This graph shows the population density in the federal state of New Jersey from 1960 to 2018. In 2018, the population density of New Jersey stood at 1,211.3 residents per square mile of land area.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Harvard Forest (HFR) contains human population density measurements in numberPerKilometerSquared units and were aggregated to a yearly timescale.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined because of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard Census Bureau geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous.

This data set represents 2000 population density by block group as a 100-m grid using data from the 2000 Census of Population and Housing. The demographic data is from CensusCD 2000 Short Form Blocks published by GeoLytics, E. Brunswick, NJ, which uses the 2000 Census Summary File 1 (SF 1). Grid cell values represent population density in people per square kilometer multiplied by 10 so that the data could be stored as integer.

This raster dataset represents 2020 population density from the Gridded Population of the World, Version 4 (GPWv4) dataset, sourced from the Center for International Earth Science Information Network (CIESIN). The data has been clipped to the Northeast USA and normalized to a 0-100 scale to facilitate comparison between population distribution and recreational use of forests. This raster helps identify spatial outliers, where forest recreation is high in areas with low population density, offering insights for land management and conservation planning.Data Source:GPWv4 Population Density, 2020 Revision 11Clipped to the Northeast (ME, NH, VT, NY, MA, CT, RI, PA, NJ)Use Case:Used to compare forest recreation hotspots with population density, revealing areas where recreation is disproportionate to local population, assisting in identifying outliers for focused study or management efforts.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Harvard Forest (HFR) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

Eligible Neighborhood Preservation Program Census Tracts consist of Census Tracts that were eligible in the prior funding cycle (Legacy Tracts) as well as newly identified Census Tracts (New Tracts) in the 2021 funding cycle. New Tracts are located in municipalities where the following criteria are met: 1. Neighborhood decline requirement (threatened): The Census Tract is on a negative trajectory since 2010 through 2019 on an index of housing vacancies, home values, jobs, and poverty (75th Percentile on Index) OR Municipal COVID Economic Impact Score of 53.6 or higher - median for block groups (Score is an index of the post-COVID change in the unemployment rate and the business vacancy rate) AND The Census Tract has at least one block group with a Median Household Income less than State Median. 2. Viability requirement (viable): The Census Tract has at least one block group with a Median Home Value at least 50% of County Median. 3. Mixed-use requirement: The Census Tract has a Job to population ratio above the state median AND The Census Tract Has at least one block group with a mixed block share that is over twice the state median. A mixed block is a block with at least one commercial parcel and one residential or apartment parcel. 4. Walkability requirement: The Census Tract has at least one block group with a Walkability Score above the state average (Score consists of median block size, % walking to work, and population density). Legacy Tracts that established eligibility in the prior funding cycle were defined using the following criteria: (1) Municipalities must rank between the 64th and 98th percentiles on the Municipal Revitalization Index. (2) Municipalities must have at least one neighborhood (census tract) meeting the following criteria: (a) On a negative trajectory since 2010 through 2016 on an index of housing vacancies, home values, jobs, and poverty. (b) Below the state median income level. (c) Home values at least 60% of the county median. (d) Job to population ratio above the state median. (3) Municipalities must have sufficient mixed-use blocks (defined as any block with at least one residential lot and one commercial block) as measured by: State of New Jersey: Neighborhood Preservation Program Guidelines. (a) Municipality has more mixed use blocks than the State median number (33) or; (b) Municipality has at least two times the State median for mixed use blocks as a percentage of all blocks (35.4%). (4) Municipalities must have at least one “walkable” neighborhood as measured by: (a) Median block size of no more than 25% greater than the State median; (b) The percentage of employed people walking to work is more than two times the State median; (c) The jobs to population ratio is more than two times the State median or the ratio of jobs to square mile is more than 150% of the State median; (d) The population density is no less than 25% of the State median.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Harvard Forest (HFR) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

This dataset contains the boundaries of the Planning Areas of the NJ State Development and Redevelopment Plan (NJSDRP). The State Plan's Statewide Policies are applied to the natural and built resources of the state through the designation of five Planning Areas. These Planning Areas reflect distinct geographic and economic units within the state and serve as an organizing framework for application of the Statewide Policies of the State Plan. Planning Areas are areas of land, not less than one square mile, that share certain conditions, such as population density, infrastructure systems, level of development, or environmental sensitivity. Planning Areas do not necessarily coincide with municipal or county boundaries, but define geographic areas that are suitable for common application of public policy. The State Plan anticipates continued growth throughout New Jersey in all Planning Areas. The character, location and magnitude of this growth vary among Planning Areas according to the specific character of the area. Each Planning Area has Policy Objectives that guide growth in the context of its unique qualities and conditions. The Policy Objectives also shape and define the application of the Statewide Policies in each Planning Area. Refer to the NJSDRP for further description of the geographic nature of Planning Areas.

This dataset contains the boundaries of the Urban Complexes of the NJ State Development and Redevelopment Plan (NJSDRP). Adopted March 1, 2001.

The State Plan's Statewide Policies are applied to the natural and built resources of the state through the designation of five Planning Areas. These Planning Areas reflect distinct geographic and economic units within the state and serve as an organizing framework for application of the Statewide Policies of the State Plan. Planning Areas are areas of land, not less than one square mile, that share certain conditions, such as population density, infrastructure systems, level of development, or environmental sensitivity. Planning Areas do not necessarily coincide with municipal or county boundaries, but define geographic areas that are suitable for common application of public policy. The State Plan anticipates continued growth throughout New Jersey in all Planning Areas. The character, location and magnitude of this growth vary among Planning Areas according to the specific character of the area. Each Planning Area has Policy Objectives that guide growth in the context of its unique qualities and conditions. The Policy Objectives also shape and define the application of the Statewide Policies in each Planning Area. Refer to the NJSDRP for further description of the geographic nature of Planning Areas.

Source: http://www.nj.gov/dca/divisions/osg/resources/gis.html

The 2015 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2010.

This surface hydrology dataset complements 13 other datasets as part of a study that compared ancient settlement patterns with modern environmental conditions in the Jazira region of Syria. This study examined settlement distribution and density patterns over the past five millennia using archaeological survey reports and French 1930s 1:200,000 scale maps to locate and map archaeological sites. An archaeological site dataset was created and compared to and modelled with soil, geology, terrain (contour), surface and subsurface hydrology and normal and dry year precipitation pattern datasets; there are also three spreadsheet datasets providing 1963 precipitation and temperature readings collected at three locations in the region. The environmental datasets were created to account for ancient and modern population subsistence activities, which comprise barley and wheat farming and livestock grazing. These environmental datasets were subsequently modelled with the archaeological site dataset, as well as, land use and population density datasets for the Jazira region. Ancient trade routes were also mapped and factored into the model, and a comparison was made to ascertain if there was a correlation between ancient and modern settlement patterns and environmental conditions; the latter influencing subsistence activities. All surface hydrology was captured for this dataset including ephemeral streams such as wadis. This dataset's attributes include stream order (0 to 6) and types (ephemeral, intermittent and permanent) and values. Settlement pattern evidence suggests that water runoff, from ephemeral and seasonal streams, could have been used to irrigate crops? Rainfall patterns in the Jazira region indicate more for higher elevations, this occurring during wetter times of the year (winter and spring). Surface hydrology line data captured from the following 1:200,000 French series maps: 1) NI-37 XVII, Abou Kemal 2) NI-37 XVIII, Ana 3) NI-37 XXI, Ressafe 4) NI-37 XXII, Raqqa 5) NI-37 XXIII, Deir ez Zoir 6) NI-37 XXIV, Bouara 7) NI-37-III, Djerablous 8) NJ-37 IV, Toual Aaba 9) NJ-37 V, Hassetche 10) NJ-37 VI, Qamishliye-Sinjar 11) (No sheet number), Qaratchok-Darh Dresse par la Service Geographique des F.F.L. en 1945 Reimprime par l'Institut Geographique National en 1950 (Originally produced by this Geographic Service of the F.F.L. (Forces Francaises Libres) in 1945 and reprinted by the National Geographic Institute in 1950). Paris: France. Institut Geographique National, 1945-1950. Original map series might be traced to Beirut: Bureau Topographique des Troupes francaises du Levant, 1933-1938.The surface hydrology dataset was captured from 11 map sheets, which were based on the French Levant surveys conducted in Syria during the 1930s and mapped at a scale of 1:200,000. The size of each map measures 69 x 59 cm. The surface hydrology lines on each sheet were traced to mylar. Subsequently, each mylar sheet was photocopied and reduced in size to an 11 x 17 inch sheet. These sheets were merged to form the contiguous area comprising the full extent of the boundary for the study area. This was then traced again to another mylar sheet and subsequently scanned and cleaned for further processing and use in a GIS. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2010-06-30 and migrated to Edinburgh DataShare on 2017-02-21.