Community Reporting Areas with selected 1990, 2000, 2010, 2020 P.L. 94-171 redistricting data. This includes group quarters population (institutionalized/non) from the 1990, 2000 and 2010 summary file to be consistent with the available 2020 data.For more information about the P.L. 94-171 redistricting data, please visit the U.S. Census Bureau. For a detailed description of the data included please see the 2020 Census State Redistricting Data Summary File.

Please Note: Community Reporting Areas (CRA) have been updated to follow the 2020 census tract lines which resulted in minor changes to some boundary conditions. They have also been extended into water areas to allow the assignment of CRAs to overwater housing and businesses. To exclude the water polygons from a map choose the filter, water=0.Community reporting areas (CRAs) are designed to address a gap that existed in city geography. The task of reporting citywide information at a "community-like level" across all departments was either not undertaken or it was handled in inconsistent ways across departments. The CRA geography provides a "common language" for geographic description of the city for reporting purposes. Therefore, this geography may be used by departments for geographic reporting and tracking purposes, as appropriate. The U.S. Census Bureau census tract geography was chosen as the basis of the CRA geography due to their stability through time and link to widely-used demographic data.The following criteria for a CRA geography were defined for this effort:no overlapping areascomplete coverage of the citysuitable scale to represent neighborhood areas/conditionsreasonably stable over timeconsistent with census geographyrelatively easy to use in a data contextfamiliar system of common place namesrespects neighborhood district geography to the extent possibleThe following existing geographies were reviewed during this effort:neighborhood planning areas (DON)neighborhood districts (DON/CNC/Neighborhood District Councils)city sectors/neighborhood plan implementation areas (DON)urban centers/urban villages (DPD)population sub-areas (DPD)Neighborhood Map Atlas (City Clerk)Census tract geographytopographyvarious other geographic information sources related to neighborhood areas and common place namesThis is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

Data from: American Community Survey, 5-year Series 2006-2010Community Reporting Area boundaries with American Community Survey data and attachments of census reports. Community Reporting Areas (CRAs) were established in 2004 as a standard, consistent, citywide geography for reporting purposes. There are 53 CRAs composed of from one to six census tracts.Neighborhood aggregations of American Community Survey tract-based data derived from the U.S. Census Bureau's demographic profiles (DP02-DP05). The geo service includes over 50 attributes of the most frequently requested data.Also includes custom reports in pdf format as attachments to each neighborhood.Please see the item page for the source map service for more information.When downloading the data, please select "GDB Download" under "Additional Resources" to preserve long field names and attachments. The associated file geodatabase contains a separate feature class for three levels of neighborhood geography - council districts, community reporting areas, and urban village demographic areas that includes these 50+ attributes.

Displacement risk indicator classifying community reporting areas according to apartment vacancy rates. Vacancy rates are calculated at the Community Reporting Area level, which are a combination of one or more census tracts. We visualize them as census tracts here, but columns should not be summed to make a total. We include both vacancy rates and change in year over year vacancy rates.Note: Vacancy rate calculations include market-rate and mixed-income multifamily apartment properties with 5 or more rental units in Seattle, excluding special types like student, senior, corporate or military housing.Source: Data from CoStar Group, www.costar.com, prepared by City of Seattle, Office of Planning and Community Development

The World Database on Protected Areas (WDPA) is the most comprehensive global database of marine and terrestrial protected areas, updated on a monthly basis, and is one of the key global biodiversity data sets being widely used by scientists, businesses, governments, International secretariats and others to inform planning, policy decisions and management.The WDPA is a joint project between UN Environment and the International Union for Conservation of Nature (IUCN). The compilation and management of the WDPA is carried out by UN Environment World Conservation Monitoring Centre (UNEP-WCMC), in collaboration with governments, non-governmental organisations, academia and industry. There are monthly updates of the data which are made available online through the Protected Planet website where the data is both viewable and downloadable.Data and information on the world's protected areas compiled in the WDPA are used for reporting to the Convention on Biological Diversity on progress towards reaching the Aichi Biodiversity Targets (particularly Target 11), to the UN to track progress towards the 2030 Sustainable Development Goals, to some of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) core indicators, and other international assessments and reports including the Global Biodiversity Outlook, as well as for the publication of the United Nations List of Protected Areas. Every two years, UNEP-WCMC releases the Protected Planet Report on the status of the world's protected areas and recommendations on how to meet international goals and targets.Many platforms are incorporating the WDPA to provide integrated information to diverse users, including businesses and governments, in a range of sectors including mining, oil and gas, and finance. For example, the WDPA is included in the Integrated Biodiversity Assessment Tool, an innovative decision support tool that gives users easy access to up-to-date information that allows them to identify biodiversity risks and opportunities within a project boundary.The reach of the WDPA is further enhanced in services developed by other parties, such as the Global Forest Watch and the Digital Observatory for Protected Areas, which provide decision makers with access to monitoring and alert systems that allow whole landscapes to be managed better. Together, these applications of the WDPA demonstrate the growing value and significance of the Protected Planet initiative.Community Protected Areas query:All of these expressions must be true:Status is 'Inscribed' orStatus is 'Established' orStatus is 'Designated'andGovernace Type is 'Local communities' orGovernace Type is 'Indigenous peoples'

Data from: American Community Survey, 5-year SeriesKing County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010 of over 50 attributes of the most requested data derived from the U.S. Census Bureau's demographic profiles (DP02-DP05). Also includes the most recent release annually with the vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, <a href='https://www.census.gov/programs-surveys/acs/news/data-releases/2023/release.html#5yr' style='font-family:inherit;' target='_blank' rel='nofollow ugc noopener noreferr

Table from the American Community Survey (ACS) 5-year series on disabilities and health insurance related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes C21007 Age by Veteran Status by Poverty Status in the Past 12 Months by Disability Status, B27010 Types of Health Insurance Coverage by Age, B22010 Receipt of Food Stamps/SNAP by Disability Status for Households. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.

In 2014 and 2015, The LA County Enterprise GIS team under the Geographic Information Officer worked with the Unincorporated Area Deputies and Field Deputies of each Board Office to establish names that reflect the desires of residents. CSAs differ from the more informal Community geographies because:They are focused on broad statistics and reporting, not mapping of communities.They represent board approved names assigned to Census block groups and city boundaries.They cover the entire unincorporated County (no gaps).There are not overlapping areas. Additionally, CSAs use the following naming conventions:All names are assumed to begin with Unincorporated (e.g. Unincorporated El Camino Village) which will not be part of the CSA Name (so the name of the Statistical Area would be El Camino Village).Names will not contain “Island.” Beginning each name with Unincorporated will distinguish an area from any surrounding cities. There may be one or more exceptions for certain small areas (e.g. Bandini Islands)A forward slash implies an undetermined boundary between two areas within a statistical geography (e.g. Westfield/Academy Hills or View Park/Windsor Hills)Certain established names may include hyphens (e.g. Florence-Firestone)Aliases may be defined in parentheses (e.g. Unincorporated Long Beach (Bonner/Carson Park))The original set of names were derived from community names used in the 2011 Redistricting process, chosen with the assistance of the Board of Supervisors.Updates: 2023 December: CSA data updated to include "Unincorporated Charter Oak" (south of 10 Freeway) into "Unincorporated Covina".2023 June: CSA data was updated to include "Kinneloa Mesa" community, which was a part of Unincorporated East Pasadena.2023 January: Updated layer schema to include feature type (“FEAT_TYPE”) field, which can be one of land, water, breakwater, or pier (consistent with the City Boundaries layer).2022 December: CSA data was updated to incorporate the “Tesoro Del Valle” annexation to the city of Santa Clarita. Unincorporated Valencia is now completely annexed to the City of Santa Clarita. In addition to land area, this data also includes other feature types such as piers, breakwater and water area. 2022 September: CSA data was updated to match with city boundaries along shoreline/coastal area and minor boundary adjusted in some other areas.

2020 census geography including tracts for the city of Seattle, King County, Washington. Excludes partial tracts with very small populations within the city limits along the southern border of the city.Includes assignment of Seattle Community Reporting Areas (CRA-53), Community Reporting Area Groups (neighborhood roll up-13), Council Districts (7-assigned to the tract with the majority of the population based on the distribution of the component census blocks), and Urban Village Demographic Areas (UVDA). UVDA assignments subject to change based on future planning areas.

Table from the American Community Survey (ACS) 5-year series on education enrollment and attainment related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B14007/B14002 School Enrollment, B15003 Educational Attainment. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B14007, B15003, B14002Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:</di

This infographic template provides an overview of a community’s demographics using a color palette of reds and yellows on a dark background. It contains demographic data provided by Esri and the U.S. Census Bureau, from the Esri Updated Demographics, American Community Survey, and Census 2010 datasets. Variables included in the template present information on population, occupation, housing, income, age, education, and commute times. This infographic may be useful for learning about basic demographic and work-related information in an area.

Table from the American Community Survey (ACS) 5-year series on languages spoken and English ability related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B16004 Age by Language Spoken at Home by Ability to Speak English, C16002 Household Language by Household Limited English-Speaking Status. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.

This map layer shows community planning areas in the City of Columbus. Community planning areas are used by City departments for a variety of planning and reporting purposes.

Table from the American Community Survey (ACS) B17004 of poverty status in the past 12 months of individuals by sex by work experience. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, 2023ACS Table(s): B17004Data downloaded from: Census Bureau's Expl

Table from the American Community Survey (ACS) 5-year series on transportation related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B08303 Travel Time to Work, B25044 Tenure by Vehicles Available, B08301 Means of Transportation to Work. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B08303, B25044, B08301Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Da

Table from the American Community Survey (ACS) 5-year series on poverty and employment status related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B23025 Employment Status for the Population 16 years and over, B23024 Poverty Status by Disability Status by Employment Status for the Population 20 to 64 years, B17010 Poverty Status of Families by Family Type by Presence of Related Children under 18 years, C17002 Ratio of Income to Poverty Level in the Past 12 Months. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B23025, B23024, B17010, C17002Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.<d

Table from the American Community Survey (ACS) 5-year series on race and ethnicity related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B03002 Hispanic or Latino Origin by Race, B02008-B02013 Race Alone or in Combination with One or More. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B03002, B02008, B02009, B02010, B02011, B02012, B02013Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews &

As part of the Detroit Community Health Assessment (CHA) process, the Health Department and community partners worked with the University of Michigan Detroit Metropolitan Area Communities Study (DMACS) team to conduct a representative citywide survey of 1,216 residents to gather relevant information about Detroiters’ experiences, perceptions, priorities and aspirations around community health. The survey was implemented in the summer of 2018 and the results of the survey are included here.

This layer shows health insurance coverage by type and by age group. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the count and percent uninsured. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B27010 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.