About this dataset

Context

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

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)

• New Jersey Population Breakdown by Race
• New Jersey Non-Hispanic Population Breakdown by Race
• New Jersey 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/.

The data contained within include high-water marks collected at 50 sites throughout the regions of New Jersey affected by significant flooding from Hurricane Ida during September of 2021. Each site contains between one to six associated high-water marks that were documented, photographed, and surveyed to datum. The datum represented by the elevations of the high-water marks is the North American Vertical Datum of 1988. All data (excluding photographs) associated with the high-water marks are contained within the data release associated with these metadata, as well as the USGS Short Term Network Flood Event Viewer (STN-FEV, U.S. Geological Survey (2021a)). Photographs can be found within the STN-FEV. A summary of the event leading to the collection of these data is provided below. Hurricane Ida was a large and destructive storm that originally made landfall on the Louisiana coast on August 29, 2021, causing extensive damage. Following landfall in Louisiana, the system weakened to a tropical depression as it moved northeast across the United States. As it approached the mid-Atlantic region, it interacted with a frontal system eventually becoming a strongly forced frontal low. As the low passed over parts of southeastern Pennsylvania, central and northern New Jersey, and southern New York, it produced rainfall totals nearing 10 inches in some localized areas during a 24-hour period, in addition to significant severe weather including tornadoes (National Weather Service, 2021). Two weeks prior, the region received significant precipitation from Hurricane Henri, and most larger river basins were still receding from that event. In New Jersey, the hardest-hit areas spanned from Hunterdon and Mercer counties northeastward through Somerset, Middlesex, Union, Essex, and Hudson Counties. Heavy rainfall rates associated with the remnants of Hurricane Ida caused flash flooding in several urban communities resulting in local stormwater drainage systems being overwhelmed. Small stream and larger river flooding also occurred along the storm path. In many cases, hydraulic structures such as bridges and culverts were quickly overwhelmed by the volume of stormwater which resulted in roads being overtopped by high-energy floodwaters and damaged or washed out. In Hunterdon County, the Wickecheoke, Swan, and Harihokake Creeks all experienced these effects. In Mercer and Somerset Counties, smaller stream basins such as Stony Brook, Beden Brook, Rock Brook, and Peters Brook were notable examples of streams that overtopped their banks during this event. Moving to the northeast in Union and Essex Counties, the Rahway, Elizabeth, and Second Rivers overwhelmed flood control projects and concrete-lined channels in urban areas resulting in some of the worst examples of flooding from Ida in New Jersey. Major flooding on other large rivers was somewhat restricted in New Jersey because precipitation produced by this event did not encompass the entire state. For example, northern basins such as the Ramapo did not receive as much precipitation as some central parts of the state. This in turn prevented catastrophic flooding on the lower Passaic River basin which has been notable during past widespread flooding events such as Hurricane Irene. The Raritan and Millstone River basins took the brunt of the effects of the storm, as most of the previously mentioned streams drain into these rivers. The provisional peak gage height at the U.S. Geological Survey (USGS) 01400500 Raritan River at Manville, NJ, streamgage exceeded the gage height recorded during the Hurricane Floyd flooding event that occurred in 1999, which was the period-of-record gage height peak. Main stem river flooding on the Raritan and Millstone Rivers caused significant flooding from backwater along many tributaries throughout the basin that in some cases took days to recede. Following the event, the USGS New Jersey Water Science Center deployed field crews to perform discharge measurements, assess damage to streamgages, and confirm provisional period-of-record peaks. The Federal Emergency Management Agency (FEMA) issued a Major Disaster Declaration for 13 New Jersey counties and requested assistance from the USGS in identifying, documenting, and surveying the depths and extents of flooding in several of the most affected communities within the disaster declared counties. The USGS deployed field crews to the communities of Milford, Stockton, Frenchtown, Lambertville, Clinton, Flemington, Rocky Hill, Somerville, Manville, Bound Brook, Plainfield, Ridgewood, Elizabeth, Cranford, and Rahway to flag and survey high-water marks. During the period from September 8-30, 2021, 139 high-water marks were documented and surveyed at 50 sites throughout the aforementioned communities. More information on the processes and techniques used to identity and survey high-water marks can be found at the USGS Water Science School page on High-Water Marks and Flooding (U.S. Geological Survey (2021b). References Cited: National Weather Service, 2021, "Event Review: September 1:Remnants of Ida", accessed October 25, 2021, at https://www.weather.gov/phi/eventreview20210901. U.S. Geological Survey, 2021a, Short-Term Network Flood Event Viewer for Tropical Cyclone Ida, accessed October 25, 2021, at https://stn.wim.usgs.gov/fev/#2021TropicalCycloneIda. U.S. Geological Survey, 2021b, USGS Water Science School: High-Water Marks and Flooding, accessed October 25, 2021, at https://www.usgs.gov/special-topic/water-science-school/science/high-water-marks-and-flooding?qt-science_center_objects=0#qt-science_center_objects.

About this dataset

Context

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

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)

• Jefferson Township, New Jersey Population Breakdown by Race
• Jefferson Township, New Jersey Non-Hispanic Population Breakdown by Race
• Jefferson Township, New Jersey 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/.

Feature layer generated from Join Features to show number of deaths from COVID 19 for Burlington County, NJ.

The Inventory of New Jersey’s The Inventory of New Jersey’s Estuarine Shellfish Resources is conducted on a rotating basis throughout the major Atlantic coastal estuaries of New Jersey. The primary purpose of the work is to estimate the standing stock of hard clams (Mercenaria mercenaria) and describe their relative distribution. Additionally, the survey describes the relative distribution of other commercially important bivalve species and vascular submerged aquatic vegetation (“SAV”), also known as seagrasses. Hard Clam: The substrate is sampled with a hydraulic hard clam dredge designed to retain clams sized 30mm and larger. All live clams collected are counted and measured to the nearest millimeter. The density of clams at each station is reported in clams per square foot. The resulting geospatial data represents the relative distribution of hard clams at either “none” (no clams collected), “low” (0.01 to 2), “moderate” (>0.20 - 2), or “high” (>0.50 clams/ft2) densities. Where no category designation is given, the area is considered a “no data” area relative to this survey. This means that the survey did not sample within this area for reasons including shallow water, obstructions, or the presence of shellfish aquaculture leases. The area may or may not be marked formally as such. However, a “no data” area may contain shellfish resources unknown to the Marine Resources Administration (MRA) or the MRA may have data for the area from other investigations. It does not automatically mean that the area is devoid of shellfish resources. This data represents a one point in time documentation of relative abundance of hard clams, and hard clams may be found presently in areas not previously sampled or at stations where they were not historically collected. Complete reports for each surveyed estuary provide methodology, analysis, charts, and additional pertinent information, and can be found on the NJ Fish and Wildlife’s website. The NJ Coastal Zone Management rules at N.J.A.C. 7:7 define shellfish densities of 0.2 clams per square foot or greater as productive shellfish habitat. The Leasing of Atlantic Coast Bottom for Aquaculture regulations discourages establishing leases in productive shellfish habitat (NJAC 7:25-24.6(d)). Note that this layer does not include delineation of shellfish leases or aquaculture development zones. Those data are provided separately. Data from 1980s were digitized based primarily on the georeferenced images of the 1980s’ map series, in combination with usage of the 1986 NJDEP Landuse/Landcover geospatial dataset to more accurately depict shoreline boundaries. Digitizing was completed using freehand and/or copying/pasting/editing waterbody features from the 1986 NJDEP Landuse/Landcover geospatial dataset. Digitizing was completed at a scale between 1:4,000 to 1:12,000. This data represents a digital interpretation of the original hard copy charts. Therefore, some anomalies may exist in the line features along the present-day coastline. Users should interpret the mapping to extend to the present-day coastline. Data from 2000s to present were created based upon survey station tabular data which was then mapped as a point feature class. Several GIS tools were then used to generate polygon features surrounding the stations to represent hard clam distribution (see Process Steps for more detail). Associated Species: When other commercially or recreationally important bivalve species are retained in the sample, they are documented, along with common invertebrate species. Data from the 1980s documents the presence of all other commercially and recreationally important bivalve species that are regulated by the State of New Jersey as well as common (but not all) shellfish predators that were retrained in the dredge while targeting hard clams. Presence indicates the area is productive for the species. The regulated bivalve species are soft clams (Mya arenaria), bay scallops (Argopecten irradians), surf clam (Spisula solidissima), Eastern oyster (Crassostrea virginica), and blue mussel (Mytilus edulis). This data is a point in time observation of production areas and regulated bivalve species may be found presently in areas not previously sampled or at stations where they were not historically collected. This data represents a digital interpretation of the original hard copy charts. Therefore, some anomalies may exist in the line features along the present-day coastline. Users should interpret the mapping to extend to the present-day coastline. It is important to note that this data is not a comprehensive evaluation of Eastern oyster populations in the Mullica River, Great Egg Harbor River, or Delaware Bay, which are surveyed separately and specifically for that species. Similarly, although surf clams are occasionally found in estuarine environments, the species primarily dwells in the Atlantic Ocean and separate comprehensive population surveys of state and federal waters are available. For additional species collected (for example sponges, non-commercial shellfish, etc.) please contact the Bureau of Shellfisheries. Historical reports for each surveyed estuary provide methodology, analysis, charts, and additional pertinent information, and can be requested by contacting the Marine Resources Administration. The features were digitized based primarily on the georeferenced images of the 1980s’ map series, in combination with usage of the 1986 NJDEP Land use/Landcover geospatial dataset in order to more accurately depict shoreline boundaries. Digitizing was completed using freehand and/or copying/pasting/editing waterbody features from the 1986 NJDEP Landuse/Landcover geospatial dataset. Digitizing was completed at a scale between 1:4,000 to 1:12,000. This data represents a digital interpretation of the original hard copy charts. Therefore, some anomalies may exist in the line features along the present-day coastline. Users should interpret the mapping to extend to the present-day coastline. Data from 2000 to present also documents the presence of all other commercially and recreationally important bivalve species that are regulated by the State of New Jersey as well as common invertebrates, including common bivalve predators. Presence indicates that area is productive for the species listed. The regulated bivalve species are soft clams (Mya arenaria), bay scallops (Argopecten irradians), surf clam (Spisula solidissima), Eastern oyster (Crassostrea virginica), and blue mussel (Mytilus edulis). This data is a one point in time observation of production areas and regulated bivalve species may be found presently in areas not previously sampled or at stations where they were not historically collected. It is important to note that this data is not a comprehensive evaluation of Eastern oyster populations in the Mullica River, Great Egg Harbor River, or Delaware Bay, which are surveyed separately and specifically for that species. Similarly, although surf clams are occasionally found in estuarine environments, the species primarily dwells in the Atlantic Ocean and separate comprehensive population surveys of state and federal waters are available. Further, data on channeled whelk (Busycotypus canaliculatus), knobbed whelk (Busycon carica), Atlantic horseshoe crab (Limulus polyphemus) and blue crab (Callinectes sapidus) are not intended for use in fishery management plans at this time. For additional species collected (for example sponges, non-commercial shellfish, etc.) please contact the Marine Resources Administration. This feature class was created based upon survey station tabular data which was then mapped as a point feature class. Several GIS tools were then used to generate polygon features surrounding the stations to represent each species’ distribution (see Process Steps for more detail). Submerged Aquatic Vegetation: When submerged aquatic vegetation (SAV; seagrass) is retained in the sample, or observed visually from the research vessel, the presence of the vegetation and species is noted. Only presence of the vegetation is provided, without inference regarding coverage, shoot density, or any other characteristic. Only regulated species (per N.J.A.C. 7:7-9.6) of vascular vegetation is presented here. This is primarily eelgrass (Zostera marina) and widgeon grass (Ruppia maritima. However, other regulated species are found in New Jersey. Data from 1980s is a “snapshot in time” of relative distribution of SAV, and SAV may be found presently in areas not previously sampled or at stations where they were not historically collected. Species composition may change over time. This data represents a digital interpretation of the original hard copy charts. Therefore, some anomalies may exist in the line features along the present-day coastline. Users should interpret the mapping to extend to the present-day coastline. Where hard copy charts were not previously created (Shrewsbury, Manasquan, and Metedeconk Rivers), a 1,000ft buffer was placed around the survey station where SAV was found. Historical reports for each surveyed estuary provide methodology, analysis, charts, and additional pertinent information, and can be requested by contacting the Marine Resources Administration. The SAV data from the 1980s can confirm the history of SAV in a given area, corroborating other survey years. However, further investigation is necessary if it is the only dataset available for a project. In such cases, please contact the Marine Resources Administration (MRA) as they may have information on the area that was collected during different surveys or is not yet published. Data from 2000s to present is also a “one point in time” documentation of relative distribution of SAV, and SAV may be found presently in areas not previously sampled or at stations where they were not historically collected. Species composition may change over time. Where SAV was found, a 1,000ft

Rate: New cases of end-stage renal disease (per 100,000 population).

Definition: New cases of end-stage renal disease per 100,000 population.

Data Sources:

(1) Population Estimates, State Data Center, New Jersey Department of Labor and Workforce Development

(2) Quality Insights Renal Network

About this dataset

Context

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

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)

• Berkeley Township, New Jersey Population Breakdown by Race
• Berkeley Township, New Jersey Non-Hispanic Population Breakdown by Race
• Berkeley Township, New Jersey 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/.

Municipal boundaries for Pennsylvania, New Jersey, Maryland, Delaware, and the District of Columbia with ortho-rectified municipal boundaries for the DVRPC Region. Municipal Boundaries have been edited by DVRPC to create a more accurate, seemless regional dataset for the DVRPC region and its surrounding area. This dataset was compiled from multiple sources. Original data sources (in order of drawing rank): DVRPC - for Mercer, Burlington, Camden, Gloucester counties in NJ (an adaptation of NJOIT's Mun Bounds) and Bucks, Montgomery, Philadelphia, Chester, and Delaware counties in PA. In most cases, boundaries have been adjusted to align with parcel data. NJOIT - remaining NJ counties (2008) PennDOT - remaining PA counties (2009) DE State Office of Mgmt & Budget - Delaware municipalities (2002) MD State Hwy Administration - Maryland municipalities (2003) Washington DC - ESRI NOTE: NJ's coast has been clipped or unioned to ESRI's data CD detailed state boundary

Due to a consolidation, Princeton Twp and Princeton Boro in Mercer County, NJ in 2013, the new municipality (named "Princeton"), uses Princeton Boro's unique ID 3402160900. Princeton Township's unique ID (3402160915)no longer exists.

Due to the name change from Washington Twp to Robbinsville Twp in Mercer County NJ in 2008, the unique ID (GEOID) for this municipality has changed from 3402177210 to 3402163850 . However, if you download 2000 census data from the Bureau's website, the unique ID (GEOID) for Robbinsville Township will still be 3402177210 in the census data…you will have to manually change its GEOID to 3402163850 in order to get the 2000 data to join to the MCD file correctly.

Due to name change from Birmingham Twp to Chadds Ford Twp in Delaware County, PA in 1997, the unique ID (GEOID) for this municipality has changed from 4204506552 to 4204512442.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

Researchers compiled datasets on prison admissions and releases that would be comparable across places and geocoded and mapped those data onto crime rates across those same places. The data used were panel data. The data were quarterly or annual data, depending on the location, from a mix of urban (Boston, Newark and Trenton) and rural communities in New Jersey covering various years between 2000 and 2010.

The crime, release, and admission data were individual level data that were then aggregated from the individual incident level to the census tract level by quarter (in Boston and Newark) or year (in Trenton). The analyses centered on the effects of rates of prison removals and returns on rates of crime in communities (defined as census tracts) in the cities of Boston, Massachusetts, Newark, New Jersey, and Trenton, New Jersey, and across rural municipalities in New Jersey.

There are 4 Stata data files. The Boston data file has 6,862 cases, and 44 variables. The Newark data file has 1,440 cases, and 45 variables. The Trenton data file has 66 cases, and 32 variables. The New Jersey Rural data file has 1,170 cases, and 32 variables.

This data is a graphical representation of the listing of licensed active child care centers in NJ. It was created for the State of New Jersey's initiative regarding child care centers near contaminated sites. The Child Care Centers GIS layer contains all active, licensed child care facilities within the State of New Jersey based on a spreadsheet provided to the NJDEP Site Remediation Waste Management Program (SRWMP) by the New Jersey Department of Children and Families (NJDCF) Office of Licensing. This monthly report also includes facilities operating in public schools (FOIPS) although these facilities are not required in most cases to submit environmental data to the NJDEP for NJDCF licensing. Proposed child care centers are not listed until a NJDCF License number is issued. ADVISORY: This data was created only to be used as guidance to find active child care centers. The data should not be used as the determining factor in conducting receptor evaluations and the actions taken to protect them. The child care data will be updated on a monthly basis as monthly updates of active child care facilities operation in New Jersey are provided to the NJDEP SRWMP by the NJDCF Office of Licensing. Users are hereby notified that data on NJDEP mapping applications for this data set may be more current than any downloadable shapefile, if provided.

About this dataset

Context

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

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)

• Piscataway Township, New Jersey Population Breakdown by Race
• Piscataway Township, New Jersey Non-Hispanic Population Breakdown by Race
• Piscataway Township, New Jersey 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/.

This dataset tracks annual two or more races student percentage from 2014 to 2023 for J.p. Case Middle School vs. New Jersey and Flemington-Raritan Regional School District

Ratio: Percent of cases simultaneously diagnosed with HIV and AIDS.

Definition: Number of cases simultaneously diagnosed with HIV and AIDS among all of those diagnosed with HIV / AIDS.

Data Source: Division of HIV/AIDS, STD, and TB Services, New Jersey Department of Health

The Assessment Unit (AU) level Temperature parameter results incorporates the water quality results for all monitoring stations associated within an AU that is included in the 2022 NJ Integrated Water Quality Monitoring and Assessment Report (Integrated Report). This data represents the assessment results in NJ's 958 AUs to determine if the Temperature parameter result was attained. If an AU includes more than one Temperature station, the ‘worst case’ station assessment represents the AU. That is, if any of the stations are impaired for Temperature, then the parameter is impaired at the AU level. If some stations are fully attaining for Temperature but others have insufficient data, then Temperature is fully attaining. The data reflects the results each assessment was assigned: Attaining- Fully Supporting, Insufficient Data- Insufficient data was available to assess, Non-Support- Non-Supporting.

This dataset tracks annual asian student percentage from 2007 to 2023 for J.p. Case Middle School vs. New Jersey and Flemington-Raritan Regional School District

About this dataset

Context

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

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)

• Haddon Township, New Jersey Population Breakdown by Race
• Haddon Township, New Jersey Non-Hispanic Population Breakdown by Race
• Haddon Township, New Jersey 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/.

About this dataset

Context

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

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)

• Jackson Township, New Jersey Population Breakdown by Race
• Jackson Township, New Jersey Non-Hispanic Population Breakdown by Race
• Jackson Township, New Jersey 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/.

This feature class depicts polygon features that were extracted from NJEMS data that could not be matched to any specific parcel in the TL_Parcels feature class. The features were manually researched in NJEMS and manually digitized and attributed. Script extraction of NJEMS data that could not be matched to specific parcels in the TL_Parcels data were populated as records in a table of unmatched activity data. These records were manually investigated in the NJEMS database to identify the location of the activities. The vast majority of the features in this dataset are associated with aquaculture licenses. Where possible, features were matched to lease area reference grids supplied by the Division of Fish & Wildlife. Otherwise, the areas were drawn from specific x/y coordinates provided in the applications. In some cases, adjoining areas from the same application were combined into the same polygon feature.

As included in this EnviroAtlas dataset, the community level domestic water use was calculated using locally available water use data per capita in gallons of water per day (GPD), distributed dasymetrically, and summarized by census block group. Domestic water use, as defined in this case, is intended to represent residential indoor and outdoor water use (e.g., cooking hygiene, landscaping, pools, etc.) for primary residences (i.e., excluding second homes and tourism rentals). For the purposes of this metric, these publicly-supplied estimates are also applied and considered representative of local self-supplied water use. Domestic water demand was calculated and applied using the Pennsylvania Department of Environmental Protection (PADEP) PWS Service Areas layer, population served per provider, and average domestic water use per provider. Within the EnviroAtlas study area, there are 108 service providers with 2016 estimates ranging from 26 to 323 GPD. In the absence of finer scale data, USGS Water Use Report county-level estimates were used for the study area extending into Delaware (80 GPD), Maryland (71 GPD), and New Jersey (80 GPD). This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

About this dataset

Context

The dataset presents median household incomes for various household sizes in Berkeley Heights Township, New Jersey, 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, Berkeley Heights township did not include 7-person households. Across the different household sizes in Berkeley Heights township the mean income is $206,851, and the standard deviation is $83,533. The coefficient of variation (CV) is 40.38%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households. Please note that the U.S. Census Bureau uses $250,001 as a JAM value to report incomes of $250,000 or more. In the case of Berkeley Heights township, there were 2 household sizes where the JAM values were used. Thus, the numbers for the mean and standard deviation may not be entirely accurate and have a higher possibility of errors. However, to obtain an approximate estimate, we have used a value of $250,001 as the income for calculations, as reported in the datasets by the U.S. Census Bureau.
• 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 $56,572. It then further increased to $270,229 for 6-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/berkeley-heights-township-nj-median-household-income-by-household-size.jpeg" alt="Berkeley Heights Township, New Jersey 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 Berkeley Heights township median household income. You can refer the same here