOISE SOURCES AGGLOMERATION ROAD (agg-road) Data indicating the level of noise according to the strategic noise mapping of major road sources within areas with a population of at least 100,000 people (Belfast Metropolitan Urban Area agglomeration).AGGLOMERATION RAIL (agg_rail) Data indicating the level of noise according to the strategic noise mapping of major rail sources withinINDUSTRY (agg_ind) Data indicating the level of noise according to the strategic noise mapping of all Part A industrial activities as defined in Schedule 1 of the Pollution Prevention and Control Regulations (Northern Ireland) 2003 (as amended) and all ports within the Belfast Metropolitan Urban Area (BMUA) agglomeration.AGGLOMERATION AIRPORT (BCA) Data indicating the level of noise according to the strategic noise mapping of airport sources within areas with a population of at least 100,000 people (Belfast Metropolitan Urban Area agglomeration). In Northern Ireland, the agglomeration airport is George Best Belfast City Airport. CONSOLIDATED (con) Data indicating the level of noise according to the strategic noise mapping of all noise sources within the Belfast Metropolitan Urban Area (BMUA) agglomeration.MAJOR AIRPORT (BIA) Data indicating the level of noise according to the strategic noise mapping of airport sources with more than 50,000 air traffic movements per year. In Northern Ireland, the major airport is Belfast International Airport (BIA).MAJOR RAIL (mrail) Data indicating the level of noise according to the strategic noise mapping along NI Translink routes with more than 30,000 train passages per year.MAJOR ROAD (mroad) Data indicating the level of noise according to the strategic noise mapping along major traffic routes with more than 3,000,000 vehicle passages per year. NOISE INDICATORS Lden (lden) The LAeq over the period 0000-2400, but with the evening values (1900-2300) weighted by the addition of 5 dB(A), and the night values (2300-0700) weighted by the addition of 10dB(A) Lday (lday) The LAeq over the period 0700-1900, local time (for strategic noise mapping this is an annual average)Levening (leve) The LAeq over the period 1900-2300, local time (for strategic noise mapping this is an annual average)Lnight (lngt) The LAeq over the period 2300-0700, local time (for strategic noise mapping this is an annual average)LAeq,6h (l6h) The LAeq over the period 2400-0600, local time (for strategic noise mapping this is an annual average)LAeq,16h (l16h) The LAeq over the period 0700-2300, local time (for strategic noise mapping this is an annual average)LAeq,18h (l18h) The LAeq over the period 0600-2400, local time (for strategic noise mapping this is an annual average) ------------------------------------------------------------------------------------------- For informations on the noise data and modelling methods used, please refer to the DAERA Northern Ireland website:https://www.daera-ni.gov.uk/services/noise-mapsContact details:Amy Holmes (amy.holmes@daera-ni.gov.uk)Air and Environmental Quality Unit - Regulatory and Natural Resources Policy DivisionDepartment of Agriculture, Environment and Rural Affairs (DAERA NI)

Defra has published strategic noise map data that give a snapshot of the estimated noise from major road and rail sources across England in 2017. The data was developed as part of implementing the Environmental Noise Directive.

This publication explains which noise sources were included in 2017 strategic noise mapping process. It provides summary maps for major road and rail sources and provides links to the detailed Geographic Information Systems (GIS) noise datasets.

This data will help transport authorities to better identify and prioritise relevant local action on noise. It will also be useful for planners, academics and others working to assess noise and its impacts.

Noise mapping Geographic Information Systems (GIS) datasets

Rail noise

• https://environment.data.gov.uk/dataset/5836745c-4e11-4767-94a5-2656f82e01a3">Laeq 16h: indicates the annual average noise levels for the 16-hour period between 0700 – 2300

• https://environment.data.gov.uk/dataset/e8e78e12-9297-450b-b875-e0523cb3c9ea">Lden: indicates a 24 hour annual average noise level with separate weightings for the evening and night periods

• https://environment.data.gov.uk/dataset/f6c0e3b6-3186-4d0a-b0e7-ca32bfb6573f">Lnight: indicates night time annual average noise level results in dB, where night is defined as 2300 - 0700

Road Noise

• https://environment.data.gov.uk/dataset/b9c6bf30-a02d-4378-94a0-2982de1bef86">Laeq 16h: indicates the annual average noise levels for the 16-hour period between 0700 – 2300

• https://environment.data.gov.uk/dataset/fd1c6327-ad77-42ae-a761-7c6a0866523d">Lden: indicates a 24 hour annual average noise level with separate weightings for the evening and night periods.

• https://environment.data.gov.uk/dataset/cc48e728-602a-4e8a-9221-49f661ab58f8">Lnight: indicates night time annual average noise level results in dB, where night is defined as 2300 - 0700

Other

• https://environment.data.gov.uk/dataset/4739c0c3-e800-4cb1-89cd-e71115b191e9">Agglomerations: urban areas Defra is required to undertake strategic noise mapping
• https://environment.data.gov.uk/dataset/55cdd950-fd18-421a-affd-130d659dc6fd">Noise action planning important areas: provide a framework for the local management of the Important Areas.

Noise exposure data

We’ve published data which shows the estimated number of people affected by noise from road traffic, railway and industrial sources.

• https://data.gov.uk/dataset/d461bbc1-eb51-4852-8a9a-45dbf28aa230/noise-exposure-data-round-3">Noise exposure data

The 2020 National Transportation Noise Map dataset utilized transportation mode input data from 2020 in a model and is current as of October 2022, published by the Bureau of Transportation Statistics (BTS), and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). Please see the website https://www.bts.gov/geospatial/national-transportation-noise-map, for downloads and more information about these datasets. For web services of these data, please navigate to https://geo.dot.gov/server/rest/services/Hosted and search for service names beginning with "Noise." Please contact j.goworowska@dot.gov for any questions. Data within the National Transportation Noise Map represent potential noise levels across the nation for an average annual day for the specified year. These data are intended to facilitate the tracking of trends in transportation-related noise by mode collectively over time and should not be used to evaluate noise levels in individual locations and/or at specific times. This dataset is developed using a 24-hr equivalent A-weighted sound level (denoted by LAeq) noise metric. The results represent the approximate average noise energy due to transportation noise sources over a 24-hour period at the receptor locations where noise is computed. Layers include Aviation, Freight and Passenger Rail, and Road Noise for the Lower 48 States as well as Alaska and Hawaii. The full listing can be found below. 2020 National Transportation Noise

      Alaska

             Alaska Aviation Noise
             Alaska Freight and Passenger Rail Noise
             Alaska Freight and Passenger Rail, Road, and Aviation Noise
             Alaska Road and Aviation Noise
             Alaska Road Noise

      Lower 48 States (CONUS)

             Lower 48 States (CONUS) Aviation Noise
             Lower 48 States (CONUS) Freight and Passenger Rail Noise
             Lower 48 States (CONUS) Freight and Passenger Rail, Road, and Aviation Noise
             Lower 48 States (CONUS) Road and Aviation Noise
             Lower 48 States (CONUS) Road Noise

      Hawaii

             Hawaii Aviation Noise
             Hawaii Road and Aviation Noise
             Hawaii Road Noise

EU Directive 2002/49/EC, transposed into Irish law by Statutory Instrument number 140 of 2006 (the ‘Environmental Noise Regulations 2006’), calls for the development of strategic noise maps and action plans for major roads, railways, airports and cities.

Under the Regulations, TII is responsible for the development of noise maps for all national roads Carrying in excess of 3 million vehicles a year.

For the 2012 phase of noise mapping, strategic noise maps were developed for just over 3 000 km of national roads. Additional noise maps were also developed for major non-national roads. The website displays noise maps for major roads outside the agglomerations of Dublin and Cork. These maps were developed by the Authority in 2012.

Visualisations are available here - http://nra-gis.maps.arcgis.com/apps/Compare/Configure/index.html?appid=0a26a9dd79fd44a68dd90f5445449701

This is a polygon dataset of the strategic noise mapping of roads, which were identified as those roads exceeding the flow threshold of 3 million passages per year, in the form of noise contours for the Lnight (night) period for Dublin and Cork agglomerations and the major roads outside of the agglomerations. The dB value represents the average decibel value during the Lnight time.

Any direct comparison of the Round 3 versus Round 2 results should be carefully considered, as changes to the model input datasets used between these rounds may be significant. This may especially apply to the terrain model used, while there may be improved building height data, & improved traffic flow data with fewer assumed flows. There may also be some revisions to the actual road network modelled in Round 3.

The noise maps are the product of assimilating a collection of digital datasets, and over the last 10 years there has been significant improvements to the quality of the digital datasets describing the natural and built environment in Ireland. This has led to the strategic noise models giving much more reliable noise results with much less tendency to over predict the impact.

UPDATE (February 2019): The Regional roads in 26 Local Authorities (LAs) outside of Dublin, and Cork have now been amended by Transport Infrastructure Ireland (TII). The original road maps had included some significant stretches of roads (~20%) that were below the 3 million vehicles movements/annum reporting threshold. These road sections have now been removed and revised Regional road maps have been released by TII.

This TII review process has resulted in an update of the National road map that is reported to the EEA. The EPA has also updated our website to reflect these changes, and we will also look to provide relevant links to the Final LA Noise Action Plans (when completed): https://www.epa.ie/monitoringassessment/noisemapping/ For more information on this dataset please go to https://gis.epa.ie/geonetwork/srv/eng/catalog.search#/metadata/5be19c63-2963-4d51-9a06-a0570b49f18e

Levels of Noise Pollution in Hampshire and the Isle of Wight Integrated Care System (ICS) during Nighttime and 24-Hour Periods Based on Data from Strategic Noise Mapping. An Interactive Map Application Recommended Citation: Tsimpida, D., & Tsakiridi, A. (2025). Levels of noise pollution in Hampshire and the Isle of Wight Integrated Care System (ICS) during nighttime and 24-hour periods based on data from strategic noise mapping: An interactive map application. License: CC BY – This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. Information about Geographic Location of Data Collection: England Related Projects: Tsimpida, D., Environmental Health and Wellbeing Dynamics: Mapping High-Exposure Neighbourhoods and Assessing Transportation Noise Pollution's Impact on Population Health. This project is funded by the Sustainability & Resilience Institute (SRI), University of Southampton. The views expressed are those of the author(s) and not necessarily those of SRI or the University of Southampton. Methodological Information: To quantify noise pollution, we used the new Noise Mapping Geographic Information Systems (GIS) datasets developed by Defra that calculate noise exposure levels and are openly available: Department for Environment, Food & Rural Affairs. Strategic noise mapping (2022) [Internet]. 2024. Available from: https://www.gov.uk/government/publications/strategic-noise-mapping-2022 For our analyses, we used both the day-evening-night level (Lden) and the night level (Lnight). The Lden level is a noise metric used to assess overall annoyance, calculated as the annual average A-weighted sound level over a 24-hour period. This measure includes a 5-decibel (dB(A)) penalty for evening noise (7 pm to 11 pm) and a 10 dB(A) penalty for nighttime noise (11 pm to 7 am). The Lnight is a nighttime noise indicator that reflects the annual average A-weighted sound level during the night period (11 pm to 7 am), representing the total sound energy equivalent to the fluctuating noise levels experienced throughout that period. _ Geospatial Analysis Information: All geospatial models in this study used Lower Super Output Areas (LSOAs) as the unit of analysis. In all analyses, we used the LSOA boundaries published by the Office for National Statistics as of March 21, 2021: Office for National Statistics. Census 2021 geographies [Internet]. 2021. Available from: https://www.ons.gov.uk/methodology/geography/ukgeographies/censusgeographies/census2021geographies _ Integrated Care Board Boundaries: Digital vector boundaries for Integrated Care Boards in England were those published by the Office for National Statistics: Integrated Care Boards (April 2023) EN BGC [Internet]. 2023. Available from: https://www.data.gov.uk/dataset/d6bcd7d1-0143-4366-9622-62a99b362a5c/integrated-care-boards-april-2023-en-bgc This version of the dataset, https://doi.org/10.5258/soton/d3377v2, was updated on 2015/02/17. The previous version is available at https://doi.org/10.5258/soton/d3377v1

This is a polygon dataset of the strategic noise mapping of airports, in the form of noise contours for the Lnight (night) period for Dublin and Cork agglomerations airports. The dB value represents the average decibel value during the Lnight time.Any direct comparison of the Round 3 versus Round 2 results should be carefully considered, as changes to the model input datasets used between these rounds may be significant. This may especially apply to the terrain model used, while there may be improved building height data, & improved traffic flow data with fewer assumed flows. There may also be some revisions to the actual road network modelled in Round 3.The noise maps are the product of assimilating a collection of digital datasets, and over the last 10 years there has been significant improvements to the quality of the digital datasets describing the natural and built environment in Ireland. This has led to the strategic noise models giving much more reliable noise results with much less tendency to over predict the impact.For more information on this dataset please go to https://gis.epa.ie/geonetwork/srv/eng/catalog.search#/metadata/c2a992d0-e492-424d-8546-4fe765bc272c

This GIS dataset was created to identify the day-night average noise levels around both Ault Field and Outlying Field (OLF) Coupeville. This created the Air Installations Compatible Use Zones (AICUZ) noise contours. This was revised in 2005 through a study done by the Navy in March 2005. The Onyx Group was the primary consultants for this study. The GIS work for the AICUZ noise zones was done by Wyle Laboratories in California.

Validation of results for 2D and 3D noise mapping.

Silencio’s Noise Pollution Index Maps provide on-demand, high-resolution visualizations of urban and regional noise patterns worldwide. Built from 35 billion+ real noise measurements and AI-enhanced interpolation, these maps are designed for seamless integration into GIS platforms, smart city dashboards, and real estate location intelligence tools. Only available on request - data in sample is the measurement basis on which the maps are created.

Maps are generated on-demand for: • Cities, regions, or custom-defined areas globally • Real estate platforms for environmental and livability scoring • Government portals and dashboards for noise regulation, urban planning, and public health monitoring • Smart city applications to visualize urban soundscapes and improve planning and infrastructure design

Key Features: • Global coverage with consistent high-density data across continents • Generated specifically based on client-selected regions or cities • Fully GIS-ready in high-resolution image formats • Derived from real measurements combined with AI-powered interpolation for accuracy

Flexible delivery via image exports and available for custom licensing.

Spatial Analysis of Urban Noise Pollution: We conducted a spatial analysis of the distribution of noise pollution across HOLC grades for 83 cities in the United States (data in HOLC_Noise_City_results.csv). To be included in the study, the city needed to be included in both datasets used in the analysis: 1) the Mapping Inequality Project dataset on the distribution of HOLC grades across cities, and 2) the U.S. Department of Transportation, National Transportation Noise Map 2018. Any cities in which the distribution of HOLC grades did not include all four grades (A-D) were excluded from the analysis, which largely excluded cities with population sizes below 100,000 people. To evaluate noise exposure across HOLC grades for each city in our study, we acquired spatial data on the distribution of HOLC grades across U.S. cities from the Mapping Inequality Project. We also acquired data on road, rail, and aircraft noise (hereafter transportation noise models), from the U.S. Department of Transportation, National Transportation Noise Map (2018). The transportation noise models represent potential exposure to transportation noise reported on a decibel scale in a 30m x 30m pixel resolution. Here noise represents the average noise energy produced by road, rail, and aviation networks over a 24-hour period, measured in A-weighted decibels (dBA) (LAeq, 24h) at sampling locations deployed across a uniform grid in each city at an elevation of 1.5 m above ground level. Noise levels below 35 dBA are assumed to have minimal negative impacts to humans and the environment and thus are represented with null values in the transportation noise models. For each HOLC grade and each city, we used zonal statistics in ArcGIS Desktop v. 10.7 to summarize the median noise levels and area covered by excess noise (i.e., values > 35 dBA). We used the resulting zonal statistics estimates and the formula from Collins et al. (2019) to calculate an area-corrected measure of excess noise:

N = (r * Md)/a

where N is excess noise in each HOLC grade (with units of dBA/900m2); r is the area covered by the 30m x 30m pixels with noise values >35 dBA across all polygons of the same HOLC grade in each city; Md is the median transportation noise value (in dBA) for those same pixels; and a is the total area of all polygons of the same HOLC grade in each city. Thus, N represents a measure of both the level of noise and the area covered by excess noise in a given HOLC grade for each city.

Literature Review on the Impacts of Noise to Urban Wildlife: To assess the effects of noise on wildlife in urban environments, we conducted a literature review using Thompson’s ISI Web of Science and adapting the methods of Shannon et al. (2016). We adjusted of Shannon et al.’s search criteria to include urban phrases, resulting in the following search terms (TS=(WILDLIFE OR ANIMAL OR MAMMAL OR REPTILE OR AMPHIBIAN OR BIRD OR FISH OR INVERTEBRATE) AND TS=(NOISE OR SONAR) AND TS=(CITY OR *URBAN OR METROPOLITAN)). We only selected papers published between 1990 and 23 June 2021 (i.e., the date we conducted our search) within the ISI Web of Science categories of ‘Acoustics’, ‘Zoology’, ‘Ecology’, ‘Environmental Sciences’, ‘Ornithology’, ‘Biodiversity Conservation’, ‘Evolutionary Biology’, and ‘Marine Freshwater Biology’. This returned 691 peer-reviewed papers, which we filtered so only empirical studies focused on documenting the effects of anthropogenic noise on wildlife in urban or suburban ecosystems or the effects of urban noise on wildlife in rural environments were included in the final data set (n = 207). We excluded reviews, meta-analyses, methods papers, and research that took place outside of urban or suburban areas where the noise was not explicitly denoted as urban (e.g., omitted studies that measured traffic noise by parks and reserves in rural areas). For the 241 articles previously analyzed in of Shannon et al. (2016), one of our authors reviewed each paper to determine which studies were focused on urban noise (n = 46). We then verified whether there were significant biological responses to a particular noise level threshold, noting each noise level if multiple biological responses were recorded. We recorded responses to noise into one of eight possible biological response categories, many of which were taken or modified from the biological response categories utilized in Shannon et al. (2016). The following were the biological response categorical values: movement behavior, vocal behavior, physiological, population, mating behavior, foraging behavior, vigilance behavior, life history / reproduction, and ecosystem. For any new articles published since the Shannon et al. (2016) dataset (n = 354) or those published between 1990 and 2013 but not reviewed by Shannon et al. (n = 96), two of our authors reviewed each paper to first determine which studies met our criteria (n = 161) and then compiled data on a number of variables of interest, including the noise levels and their resulting biological responses that were statistically significant. For this subset of papers, one author was randomly assigned a list of papers and then a second author was randomly assigned to assess the accuracy of the data collected by the first author. Any discrepancies were discussed as a group until an agreement was reached. Noise categories (environmental, transportation, industrial, multiple, other) were chosen for each paper by noting the explicitly stated source or description of urban noise described in the methodology. Noise levels and their units were reported for each paper, with only noise levels reported in decibels (dB) being used in data analysis. All terrestrial papers used a reference pressure of 20 microPascals (μPa). Due to the low sample size of aquatic studies (n = 4), differences in reference pressures, and varying sound intensities amongst aquatic studies, we only included terrestrial studies in statistical analyses and figures. We recorded the sound metric used (i.e., SPL, SPL Max, Leq) for each paper, but were unable to convert the various sound metrics given to a single sound metric for standardization during analysis. Thus, there were various sound metrics used in the analysis of the data extracted from the literature search, in particular for the cumulative weight-of-evidence curve, which poses a limitation in the comparison of noise levels amongst papers. Additionally, we recorded the weightings for each noise level, with many of the papers being A-weighted (dBA; n = 100) and Z-weighted (dBZ; n = 4). These weightings relate to typical characteristics of sounds as observed by humans. Many papers, however, did not record the weighting and/or the exact sound metric used.

This is a polygon dataset of the strategic noise mapping of rail, which were identified as those rail exceeding the flow threshold of 30,000 vehicle passages per year, in the form of noise contours for the Lnight (night) period for Dublin and Cork agglomerations and the major rail outside of the agglomerations. The dB value represents the average decibel value during the Lnight time.Any direct comparison of the Round 3 versus Round 2 results should be carefully considered, as changes to the model input datasets used between these rounds may be significant. This may especially apply to the terrain model used, while there may be improved building height data, & improved traffic flow data with fewer assumed flows. There may also be some revisions to the actual road network modelled in Round 3.The noise maps are the product of assimilating a collection of digital datasets, and over the last 10 years there has been significant improvements to the quality of the digital datasets describing the natural and built environment in Ireland. This has led to the strategic noise models giving much more reliable noise results with much less tendency to over predict the impact.For more information on this dataset please go to https://gis.epa.ie/geonetwork/srv/eng/catalog.search#/metadata/72f5b183-40ea-4b68-aa55-0d7ea87a4322

This layer defines the areas surrounding Los Angeles County airports that are subject to a range of decibel levels in a 24-hour weighted average noise level known as Community Noise Equivalent Level (CNEL). Please click here to see the Los Angeles County Airport Land Use Commission portion of our website for maps and documents. You can also review the following document from the State of California for further information: California Airport Land Use Planning Handbook. Some of the airports, such as LAX, and Burbank, have periodic updates of their noise contours. All airport layers can be seen and interacted with together in our A-NET GIS web mapping application - click here. UPDATE: 3/27/2025 - Updated noise contours for LAX Airport (4th Quarter 2024)UPDATE: 4/2/2025 - Updated noise contours for Van Nuys Airport (4th Quarter 2024)UPDATE: 4/17/2025 - Updated noise contours for Burbank Airport (4th Quarter 2024)UPDATE: 4/17/2025 - Updated noise contours for Long Beach Airport (4th Quarter 2024)UPDATE: 10/27/2025 - Updated noise contours for LAX Airport (2nd Quarter 2025)UPDATE: 10/28/2025 - Updated noise contours for Van Nuys Airport (2nd Quarter 2025) NEED MORE FUNCTIONALITY? If you are looking for more layers or advanced tools and functionality, then try our suite of GIS Web Mapping Applications.

The 2018 National Transportation Noise Map dataset utilized transportation mode input data from 2018 in a model and is current as of October 2020, published by the Bureau of Transportation Statistics (BTS), and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). Please see the website https://www.bts.gov/geospatial/national-transportation-noise-map, for downloads and more information about these datasets. For web services of these data, please navigate to https://geo.dot.gov/server/rest/services/Hosted and search for service names beginning with "Noise." Please contact the NTAD Program Manager at ntad@dot.gov for any questions. Data within the National Transportation Noise Map represent potential noise levels across the nation for an average annual day for the specified year. These data are intended to facilitate the tracking of trends in transportation-related noise by mode collectively over time and should not be used to evaluate noise levels in individual locations and/or at specific times. This dataset is developed using a 24-hr equivalent A-weighted sound level (denoted by LAeq) noise metric. The results represent the approximate average noise energy due to transportation noise sources over a 24-hour period at the receptor locations where noise is computed. Layers include Aviation, Passenger Rail (prototype), and Road Noise for the Lower 48 States as well as Alaska and Hawaii. The full listing can be found below. 2018 National Transportation Noise

      Alaska

             Alaska Aviation Noise
             Alaska Road and Aviation Noise
             Alaska Road Noise

      Lower 48 States (CONUS)

             Lower 48 States (CONUS) Aviation Noise
             Lower 48 States (CONUS) Passenger Rail Noise (prototype)
             Lower 48 States (CONUS) Passenger Rail, Road, and Aviation Noise (prototype)
             Lower 48 States (CONUS) Road and Aviation Noise
             Lower 48 States (CONUS) Road Noise

      Hawaii

             Hawaii Aviation Noise
             Hawaii Road and Aviation Noise
             Hawaii Road Noise

Updated March 2023Noise contours in decibels for areas surrounding airports in the Sacramento, Sutter, Yolo, and Yuba counties' Airport Land Use Commission (ALUC), compiled from individual airport files to make a single regional layer.The SACOG Board of Directors serves as the Airport Land Use Commission (ALUC) for Sacramento, Sutter, Yolo and Yuba counties. California’s State Aeronautics Act (Public Utilities Code, Chapter 4, Article 3.5), identifies the role and responsibilities of the ALUCs in land use planning. The Act’s ALUC requirements are intended to ensure that proposed land uses near public-use airports are compatible with airport uses in terms of safety, noise and air space.One of the ALUC’s primary functions is to develop and adopt a plan that identifies zones for safety, noise contours, and height restrictions, along with associated compatible land uses, for each public-use airport. These plans are referred to as Airport Land Use Compatibility Plans (ALUCPs). For more information regarding ALUCPs, visit the ALUC page on the SACOG website.Updates as needed.Next review: January 2024

Strategic noise map for the city of Antwerp concerning industry according to RL 2002/49/EC. The reference year of these dates is 201 6 . The sound card indicates how much noise the environment is exposed to. The Lden level is a weighted annual average sound pressure level over the course of the day at which the evening and night levels are relatively heavier, which corresponds to the finding that noise pollution is generally perceived as more annoying in the evening and at night. European research therefore shows that a Lden is a relatively good predictor of the extent to which local residents may experience nuisance. These noise maps are updated every 5 years.

Airport Noise Contour Mapping Market Outlook

According to our latest research, the global Airport Noise Contour Mapping market size in 2024 stands at USD 1.42 billion, with a robust compound annual growth rate (CAGR) of 6.9% projected through 2033. By 2033, the market is forecasted to reach USD 2.77 billion. The primary growth factor driving this market is the increasing regulatory pressure on airports to monitor, manage, and mitigate noise pollution, alongside rising community awareness and technological advancements in mapping solutions.

A significant growth factor for the Airport Noise Contour Mapping market is the continuous expansion and modernization of airport infrastructure worldwide. As air traffic volumes surge, especially in emerging economies and global travel hubs, the need to assess and manage environmental impacts becomes more pronounced. Governments and aviation authorities are intensifying their focus on sustainable airport operations, which includes investing in advanced noise contour mapping solutions to ensure compliance with stringent noise regulations. The integration of Geographic Information Systems (GIS) and acoustic modeling technologies has enabled more precise and comprehensive mapping, supporting both operational efficiency and public relations strategies for airports. Additionally, the emergence of smart airports and the adoption of IoT and big data analytics are further enhancing the capabilities and accuracy of noise mapping systems.

Another crucial driver propelling the Airport Noise Contour Mapping market is the growing public and community advocacy regarding noise pollution around airport vicinities. As urban development encroaches upon airport perimeters, residential communities are increasingly affected by aircraft noise, leading to heightened demands for transparency and mitigation measures. This has resulted in the implementation of stricter noise abatement policies and the necessity for airports to provide detailed, real-time noise contour maps. These maps are not only essential for regulatory reporting but also play a pivotal role in community engagement, helping to build trust and foster collaborative solutions between airport operators and local residents. The deployment of sophisticated remote sensing and acoustic modeling technologies is enabling airports to proactively address noise complaints, optimize flight paths, and minimize the impact on sensitive zones.

Technological advancements represent a pivotal growth catalyst in the Airport Noise Contour Mapping market. The evolution of GIS-based mapping platforms, the integration of artificial intelligence (AI) for predictive noise modeling, and the utilization of remote sensing data have revolutionized the way airports monitor and manage noise pollution. These innovations have led to the development of highly detailed and dynamic noise contour maps, which can be updated in real time and tailored to various operational scenarios. Furthermore, the availability of cloud-based services and mobile applications has democratized access to noise data, empowering stakeholders including airport authorities, environmental consultants, and government agencies to collaborate more effectively. As digital transformation accelerates within the aviation sector, the adoption of advanced noise mapping solutions is expected to become a standard practice across commercial, military, and general aviation airports.

From a regional perspective, North America and Europe currently dominate the Airport Noise Contour Mapping market, driven by mature aviation industries, stringent regulatory frameworks, and early adoption of advanced mapping technologies. However, the Asia Pacific region is witnessing the fastest growth, fueled by rapid airport expansion, urbanization, and increasing environmental consciousness. Latin America and the Middle East & Africa are also emerging as significant markets, with governments investing in airport infrastructure and environmental compliance. The regional outlook suggests that while developed regions will continue to lead in terms of market share, emerging economies will contribute significantly to market growth over the forecast period, supported by favorable government policies and increasing investments in sustainable aviation solutions.

Understanding the extent to which systemic biases influence local ecological communities is essential for developing just and equitable environmental practices. With over 270 million people across the United States living in urban areas, understanding the socio-ecological consequences of racially-targeted zoning, such as redlining, provides crucial information for urban planning. There is a growing body of literature documenting the relationships between redlining and disparities in the distribution of environmental harms and goods, including inequities in green space cover and pollutant exposure. Yet, it remains unknown whether noise pollution is also inequitably distributed, and whether inequitable noise is an important driver of ecological change in urban environments. We conducted 1) a spatial analysis of urban noise to determine the extent to which noise overlaps with the distribution of redlining categories and 2) a systematic literature review to summarize the effects of noise on..., Spatial Analysis of Urban Noise Pollution To evaluate noise exposure across HOLC redlining grades for 83 U.S. cities in our study, we acquired spatial data on the distribution of HOLC grades across U.S. cities from the Mapping Inequality Project. We also acquired data on road, rail, and aircraft noise (hereafter transportation noise models), from the U.S. Department of Transportation, National Transportation Noise Map 2018. The transportation noise models represent potential exposure to transportation noise reported on a decibel scale in a 30m x 30m pixel resolution. Here noise represents the average noise energy produced by road, rail, and aviation networks over a 24-hour period, measured in A-weighted decibels (dBA) (LAeq, 24h) at sampling locations deployed across a uniform grid in each city at an elevation of 1.5 m above ground level. Noise levels below 35 dBA are assumed to have minimal negative impacts to humans and the environment and thus are represented with null values in the ..., Data can be viewed using any software that can open a .csv file. Code can be viewed using any software that can open a .txt file., # Inequalities in noise will affect urban wildlife

https://doi.org/10.5061/dryad.s4mw6m998

Part I: Spatial Analysis of Noise Distribution across 83 U.S. cities File name: HOLC_Noise_City_Results.csv Date completed: 15 December 2021 Spatial dataset: U.S. Department of Transportation, National Transportation Noise Map 2018 Software used in analysis: ArcGIS Desktop v. 10.7

Part II: Literature review of papers published between 1990 and 23 June 2021 that focus on the impacts of noise pollution to urban wildlife. File name: Urban_noise_wildlife_literature_review.csv Date compiled: 23 June 2021 Search engine: Thompson’s ISI Web of Science Search terms (TS=(WILDLIFE OR ANIMAL OR MAMMAL OR REPTILE OR AMPHIBIAN OR BIRD OR FISH OR INVERTEBRATE) AND TS=(NOISE OR SONAR) AND TS=(CITY OR *URBAN OR METROPOLITAN)).

Data collection procedure: To assess the effects of noise on wildlife in urban environments, we conducted a literature review using Tho...

This dataset contains multibeam bathymetry, backscatter, and LiDAR bathymetry and reflectance. These GeoTIFFs represent water depth and acoustic intensity of the seafloor from Phase II of the Long Island Sound (LIS) Benthic Habitat Priority Areas of Interest (AOI) project. The original Phase II datasets were surveyed by NOAA Ship Nancy Foster (R-352), NOAA Ship Thomas Jefferson, and the Navigation Response Team (NRT-5) using 400 khz Reson 7125 multibeam sonars from 2003 to 2014. In 2018, the LIS Cable Fund contracted the State University of New York (SUNY) at Stony Brook School of Marine and Atmospheric Sciences (SoMAS) to fill gaps and resurvey areas where multibeam data was not acceptable with R/V Pritchard using 400 khz Kongsberg dual-swath EM2040c multibeam sonars in coordination with the NOAA National Centers for Coastal Ocean Science (NCCOS) Biogeography Branch and the NOAA Integrated Ocean and Coastal Mapping (IOCM) Program. The multibeam and LiDAR were corrected, calibrated, and integrated into a seamless 32-bit raster using CARIS and ArcGIS. Backscatter data was collected and mosaicked into a raster using Fledermaus Geocoder Toolbox, ArcGIS 10.4, and PCI Geomatica 2018 software.