12 datasets found
  1. U

    Offshore baseline for Boston coastal region generated to calculate shoreline...

    • data.usgs.gov
    • search.dataone.org
    • +5more
    + more versions
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    U.S. Geological Survey, Offshore baseline for Boston coastal region generated to calculate shoreline change rates from Carson Beach in South Boston to Weymouth River on the Massachusetts mainland, and including the Boston Harbor Islands 9Boston_baseline.shp) [Dataset]. http://doi.org/10.3133/ofr20121183
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    Dataset provided by
    United States Geological Survey
    Authors
    U.S. Geological Survey
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    2013
    Area covered
    South Boston, Boston, Harbor Islands- Long Island, Carson Beach, Massachusetts
    Description

    Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. The Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) in cooperation with the Massachusetts Office of Coastal Zone Management, has compiled reliable historical shoreline data along open-facing sections of the Massachusetts coast under the Massachusetts Shoreline Change Mapping and Analysis Project 2013 Update. Two oceanfront shorelines for Massachusetts (approximately 1,800 km in total length) were (1) delineated using 2008/09 color aerial orthoimagery, and (2) ...

  2. U.S. Greater Boston metro area GDP 2001-2022

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). U.S. Greater Boston metro area GDP 2001-2022 [Dataset]. https://www.statista.com/statistics/183851/gdp-of-the-greater-boston-metro-area/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The gross domestic product (GDP) of the Greater Boston metro area has increased significantly since 2001. In 2022, the area's GDP amounted to 504.1 billion chained 2017 U.S. dollars, compared to 284.1 billion U.S. dollars in 2001.

  3. Boston-Cambridge-Newton metro area population in the U.S. 2010-2023

    • statista.com
    Updated Oct 16, 2024
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    Statista (2024). Boston-Cambridge-Newton metro area population in the U.S. 2010-2023 [Dataset]. https://www.statista.com/statistics/815215/boston-metro-area-population/
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    Dataset updated
    Oct 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, the population of the Boston-Cambridge-Newton metropolitan area in the United States was about 4.92 million people. This is a slight increase when compared with last year's population, which was about 4.9 million people.

  4. N

    Median Household Income Variation by Family Size in Boston, New York:...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
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    Neilsberg Research (2024). Median Household Income Variation by Family Size in Boston, New York: Comparative analysis across 7 household sizes [Dataset]. https://www.neilsberg.com/research/datasets/1ab3adc9-73fd-11ee-949f-3860777c1fe6/
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    csv, jsonAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Boston, New York, Boston
    Variables measured
    Household size, Median Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It delineates income distributions across 7 household sizes (mentioned above) following an initial analysis and categorization. Using this dataset, you can find out how household income varies with the size of the family unit. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median household incomes for various household sizes in Boston, New York, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

    Key observations

    • Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Boston town did not include 7-person households. Across the different household sizes in Boston town the mean income is $106,012, and the standard deviation is $34,132. The coefficient of variation (CV) is 32.20%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
    • In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $47,277. It then further increased to $130,010 for 6-person households, the largest household size for which the bureau reported a median household income.

    https://i.neilsberg.com/ch/boston-ny-median-household-income-by-household-size.jpeg" alt="Boston, New York median household income, by household size (in 2022 inflation-adjusted dollars)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Household Sizes:

    • 1-person households
    • 2-person households
    • 3-person households
    • 4-person households
    • 5-person households
    • 6-person households
    • 7-or-more-person households

    Variables / Data Columns

    • Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Boston town median household income. You can refer the same here

  5. A

    Canopy Change Assessment: Parcels FY19 Land Use

    • data.boston.gov
    • gis.data.mass.gov
    • +3more
    Updated May 17, 2021
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    Boston Maps (2021). Canopy Change Assessment: Parcels FY19 Land Use [Dataset]. https://data.boston.gov/dataset/canopy-change-assessment-parcels-fy19-land-use
    Explore at:
    html, geojson, csv, kml, arcgis geoservices rest api, zip, shpAvailable download formats
    Dataset updated
    May 17, 2021
    Dataset provided by
    BostonMaps
    Authors
    Boston Maps
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    Learn more about the project and how to use the canopy assessment data by visiting the StoryMap!

    Data Dictionary


    Project generalized the LU codes in their FY 2019 parcels dataset to create a new attribute LU_general as shown below. Open space was added as a land use category by overlaying Boston’s Open_space dataset onto the parcels (open space taking precedence over underlying parcel land use designation). Dissolve on generalized LU codes. Overlay with city boundary (BostonCity_AOI) to identify ROW (anything not covered by parcels or open space polygons).

    FY19 parcels label--> LU_general

    - Unknown

    A Residential

    AH Commercial

    C Commercial

    CL Commercial

    CM <span style='font-size:11pt; font-family:Lora,serif; color:#4c4c4c;

  6. Monthly apartment rent and rental growth in Boston, MA, 2018-2023

    • statista.com
    Updated Jan 28, 2025
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    Monthly apartment rent and rental growth in Boston, MA, 2018-2023 [Dataset]. https://www.statista.com/statistics/1365735/apartment-rent-and-rental-growth-boston/
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    Dataset updated
    Jan 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2018 - Dec 2023
    Area covered
    Massachusetts
    Description

    The median rent for one- and two-bedroom apartments in Boston, Massachusetts, amounted to about 2,302 U.S. dollars by the end of 2023. Rents decreased slightly after the beginning of the coronavirus pandemic,this trend reversed in 2021 and as of December 2023, the annual rental growth stood at 3.32 percent. Among the different states in the U.S., Massachusetts ranks as one of the most expensive rental markets.

  7. M

    Boston Metro Area Population 1950-2025

    • macrotrends.net
    csv
    Updated Feb 28, 2025
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    MACROTRENDS (2025). Boston Metro Area Population 1950-2025 [Dataset]. https://www.macrotrends.net/global-metrics/cities/22939/boston/population
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    csvAvailable download formats
    Dataset updated
    Feb 28, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1950 - Mar 26, 2025
    Area covered
    Boston Metropolitan Area, United States
    Description

    Chart and table of population level and growth rate for the Boston metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

  8. m

    Canopy Change Assessment: 2014-2019 Tree Canopy Change Image

    • gis.data.mass.gov
    • data.boston.gov
    • +1more
    Updated May 17, 2021
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    BostonMaps (2021). Canopy Change Assessment: 2014-2019 Tree Canopy Change Image [Dataset]. https://gis.data.mass.gov/datasets/boston::canopy-change-assessment-2014-2019-tree-canopy-change-image
    Explore at:
    Dataset updated
    May 17, 2021
    Dataset authored and provided by
    BostonMaps
    Area covered
    Description

    This layer is a high-resolution tree canopy change-detection layer for City of Boston, MA. It contains three tree-canopy classes for the period 5 years: (1) No Change; (2) Gain; and (3) Loss. It was created by extracting tree canopy from existing high-resolution land-cover maps for 2014 and 2019 and then comparing the mapped trees directly. Tree canopy that existed during both time periods was assigned to the No Change category while trees removed by development, storms, or disease were assigned to the Loss class. Trees planted during the interval were assigned to the Gain category, as were the edges of existing trees that expanded noticeably. Direct comparison was possible because both the 2014 and 2019 maps were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset will be subjected to manual review and correction.

  9. Imagery Layer Evening Air Temperature in Boston MA

    • noaa.hub.arcgis.com
    Updated May 5, 2022
    + more versions
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    NOAA GeoPlatform (2022). Imagery Layer Evening Air Temperature in Boston MA [Dataset]. https://noaa.hub.arcgis.com/datasets/f326a5c5235a49a79d83375bf3864077
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    Dataset updated
    May 5, 2022
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA GeoPlatform
    Area covered
    Description

    Urban heat islands are small areas where temperatures are unnaturally high - usually due to dense buildings, expansive hard surfaces, or a lack of tree cover or greenspace. People living in these communities are exposed to more dangerous conditions, especially as daytime high and nighttime low temperatures increase over time. NOAA Climate Program Office and CAPA Strategies have partnered with cities around the United States to map urban heat islands. Using Sentinel-2 satellite thermal data along with on-the-ground sensors, air temperature and heat indexes are calculated for morning, afternoon, and evening time periods. The NOAA Visualization Lab, part of the NOAA Satellite and Information Service, has made the original heat mapping data available as dynamic image services.Dataset SummaryPhenomenon Mapped: Sensing package time step valuesUnits: decimal degrees Cell Size: 30 metersPixel Type: 32 bit floating pointData Coordinate Systems: WGS84 Mosaic Projection: WGS84 Extent: cities within the United StatesSource: NOAA and CAPA StrategiesPublication Date: September 20, 2021What can you do with this layer?This imagery layer supports communities' UHI spatial analysis and mapping capabilities. The symbology can be manually changed, or a processing template applied to the layer will provide a custom rendering. Each city can be queried.Cities IncludedBaltimore, Boise, Boston, Fort Lauderdale, Honolulu, Los Angeles, Nampa, Oakland-Berkeley, Portland, Richmond, Sacramento, San Bernardino, San Juan, Victorville, Washington, West Palm Beach, Worcester, Charleston and YonkersCities may apply to be a part of the Heat Watch program through the CAPA Strategies website. Attribute Table Informationcity_name: Boston MAEvening air temperatures in cities

  10. Boston Red Sox revenue 2001-2023

    • statista.com
    Updated Sep 5, 2024
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    Statista (2024). Boston Red Sox revenue 2001-2023 [Dataset]. https://www.statista.com/statistics/196639/revenue-of-the-boston-red-sox-since-2006/
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    Dataset updated
    Sep 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, the revenue of the Boston Red Sox amounted to 500 million U.S. dollars. This shows a decrease of 13 million U.S. dollars over the previous year. The Boston Red Sox are owned by John Henry and Thomas Werner, who bought the franchise for 380 million U.S. dollars in 2002.

  11. A

    Canopy Change Assessment: 2019 Land Cover

    • data.boston.gov
    • hub.arcgis.com
    • +1more
    Updated May 20, 2024
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    Boston Maps (2024). Canopy Change Assessment: 2019 Land Cover [Dataset]. https://data.boston.gov/dataset/canopy-change-assessment-2019-land-cover
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    arcgis geoservices rest api, html, csv, geojson, kml, zipAvailable download formats
    Dataset updated
    May 20, 2024
    Dataset provided by
    University of Vermont Spatial Analysis Laboratory
    Authors
    Boston Maps
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    High resolution land cover dataset for Boston, MA. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The primary sources used to derive this land cover layer were 2019 LiDAR data and 2018 NAIP imagery. Ancillary data sources included GIS data provided by City of Boston or created by the UVM Spatial Analysis Laboratory. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:2000 and all observable errors were corrected.

  12. A

    Climate Ready Boston Social Vulnerability

    • data.boston.gov
    • gis.data.mass.gov
    • +1more
    Updated Sep 21, 2017
    + more versions
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    Boston Maps (2017). Climate Ready Boston Social Vulnerability [Dataset]. https://data.boston.gov/dataset/climate-ready-boston-social-vulnerability
    Explore at:
    arcgis geoservices rest api, html, csv, kml, geojson, zipAvailable download formats
    Dataset updated
    Sep 21, 2017
    Dataset provided by
    BostonMaps
    Authors
    Boston Maps
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    Boston
    Description
    Social vulnerability is defined as the disproportionate susceptibility of some social groups to the impacts of hazards, including death, injury, loss, or disruption of livelihood. In this dataset from Climate Ready Boston, groups identified as being more vulnerable are older adults, children, people of color, people with limited English proficiency, people with low or no incomes, people with disabilities, and people with medical illnesses.

    Source:

    The analysis and definitions used in Climate Ready Boston (2016) are based on "A framework to understand the relationship between social factors that reduce resilience in cities: Application to the City of Boston." Published 2015 in the International Journal of Disaster Risk Reduction by Atyia Martin, Northeastern University.

    Population Definitions:

    Older Adults:
    Older adults (those over age 65) have physical vulnerabilities in a climate event; they suffer from higher rates of medical illness than the rest of the population and can have some functional limitations in an evacuation scenario, as well as when preparing for and recovering from a disaster. Furthermore, older adults are physically more vulnerable to the impacts of extreme heat. Beyond the physical risk, older adults are more likely to be socially isolated. Without an appropriate support network, an initially small risk could be exacerbated if an older adult is not able to get help.
    Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for population over 65 years of age.
    Attribute label: OlderAdult

    Children:
    Families with children require additional resources in a climate event. When school is cancelled, parents need alternative childcare options, which can mean missing work. Children are especially vulnerable to extreme heat and stress following a natural disaster.
    Data source: 2010 American Community Survey 5-year Estimates (ACS) data by census tract for population under 5 years of age.
    Attribute label: TotChild

    People of Color:
    People of color make up a majority (53 percent) of Boston’s population. People of color are more likely to fall into multiple vulnerable groups as
    well. People of color statistically have lower levels of income and higher levels of poverty than the population at large. People of color, many of whom also have limited English proficiency, may not have ready access in their primary language to information about the dangers of extreme heat or about cooling center resources. This risk to extreme heat can be compounded by the fact that people of color often live in more densely populated urban areas that are at higher risk for heat exposure due to the urban heat island effect.
    Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract: Black, Native American, Asian, Island, Other, Multi, Non-white Hispanics.
    Attribute label: POC2

    Limited English Proficiency:
    Without adequate English skills, residents can miss crucial information on how to prepare
    for hazards. Cultural practices for information sharing, for example, may focus on word-of-mouth communication. In a flood event, residents can also face challenges communicating with emergency response personnel. If residents are more socially
    isolated, they may be less likely to hear about upcoming events. Finally, immigrants, especially ones who are undocumented, may be reluctant to use government services out of fear of deportation or general distrust of the government or emergency personnel.
    Data Source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract, defined as speaks English only or speaks English “very well”.
    Attribute label: LEP

    Low to no Income:
    A lack of financial resources impacts a household’s ability to prepare for a disaster event and to support friends and neighborhoods. For example, residents without televisions, computers, or data-driven mobile phones may face challenges getting news about hazards or recovery resources. Renters may have trouble finding and paying deposits for replacement housing if their residence is impacted by flooding. Homeowners may be less able to afford insurance that will cover flood damage. Having low or no income can create difficulty evacuating in a disaster event because of a higher reliance on public transportation. If unable to evacuate, residents may be more at risk without supplies to stay in their homes for an extended period of time. Low- and no-income residents can also be more vulnerable to hot weather if running air conditioning or fans puts utility costs out of reach.
    Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for low-to- no income populations. The data represents a calculated field that combines people who were 100% below the poverty level and those who were 100–149% of the poverty level.
    Attribute label: Low_to_No

    People with Disabilities:
    People with disabilities are among the most vulnerable in an emergency; they sustain disproportionate rates of illness, injury, and death in disaster events.46 People with disabilities can find it difficult to adequately prepare for a disaster event, including moving to a safer place. They are more likely to be left behind or abandoned during evacuations. Rescue and relief resources—like emergency transportation or shelters, for example— may not be universally accessible. Research has revealed a historic pattern of discrimination against people with disabilities in times of resource scarcity, like after a major storm and flood.
    Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for total civilian non-institutionalized population, including: hearing difficulty, vision difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty.
    Attribute label: TotDis

    Medical Illness:
    Symptoms of existing medical illnesses are often exacerbated by hot temperatures. For example, heat can trigger asthma attacks or increase already high blood pressure due to the stress of high temperatures put on the body. Climate events can interrupt access to normal sources of healthcare and even life-sustaining medication. Special planning is required for people experiencing medical illness. For example, people dependent on dialysis will have different evacuation and care needs than other Boston residents in a climate event.
    Data source: Medical illness is a proxy measure which is based on EASI data accessed through Simply Map. Health data at the local level in Massachusetts is not available beyond zip codes. EASI modeled the health statistics for the U.S. population based upon age, sex, and race probabilities using U.S. Census Bureau data. The probabilities are modeled against the census and current year and five year forecasts. Medical illness is the sum of asthma in children, asthma in adults, heart disease, emphysema, bronchitis, cancer, diabetes, kidney disease, and liver disease. A limitation is that these numbers may be over-counted as the result of people potentially having more than one medical illness. Therefore, the analysis may have greater numbers of people with medical illness within census tracts than actually present. Overall, the analysis was based on the relationship between social factors.
    Attribute label: MedIllnes

    Other attribute definitions:
    GEOID10: Geographic identifier: State Code (25), Country Code (025), 2010 Census Tract
    AREA_SQFT: Tract area (in square feet)
    AREA_ACRES: Tract area (in acres)
    POP100_RE: Tract population count
    HU100_RE: Tract housing unit count
    Name: Boston Neighborhood
  13. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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U.S. Geological Survey, Offshore baseline for Boston coastal region generated to calculate shoreline change rates from Carson Beach in South Boston to Weymouth River on the Massachusetts mainland, and including the Boston Harbor Islands 9Boston_baseline.shp) [Dataset]. http://doi.org/10.3133/ofr20121183

Offshore baseline for Boston coastal region generated to calculate shoreline change rates from Carson Beach in South Boston to Weymouth River on the Massachusetts mainland, and including the Boston Harbor Islands 9Boston_baseline.shp)

Explore at:
Dataset provided by
United States Geological Survey
Authors
U.S. Geological Survey
License

U.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically

Time period covered
2013
Area covered
South Boston, Boston, Harbor Islands- Long Island, Carson Beach, Massachusetts
Description

Due to continued coastal population growth and increased threats of erosion, current data on trends and rates of shoreline movement are required to inform shoreline and floodplain management. The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. The Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) in cooperation with the Massachusetts Office of Coastal Zone Management, has compiled reliable historical shoreline data along open-facing sections of the Massachusetts coast under the Massachusetts Shoreline Change Mapping and Analysis Project 2013 Update. Two oceanfront shorelines for Massachusetts (approximately 1,800 km in total length) were (1) delineated using 2008/09 color aerial orthoimagery, and (2) ...

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