Census Blocks in Macon-Bibb County.
A census block is the smallest geographic unit used by the United States Census Bureau for tabulation of 100-percent data (data collected from all houses, rather than a sample of houses). The number of blocks in the United States, including Puerto Rico, for the 2010 Census was 11,155,486.[1]
Census blocks are grouped into block groups, which are grouped into census tracts. There are on average about 39 blocks per block group. Blocks typically have a four-digit number; the first number indicates which block group the block is in. For example, census block 3019 would be in block group 3.
Blocks are typically bounded by streets, roads or creeks. In cities, a census block may correspond to a city block, but in rural areas where there are fewer roads, blocks may be limited by other features. The population of a census block varies greatly. As of the 2010 census, there were 4,871,270 blocks with a reported population of zero,[2] while a block that is entirely occupied by an apartment complex might have several hundred inhabitants.
Census blocks covering the entire country were introduced with the 1990 census. Before that, back to the 1940 census, only selected areas were divided into blocks.
To review a table detailing Census Block information in the United States visit https://www.census.gov/geo/maps-data/data/tallies/tractblock.
https://www.icpsr.umich.edu/web/ICPSR/studies/28501/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/28501/terms
The 1915 Iowa State Census is a unique document. It was the first census in the United States to include information on education and income prior to the United States Federal Census of 1940. It contains considerable detail on other aspects of individuals and households, e.g., religion, wealth and years in the United States and Iowa. The Iowa State Census of 1915 was a complete sample of the residents of the state and the returns were written by census takers (assessors) on index cards. These cards were kept in the Iowa State Archives in Des Moines and were microfilmed in 1986 by the Genealogical Society of Salt Lake City. The census cards were sorted by county, although large cities (those having more than 25,000 residents) were grouped separately. Within each county or large city, records were alphabetized by last name and within last name by first name. This data set includes individual-level records for three of the largest Iowa cities (Des Moines, Dubuque, and Davenport; the Sioux City films were unreadable) and for ten counties that did not contain a large city. (Additional details on sample selection are available in the documentation). Variables include name, age, place of residence, earnings, education, birthplace, religion, marital status, race, occupation, military service, among others. Data on familial ties between records are also included.
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License information was derived automatically
This dataset comprises physician-level entries from the 1906 American Medical Directory, the first in a series of semi-annual directories of all practicing physicians published by the American Medical Association [1]. Physicians are consistently listed by city, county, and state. Most records also include details about the place and date of medical training. From 1906-1940, Directories also identified the race of black physicians [2].This dataset comprises physician entries for a subset of US states and the District of Columbia, including all of the South and several adjacent states (Alabama, Arkansas, Delaware, Florida, Georgia, Kansas, Kentucky, Louisiana, Maryland, Mississippi, Missouri, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia). Records were extracted via manual double-entry by professional data management company [3], and place names were matched to latitude/longitude coordinates. The main source for geolocating physician entries was the US Census. Historical Census records were sourced from IPUMS National Historical Geographic Information System [4]. Additionally, a public database of historical US Post Office locations was used to match locations that could not be found using Census records [5]. Fuzzy matching algorithms were also used to match misspelled place or county names [6].The source of geocoding match is described in the “match.source” field (Type of spatial match (census_YEAR = match to NHGIS census place-county-state for given year; census_fuzzy_YEAR = matched to NHGIS place-county-state with fuzzy matching algorithm; dc = matched to centroid for Washington, DC; post_places = place-county-state matched to Blevins & Helbock's post office dataset; post_fuzzy = matched to post office dataset with fuzzy matching algorithm; post_simp = place/state matched to post office dataset; post_confimed_missing = post office dataset confirms place and county, but could not find coordinates; osm = matched using Open Street Map geocoder; hand-match = matched by research assistants reviewing web archival sources; unmatched/hand_match_missing = place coordinates could not be found). For records where place names could not be matched, but county names could, coordinates for county centroids were used. Overall, 40,964 records were matched to places (match.type=place_point) and 931 to county centroids ( match.type=county_centroid); 76 records could not be matched (match.type=NA).Most records include information about the physician’s medical training, including the year of graduation and a code linking to a school. A key to these codes is given on Directory pages 26-27, and at the beginning of each state’s section [1]. The OSM geocoder was used to assign coordinates to each school by its listed location. Straight-line distances between physicians’ place of training and practice were calculated using the sf package in R [7], and are given in the “school.dist.km” field. Additionally, the Directory identified a handful of schools that were “fraudulent” (school.fraudulent=1), and institutions set up to train black physicians (school.black=1).AMA identified black physicians in the directory with the signifier “(col.)” following the physician’s name (race.black=1). Additionally, a number of physicians attended schools identified by AMA as serving black students, but were not otherwise identified as black; thus an expanded racial identifier was generated to identify black physicians (race.black.prob=1), including physicians who attended these schools and those directly identified (race.black=1).Approximately 10% of dataset entries were audited by trained research assistants, in addition to 100% of black physician entries. These audits demonstrated a high degree of accuracy between the original Directory and extracted records. Still, given the complexity of matching across multiple archival sources, it is possible that some errors remain; any identified errors will be periodically rectified in the dataset, with a log kept of these updates.For further information about this dataset, or to report errors, please contact Dr Ben Chrisinger (Benjamin.Chrisinger@tufts.edu). Future updates to this dataset, including additional states and Directory years, will be posted here: https://dataverse.harvard.edu/dataverse/amd.References:1. American Medical Association, 1906. American Medical Directory. American Medical Association, Chicago. Retrieved from: https://catalog.hathitrust.org/Record/000543547.2. Baker, Robert B., Harriet A. Washington, Ololade Olakanmi, Todd L. Savitt, Elizabeth A. Jacobs, Eddie Hoover, and Matthew K. Wynia. "African American physicians and organized medicine, 1846-1968: origins of a racial divide." JAMA 300, no. 3 (2008): 306-313. doi:10.1001/jama.300.3.306.3. GABS Research Consult Limited Company, https://www.gabsrcl.com.4. Steven Manson, Jonathan Schroeder, David Van Riper, Tracy Kugler, and Steven Ruggles. IPUMS National Historical Geographic Information System: Version 17.0 [GNIS, TIGER/Line & Census Maps for US Places and Counties: 1900, 1910, 1920, 1930, 1940, 1950; 1910_cPHA: ds37]. Minneapolis, MN: IPUMS. 2022. http://doi.org/10.18128/D050.V17.05. Blevins, Cameron; Helbock, Richard W., 2021, "US Post Offices", https://doi.org/10.7910/DVN/NUKCNA, Harvard Dataverse, V1, UNF:6:8ROmiI5/4qA8jHrt62PpyA== [fileUNF]6. fedmatch: Fast, Flexible, and User-Friendly Record Linkage Methods. https://cran.r-project.org/web/packages/fedmatch/index.html7. sf: Simple Features for R. https://cran.r-project.org/web/packages/sf/index.html
2000 Census blocks for the Wichita / Sedgwick County area, clipped to the county line. Features were extracted based upon County FIPS code 173 which correlates to Sedgwick County Kansas.US Census Defines Census Block as the following: A census block is the smallest geographic unit used by the United States Census Bureau for tabulation of 100-percent data (data collected from all houses, rather than a sample of houses).Census blocks are grouped into block groups, which are grouped into census tracts. There are on average about 39 blocks per block group. Blocks typically have a four-digit number; the first number indicates which block group the block is in. For example, census block 3019 would be in block group 3.[2]Blocks are typically bounded by roads and highways, town/city/county/state boundaries, creeks and rivers, etc. In cities, a census block may correspond to a city block, but in rural areas where there are fewer roads, blocks may be delimited by other features such as political boundaries, rivers and other natural features, as well as parks and similar facilities, etc. The population of a census block varies greatly. As of the 2010 census, there were 4,871,270 blocks with a reported population of zero,[3] while a block that is entirely occupied by an apartment complex might have several hundred inhabitants.Census blocks covering the entire country were introduced with the 1990 census. Before that, back to the 1940 census, only selected areas were divided into blocks.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
PLURAL (Place-level urban-rural indices) is a framework to create continuous classifications of "rurality" or "urbanness" based on the spatial configuration of populated places. PLURAL makes use of the concept of "remoteness" to characterize the level of spatial isolation of a populated place with respect to its neighbors. There are two implementations of PLURAL, including (a) PLURAL-1, based on distances to the nearest places of user-specified population classes, and (b) PLURAL-2, based on neighborhood characterization derived from spatial networks. PLURAL requires simplistic input data, i.e., the coordinates (x,y) and population p of populated places (villages, towns, cities) in a given point in time. Due to its simplistic input, the PLURAL rural-urban classification scheme can be applied to historical data, as well as to data from data-scarce settings. Using the PLURAL framework, we created place-level rural-urban indices for the conterminous United States from 1930 to 2018. Rural-urban classifications are essential for analyzing geographic, demographic, environmental, and social processes across the rural-urban continuum. Most existing classifications are, however, only available at relatively aggregated spatial scales, such as at the county scale in the United States. The absence of rurality or urbanness measures at high spatial resolution poses significant problems when the process of interest is highly localized, as with the incorporation of rural towns and villages into encroaching metropolitan areas. Moreover, existing rural-urban classifications are often inconsistent over time, or require complex, multi-source input data (e.g., remote sensing observations or road network data), thus, prohibiting the longitudinal analysis of rural-urban dynamics. We developed a set of distance- and spatial-network-based methods for consistently estimating the remoteness and rurality of places at fine spatial resolution, over long periods of time. Based on these methods, we constructed indices of urbanness for 30,000 places in the United States from 1930 to 2018. We call these indices the place-level urban-rural index (PLURAL), enabling long-term, fine-grained analyses of urban and rural change in the United States. The method paper has been peer-reviewed and is published in "Landscape and Urban Planning". The PLURAL indices from 1930 to 2018 are available as CSV files, and as point-based geospatial vector data (.SHP). Moreover, we provide animated GIF files illustrating the spatio-temporal variation of the different variants of the PLURAL indices, illustrating the dynamics of the rural-urban continuum in the United States from 1930 to 2018. Apply the PLURAL rural-urban classification to your own data: Python code is fully open source and available at https://github.com/johannesuhl/plural. Data sources: Place-level population counts (1980-2010) and place locations 1930 - 2018 were obtained from IPUMS NHGIS, (University of Minnesota, www.nhgis.org; Manson et al. 2022). Place-level population counts 1930-1970 were digitized from historical census records (U.S. Census Bureau 1942, 1964). References: Uhl, J.H., Hunter, L.M., Leyk, S., Connor, D.S., Nieves, J.J., Hester, C., Talbot, C. and Gutmann, M., 2023. Place-level urban–rural indices for the United States from 1930 to 2018. Landscape and Urban Planning, 236, p.104762. DOI: https://doi.org/10.1016/j.landurbplan.2023.104762 Steven Manson, Jonathan Schroeder, David Van Riper, Tracy Kugler, and Steven Ruggles. IPUMS National Historical Geographic Information System: Version 16.0 [dataset]. Minneapolis, MN: IPUMS. 2021. http://doi.org/10.18128/D050.V16.0 U.S. Census Bureau (1942). U.S. Census of Population: 1940. Vol. I, Number of Inhabitants. U.S. Government Printing Office, Washington, D.C. U.S. Census Bureau (1964). U.S. Census of Population: 1960. Vol. I, Characteristics of the Population. Part I, United States Summary. U.S. Government Printing Office, Washington, D.C.
2010 Census blocks or the Wichita / Sedgwick County area, clipped to the county line. Features were extracted based upon County FIPS code 173 which correlates to Sedgwick County Kansas.US Census Defines Census Block as the following: A census block is the smallest geographic unit used by the United States Census Bureau for tabulation of 100-percent data (data collected from all houses, rather than a sample of houses).Census blocks are grouped into block groups, which are grouped into census tracts. There are on average about 39 blocks per block group. Blocks typically have a four-digit number; the first number indicates which block group the block is in. For example, census block 3019 would be in block group 3.[2]Blocks are typically bounded by roads and highways, town/city/county/state boundaries, creeks and rivers, etc. In cities, a census block may correspond to a city block, but in rural areas where there are fewer roads, blocks may be delimited by other features such as political boundaries, rivers and other natural features, as well as parks and similar facilities, etc. The population of a census block varies greatly. As of the 2010 census, there were 4,871,270 blocks with a reported population of zero,[3] while a block that is entirely occupied by an apartment complex might have several hundred inhabitants.Census blocks covering the entire country were introduced with the 1990 census. Before that, back to the 1940 census, only selected areas were divided into blocks.
2020 Census blocks for the Wichita / Sedgwick County area, clipped to the county line. Features were extracted based upon County FIPS code 173 which correlates to Sedgwick County Kansas.US Census Defines Census Block as the following: A census block is the smallest geographic unit used by the United States Census Bureau for tabulation of 100-percent data (data collected from all houses, rather than a sample of houses).Census blocks are grouped into block groups, which are grouped into census tracts. There are on average about 39 blocks per block group. Blocks typically have a four-digit number; the first number indicates which block group the block is in. For example, census block 3019 would be in block group 3.[2]Blocks are typically bounded by roads and highways, town/city/county/state boundaries, creeks and rivers, etc. In cities, a census block may correspond to a city block, but in rural areas where there are fewer roads, blocks may be delimited by other features such as political boundaries, rivers and other natural features, as well as parks and similar facilities, etc. The population of a census block varies greatly. As of the 2010 census, there were 4,871,270 blocks with a reported population of zero,[3] while a block that is entirely occupied by an apartment complex might have several hundred inhabitants.Census blocks covering the entire country were introduced with the 1990 census. Before that, back to the 1940 census, only selected areas were divided into blocks.
1990 Census blocks for the Wichita / Sedgwick County area, clipped to the county line. Features were extracted based upon County FIPS code 173 which correlates to Sedgwick County Kansas.US Census Defines Census Block as the following: A census block is the smallest geographic unit used by the United States Census Bureau for tabulation of 100-percent data (data collected from all houses, rather than a sample of houses).Census blocks are grouped into block groups, which are grouped into census tracts. There are on average about 39 blocks per block group. Blocks typically have a four-digit number; the first number indicates which block group the block is in. For example, census block 3019 would be in block group 3.[2]Blocks are typically bounded by roads and highways, town/city/county/state boundaries, creeks and rivers, etc. In cities, a census block may correspond to a city block, but in rural areas where there are fewer roads, blocks may be delimited by other features such as political boundaries, rivers and other natural features, as well as parks and similar facilities, etc. The population of a census block varies greatly. As of the 2010 census, there were 4,871,270 blocks with a reported population of zero,[3] while a block that is entirely occupied by an apartment complex might have several hundred inhabitants.Census blocks covering the entire country were introduced with the 1990 census. Before that, back to the 1940 census, only selected areas were divided into blocks.
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Census Blocks in Macon-Bibb County.
A census block is the smallest geographic unit used by the United States Census Bureau for tabulation of 100-percent data (data collected from all houses, rather than a sample of houses). The number of blocks in the United States, including Puerto Rico, for the 2010 Census was 11,155,486.[1]
Census blocks are grouped into block groups, which are grouped into census tracts. There are on average about 39 blocks per block group. Blocks typically have a four-digit number; the first number indicates which block group the block is in. For example, census block 3019 would be in block group 3.
Blocks are typically bounded by streets, roads or creeks. In cities, a census block may correspond to a city block, but in rural areas where there are fewer roads, blocks may be limited by other features. The population of a census block varies greatly. As of the 2010 census, there were 4,871,270 blocks with a reported population of zero,[2] while a block that is entirely occupied by an apartment complex might have several hundred inhabitants.
Census blocks covering the entire country were introduced with the 1990 census. Before that, back to the 1940 census, only selected areas were divided into blocks.
To review a table detailing Census Block information in the United States visit https://www.census.gov/geo/maps-data/data/tallies/tractblock.