About this dataset

Context

The dataset tabulates the Jersey Shore population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Jersey Shore. The dataset can be utilized to understand the population distribution of Jersey Shore by age. For example, using this dataset, we can identify the largest age group in Jersey Shore.

Key observations

The largest age group in Jersey Shore, PA was for the group of age 10 to 14 years years with a population of 572 (13.84%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Jersey Shore, PA was the 25 to 29 years years with a population of 51 (1.23%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Jersey Shore is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Jersey Shore total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Jersey Shore Population by Age. You can refer the same here

Historical shoreline surveys were conducted by the National Ocean Service (NOS), dating back to the early 1800s. The maps resulting from these surveys, often called t-sheets, provide a reference of historical shoreline position that can be compared to modern data to identify shoreline change. The t-sheets are stored at the National Archives and many have been scanned by the National Oceanic and Atmospheric Administration (NOAA) and are available on the NOAA Shoreline Web site (http://www.shoreline.noaa.gov/data/datasheets/t-sheets.html). While some scanned t-sheets were georeferenced and digitized by NOAA, still others remain as non-georeferenced raster files (http://nosimagery.noaa.gov/images/shoreline_surveys/survey_scans/NOAA_Shoreline_Survey_Scans.html). New_Jersey_1839_75_Digitized_Shoreline.zip features a digitized historic shoreline for the New Jersey coastline from 1839 to 1875. The data were scanned by NOAA, but were not georeferenced. The t-sheets included in this data release are: T-121 (1839), T-119 Part 1 (1841), T-1084 (1868), T-1166 (1870), T-1333 (1871), T-1315a (1872), T-1371 (1874), T-1407 (1875). Digital files were georeferenced, corrected to a modern datum, and shorelines digitized to provide a vector polyline depicting the historical shoreline position. All shorelines, including the foreshore, backshore, mainland and island shorelines were delineated and digitized for each survey using ArcMap 10.3.1. These shorelines were digitized for use in long-term shoreline and wetland analyses for Hurricane Sandy wetland physical change assessment.

This dataset defines the volume of sand along a 10-meter (m) wide profile between the seaward-most dune toe and the mean high water shoreline derived from light detection and ranging (lidar) digital elevation models (DEMs). Refer to Doran and others (2017) for more information about the source lidar data. These data support the National Fish and Wildlife Foundation (NFWF)-funded project entitled “Monitoring Hurricane Sandy Beach and Marsh Resilience in New York and New Jersey” (NFWF project ID 2300.16.055110), for which the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) is using remotely-sensed data and targeted in-situ observations to monitor the post-restoration evolution of beaches, dunes, vegetative cover, and sediment budgets at seven post-Hurricane Sandy restoration sites in New York and New Jersey.

About this dataset

Context

The dataset tabulates the Jersey Shore population by race and ethnicity. The dataset can be utilized to understand the racial distribution of Jersey Shore.

Content

The dataset will have the following datasets when applicable

Please note that in case when either of Hispanic or Non-Hispanic population doesnt exist, the respective dataset will not be available (as there will not be a population subset applicable for the same)

• Jersey Shore, PA Population Breakdown by Race
• Jersey Shore, PA Non-Hispanic Population Breakdown by Race
• Jersey Shore, PA Hispanic or Latino Population Distribution by Their Ancestries

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/.

These data were automated to provide an accurate high-resolution historical shoreline of New Jersey suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808

Sedimentologic and topographic data from Hurricane Sandy washover deposits were collected from Southern Long Beach Island, New Jersey, in order to document changes to the barrier-island beaches, dunes, and coastal wetlands due to Hurricane Sandy and subsequent storm events. These data will provide a baseline dataset for use in future coastal change descriptive and predictive studies and assessments. The data presented here were collected as part of the U.S. Geological Survey’s Barrier Island and Estuarine Wetland Physical Change Assessment project (http://coastal.er.usgs.gov/sandy-wetland-assessment/), which aims to assess ecological and societal vulnerability that results from long- and short-term physical changes to barrier islands and coastal wetlands. This metadata record describes data that were collected in April 2015, approximately two and a half years after Hurricane Sandy’s landfall on 29 October 2012. During the field campaign, washover deposits were photographed, and described. In addition, sediment samples, cores, and surface elevations were collected. Data collected during this study including sample locations and elevations, core photographs, computed tomography (CT) scans, descriptive core logs, sediment grain-size data, and accompanying Federal Geographic Data Committee (FGDC) metadata are provided in the associated USGS Data Release, available at https://doi.org/10.5066/F7PK0D7S.

This dataset provides information about the number of properties, residents, and average property values for Main Road cross streets in Jersey Shore, PA.

This dataset provides information about the number of properties, residents, and average property values for Middle Road cross streets in Jersey Shore, PA.

This dataset provides information about the number of properties, residents, and average property values for Valley View Drive cross streets in Jersey Shore, PA.

About this dataset

Context

The dataset tabulates the population of Jersey Shore by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Jersey Shore. The dataset can be utilized to understand the population distribution of Jersey Shore by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Jersey Shore. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Jersey Shore.

Key observations

Largest age group (population): Male # 5-9 years (300) | Female # 10-14 years (291). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Jersey Shore population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Jersey Shore is shown in the following column.
• Population (Female): The female population in the Jersey Shore is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Jersey Shore for each age group.

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 Jersey Shore Population by Gender. You can refer the same here

New_Jersey_1971_78_Digitized_Shoreline.zip features a digitized historic shoreline for the New Jersey coastline (Point Pleasant, NJ to Longport, NJ) from 1971 to 1978. Imagery of the New Jersey coastline was acquired from the New Jersey Geographic Information Network (NJGIN) as two images: “1970 NJDEP Wetlands Basemap” (1971-78) and the “1977 Tidelands Basemaps” (1977-78). These images are available as a web mapping service (WMS) through the NJGIN website (https://njgin.state.nj.us/NJ_NJGINExplorer/jviewer.jsp?pg=wms_instruct). To reduce digitizing error, the imagery was acquired on a hard drive from the NJGIN via personal communication. Using ArcMap 10.3.1, the "1970 NJDEP Wetlands Basemap" was used to delineate and digitize historical foreshore, backshore, mainland, and island shoreline positions, with the “1977 Tidelands Basemaps” being used to fill in missing shorelines and clarify areas of uncertainty from the 1970s imagery. These shorelines were digitized for use in long-term shoreline and wetland analyses for Hurricane Sandy wetland physical change assessment.

The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Pre Hurricane Sandy New York and New Jersey United States Geological Survey (USGS) Experimental Advanced Airborne Research lidar B (EAARL-B) survey. Beach width is included and is defined as the distance between the dune toe and shoreline along a cross-shore profile. The beach slope is calculated using this beach width and the elevation of the shoreline and dune toe.

This dataset defines shoreline change rates for each 10-meter (m)-wide profile calculated via endpoint rate and linear regression from Himmelstoss and others (2018). Shoreline change rates were calculated for two time periods: pre-Sandy (2010-2012) and post-Sandy (2012-2022). The profiles were derived from light detection and ranging (lidar) digital elevation models (DEMs). Refer to Doran and others (2017) for more information about the source lidar data. These data support the National Fish and Wildlife Foundation (NFWF)-funded project entitled “Monitoring Hurricane Sandy Beach and Marsh Resilience in New York and New Jersey” (NFWF project ID 2300.16.055110), for which the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) is using remotely-sensed data and targeted in-situ observations to monitor the post-restoration evolution of beaches, dunes, vegetative cover, and sediment budgets at seven post-Hurricane Sandy restoration sites in New York ...

This data is a graphical representation of the historic shorelines for the four Atlantic Ocean counties (Atlantic, Cape May, Ocean, and Monmouth). It details the 11 different Atlantic Ocean shorelines in New Jersey from the years of 1836-1977. The shorelines are from 1836-42, 1855, 1866-68, 1871-75, 1879-85, 1899, 1932-36, 1943, 1951-53, 1971, and 1977. Not all years are complete or run the entire length of the four Atlantic counties. The coast coverage can be used as a 1986 shoreline.

This dataset provides information about the number of properties, residents, and average property values for Dennison Road cross streets in Jersey Shore, PA.

These data were automated to provide an accurate high-resolution historical shoreline of Atlantic City-New Jersey Coast, NJ suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://inport.nmfs.noaa.gov/inport/item/39808

This dataset provides information about the number of properties, residents, and average property values for Fox Road cross streets in Jersey Shore, PA.

This dataset provides information about the number of properties, residents, and average property values for Canoe Run Road cross streets in Jersey Shore, PA.

As part of the National Fish and Wildlife Foundation (NFWF)-funded Monitoring Hurricane Sandy Beach and Marsh Resilience in New York and New Jersey project (NFWF project ID 2300.16.055110), the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) is using remotely-sensed data and targeted in-situ observations to monitor the post-restoration evolution of beaches, dunes, vegetative cover, and sediment budgets at seven post-Hurricane Sandy beach and marsh restoration sites in New York and New Jersey. These data and derived ecological resilience metrics will be used to assess the cost-effectiveness and ecological benefits of the restoration techniques and evaluate how the restored parts of the coast have changed through time. The USGS National Assessment of Coastal Change Hazards project publishes lidar-derived beach morphologic features including dune crest, dune toe, and shoreline position as well as beach width and beach slope along cross-shore transects to help define coastal vulnerability to storm impacts and long-term shoreline change (Doran and others, 2020; https://coastal.er.usgs.gov/data-release/doi-F7GF0S0Z/). This dataset represents a subset of the lidar-derived beach morphology data that includes the coastline from Seven Mile Island to Maurice River along the Cape May Peninsula, New Jersey. This subset area encompasses NFWF restoration projects NFWF-41991 (Increasing Seven Mile Island's Beach Resiliency), NFWF-43429 (Creating a Resilient Delaware Bay Shoreline in Cape May and Cumberland Counties), and USFWS-6 (Increase Resilience of Beach Habitat at Pierce's Point, Reed's Beach, and Moore's Beach, New Jersey). In addition to subsetting the dataset to the specified alongshore extent, the published data (Doran and others, 2020; https://coastal.er.usgs.gov/data-release/doi-F7GF0S0Z/) were transformed from the North American Vertical Datum of 1988 (NAVD88), GEOID96 to NAVD88, GEOID12B for consistency with other data collected as part of NFWF project 2300.16.055110. Data are provided as digital tabular data in comma-separated values (.csv) format. For more information, please refer to the full metadata included with each data resource.

These data were automated to provide an accurate high-resolution historical shoreline of Sandy Hook Bay to Raritan Bay, NJ suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://inport.nmfs.noaa.gov/inport/item/39808