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) Database (MTDB). The MTDB 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. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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U.S. Census Bureau QuickFacts statistics for Tulsa city, Oklahoma. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.
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Context
This list ranks the 28 cities in the Tulsa County, OK by Non-Hispanic White population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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 provides information about the number of properties, residents, and average property values for Tulsa Avenue cross streets in Oklahoma City, OK.
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This list ranks the 28 cities in the Tulsa County, OK by Non-Hispanic Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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 survey was the second of two Tulsa area studies generally modeled on the Oklahoma City studies undertaken by the University of Oklahoma. Tulsa area residents were asked about a wide range of local and national issues with additional questions covering religious preference, educational and occupational background, and political attitudes and opinions.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
This list ranks the 28 cities in the Tulsa County, OK by Non-Hispanic Native Hawaiian and Other Pacific Islander (NHPI) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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/.
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Chart and table of population level and growth rate for the Tulsa metro area from 1950 to 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 28 cities in the Tulsa County, OK by Hispanic Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
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/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Credit report of Grace Turinawe Tulsa Oklahoma City Ok Usa contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Oklahoma City Blue NBA G League de oynayan ve merkezi Oklahoma eyaletinde Oklahoma City şehrinde bulunan bir Amerikan ba
https://www.oklahoma-demographics.com/terms_and_conditionshttps://www.oklahoma-demographics.com/terms_and_conditions
A dataset listing the 20 richest cities in Oklahoma for 2024, including information on rank, city, county, population, average income, and median income.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Oklahoma City Blue NBA G League de oynayan ve merkezi Oklahoma eyaletinde Oklahoma City şehrinde bulunan bir Amerikan ba
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This feature class models the future "ultimate" land use condition of the Tulsa Metro Area and the hydrologic curve numbers (CN) that correspond to the land use categories for various soil types. The land use categories are an amalgamation of the National Land Use Land Cover (LULC) database and local Future Land Use data contained within feature classes provided by the local municipalities (Bixby, Broken Arrow, Glenpool, Jenks, Owasso, Sand Springs, Sperry, City of Tulsa, and Tulsa County). The National LULC database forms the base of the dataset. Anywhere local future land use data was available, the associated polygons replaced the National LULC data. The dataset is clipped to an area that bounds the major hydrologic catchments that impact the City of Tulsa. The local datasets were altered programmatically to remove polygons that were duplicates or that lacked data that described the future land use of that polygon. In the case of the City of Tulsa, the future land use in areas deemed "stable" were removed under the assumption that the National Land Use Land Cover dataset of the current condition (derived through remote sensing) is more detailed and accurate than broad planning areas if the condition is not expected to change. This dataset is intended to be used in hydrologic modeling to represent the "ultimate" condition that is currently planned for ultimate future build-out with future development. For each land use condition, the city storm water engineer has attributed CN values, a hydrologic parameter that describes the stormwater runoff potential, that correspond to each land use category for each soil type (A, B, C, D, A/B. A/C, B/C, A/D, B/C, C/D). The numbers were assigned for each land use category by selecting the best match to charts of research values from a number of scientifically validated sources: USDA (United state Department of Agriculture) Urban Hydrology for Small Watershed, Technical release 55 (TR-55) reference manual, 210-VI-TR-55, Second Ed., June 1986.Chow, V.T. et al., 1988. Applied Hydrology. McGraw-Hill Book Company, Inc. New York, NY.National engineering handbook, Part 630 Hydrology, Section 4-Hydrology, Chapter 5-10. National Resources Conservation Services (NRCS), 210-vi, NEH, September 1997, Washington, DC.United States Department of Agriculture, Forest Service. 1959a. Forest and range hydrology handbook. Washington, DC.United States Department of Agriculture, Forest Service. 1959b. Section 1 of Handbook on methods of hydrologic analysis, Section 1. Washington, DC.United States Department of Agriculture, Natural Resources Conservation Service. 2003. Small Watershed Hydrology (WinTR–55), November 2003.United States Department of Agriculture, Natural Resources Conservation Service. 2004. Watershed Hydrology (WinTR–20), draft, March 2004.Soil Conservation Service, 1982. TR-20, Project Formulation-Hydrology, Technical Release 20, Lanham, MD.ODOT (Oklahoma Department of Transportation) Roadway Drainage Manual, Chapter 7 Hydrology, November 2014.USDOT (United state Department of Transportation) Hydraulic Engineering Circular (HEC-22) No. 22, 3rd Edition, Urban Drainage Design Manual, Publication No. FHWA-NHI-10-009, September 2009, Revised August 2013.AASHTO. Highway Drainage Guidelines, Chapter 2 Hydrology. Washington, DC : Technical Committee on Hydrology and Hydraulics, American Association of State Highway and Transportation Officials, 2007.FHWA. Highway Hydrology, Hydraulic Design Series No. 2, 2nd Edition. Washington, DC: Federal Highway Administration, 2002. FHWA-NHI-02-001.NCRS. A Method for Estimating Volume and Rate of Runoff in Small Watersheds. Washington, DC : National Resources Conservation Service, US Department of Agriculture, 1973. SCS-TP-149.Chow, V. T., and B. C. Yen, Urban stormwater runoff: determination of volumes and flowrates, report EPA-600/2-76-116, Municipal Environmental Research Laboratory, Office of Research and Development, U. S. Environmental Protection Agency, Cincinnati, Ohio, May 1976.Chow, V.T. 1959. Open channel hydraulics. McGraw-Hill Book Company, Inc. New York, NY.American Society of Civil Engineers, 1992. Design and Construction of Urban Stormwater Management Systems, "ASCE Manuals and Reports of Engineering Practice No. 77, WEF Manual of Practice FD-20," New York, NY.American Public Works Association Research Foundation and the Institute for Water Resources, 1981. Urban Stormwater Management, Special Report No. 49, American Public Works Association, Washington, D.C.Rawls, W.J., A. Shalaby, and R.H. McCuen. 1981. Evaluation of methods for determining urban runoff curve numbers. Trans. Amer. Soc. Agriculture. Eng. 24(6):1562-1566
Disc golf is a flying disc sport in which players throw a disc at a target using similar rules to golf. The courses commonly have nine or 18 holes. In the United States, some cities are home to more disc golf courses than others. Tulsa, Oklahoma and Spokane, Washington had the greatest density with 2.2 disc golf courses per 100,000 residents.
This statistic shows the leading metropolitan areas in the United States in 2023 with the highest percentage of American Indian or Alaska Native population. Among the 81 largest metropolitan areas, Tulsa, Oklahoma was ranked first, with 14.6 percent of the population reporting as American Indian/Alaska Native in 2023.
https://www.oklahoma-demographics.com/terms_and_conditionshttps://www.oklahoma-demographics.com/terms_and_conditions
A dataset listing Oklahoma counties by population for 2024.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Clayton Clay Ike Bennett d 1959 LLC Profesyonel Basketbol Kulübü Oklahoma City Thunder ve Tulsa 66ers in sahibi olan Ame
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Tulsa: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
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 Tulsa median household income by age. You can refer the same here
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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) Database (MTDB). The MTDB 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. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.