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TwitterVintage 2020 population projections by Hispanic origin (total population/Hispanic/non-Hispanic) and race (white/non-white) for North Carolina and North Carolina counties. Includes estimates from 2010 through 2019 and population projections from 2020 through 2050.
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Context
The dataset tabulates the Rockingham County 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 Rockingham County. The dataset can be utilized to understand the population distribution of Rockingham County by age. For example, using this dataset, we can identify the largest age group in Rockingham County.
Key observations
The largest age group in Rockingham County, NC was for the group of age 60 to 64 years years with a population of 7,169 (7.86%), according to the ACS 2018-2022 5-Year Estimates. At the same time, the smallest age group in Rockingham County, NC was the 85 years and over years with a population of 2,050 (2.25%). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates
Age groups:
Variables / Data Columns
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.
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 is a part of the main dataset for Rockingham County Population by Age. You can refer the same here
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TwitterDecennial census counts and population estimates and projections by age, race, and sex for North Carolina and all counties. Produced by the State Demographer of North Carolina. Race categorizes as defined by Census Bureau's Modified Race Data Summary Files. CAUTION: Historical data on race have not been normalized here - there is a break in 2010. See full projection dataset on demography.osbm.nc.gov for normalized race categories from 2000 through 2050.
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Population projections for Pacific Island Countries and territories from 1950 to 2050, by sex and by 5-years age groups.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Emerald Isle population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Emerald Isle. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 2,050 (52.36% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Age cohorts:
Variables / Data Columns
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.
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 is a part of the main dataset for Emerald Isle Population by Age. You can refer the same here
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Land use and land cover change models and scenarios are essential to understand the interconnections between global and regional factors influencing land use and demand changes, especially if we consider population growth and food demand projections in 2050.
Understanding the future of changes in land use and land cover in Brazil is fundamental for the future of global climate and biodiversity, given the richness of its five biomes. Thus, the new spatially explicit regional scenarios were developed for Brazil by 2050. Those scenarios are aligned with the Shared Socio-Economic Pathways (SSPs) and Representative Concentration Pathway (RCPs). Aim to detail global models regionally and can be used both regionally to support decision-making and enrich the overall analysis.
For the development of these new scenarios, the LuccME spatially explicit land change allocation modeling framework and the INLAND surface model were combined to incorporate climatic variables in water deficit and biophysical, socioeconomic, and institutional factors for Brazil. The scenarios were developed for land use and land cover classes: forest vegetation, grassland vegetation, planted pasture, agriculture, mosaic of occupations, and forestry.
The dataset comes in NetCDF format and includes the following products:
LUCCMEBR_land_cover_type_100km2_2000.nc: Percentage of land use and land cover for the year 2000 (Observed data).
LUCCMEBR_land_cover_type_100km2_2010.nc: Percentage of land use and land cover for the year 2010 (Observed data).
LUCCMEBR_land_cover_type_100km2_2012.nc: Percentage of land use and land cover for the year 2012 (Observed data).
LUCCMEBR_land_cover_type_100km2_2014.nc: Percentage of land use and land cover for the year 2014 (Observed data).
LUCCMEBR_SSP1_RCP19_land_cover_type_100km2_2015_2050.nc: Percentage of land use and land cover for the period 2015-2050 (Simulated data). This scenario considers the combination of SSP1 and RCP1.9.
LUCCMEBR_SSP2_RCP45_land_cover_type_100km2_2015_2050.nc: Percentage of land use and land cover for the period 2015-2050 (Simulated data). This scenario considers the combination of SSP2 and RCP4.5.
LUCCMEBR_SSP3_RCP70_land_cover_type_100km2_2015_2050.nc: Percentage of land use and land cover for the period 2015-2050 (Simulated data). This scenario considers the combination of SSP3 and RCP7.0.
Data
Percentage of land use and land cover classes: Forest vegetation (veg), Grassland vegetation (gveg), Planted pasture (pastp), Agriculture (agric), Mosaic of occupation (mosc), Forestry (fores) and Others (others).
Spatial resolution
The scenarios are available in a spatial resolution of 0.083º x 0.083º (~100 km²) and cover the entire Brazilian territory.
Temporal resolution
Period of observed data: 2000, 2010, 2012 e 2014
Scenario Period: 2015 – 2050 (each five-year)
Coordinate reference system
Geographic Coordinate System with Datum WGS84 (EPSG4326)
Data format
Data is provided as NetCDF.
Dataset usage
It is free to use, but please make sure to cite the repository and our paper properly if you use this dataset.
Publication & further information
For additional scenario information, please contact Francisco Gilney Silva Bezerra (franciscogilney@gmail.com).
Acknowledgments
The authors thank the project “MSA / BNDES (Environmental Monitoring by Satellite in the Amazon biome)” for financing the development of LuccMEBR.
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License information was derived automatically
Context
The dataset tabulates the Tyrrell County population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Tyrrell County. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.
Key observations
The largest age group was 18 to 64 years with a poulation of 2,050 (60.49% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.
Age cohorts:
Variables / Data Columns
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.
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 is a part of the main dataset for Tyrrell County Population by Age. You can refer the same here
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TwitterVintage 2020 population projections by Hispanic origin (total population/Hispanic/non-Hispanic) and race (white/non-white) for North Carolina and North Carolina counties. Includes estimates from 2010 through 2019 and population projections from 2020 through 2050.