This dataset contains model-based census tract estimates. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. The dataset includes estimates for 40 measures: 12 for health outcomes, 7 for preventive services use, 4 for chronic disease-related health risk behaviors, 7 for disabilities, 3 for health status, and 7 for health-related social needs. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2020 population data, and American Community Survey 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

This dataset contains model-based place (incorporated and census designated places) level estimates for the PLACES project 2020 release. The PLACES project is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code tabulation Areas (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. The dataset includes estimates for 27 measures: 5 chronic disease-related unhealthy behaviors, 13 health outcomes, and 9 on use of preventive services. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population data, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS because the relevant questions are only asked every other year in the BRFSS. More information about the methodology can be found at www.cdc.gov/places.

This dataset contains model-based census tract-level estimates for the PLACES 2022 release. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. The dataset includes estimates for 29 measures: 13 for health outcomes, 9 for preventive services use, 4 for chronic disease-related health risk behaviors, and 3 for health status. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population data, and American Community Survey 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates for the PLACES 2022 release. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. The dataset includes estimates for 29 measures: 13 for health outcomes, 9 for preventive services use, 4 for chronic disease-related health risk behaviors, and 3 for health status. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population data, and American Community Survey 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

This dataset contains model-based census tract-level estimates for the PLACES 2021 release. PLACES is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. The dataset includes estimates for 29 measures: 4 chronic disease-related health risk behaviors, 13 health outcomes, 3 health status, and 9 on use of preventive services. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population data, and American Community Survey (ACS) 2015–019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS because the relevant questions are only asked every other year in the BRFSS. More information about the methodology can be found at www.cdc.gov/places.

A broad and generalized selection of 2012-2016 US Census Bureau 2016 5-year American Community Survey education data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico counties). The selection is not comprehensive, but allows a first-level characterization of educational attaiment by grade level and sex (for all persons 25 years and older), plus enrollment estimates at key educational levels (for the universe of all persons 3+ years old). The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users. The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. As in the decennial census, strict confidentiality laws protect all information that could be used to identify individuals or households.The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. The primary advantage of using multiyear estimates is the increased statistical reliability of the data for less populated areas and small population subgroups. 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. While each full Data Profile contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by New Mexico county boundaries.

See full Data Guide here. Drainage Basin Set:

Connecticut Drainage Basins is 1:24,000-scale, polygon and line feature data that define natural drainage areas in Connecticut. These are small basin areas that average approximately 1 square mile in size and make up, in order of increasing size, the larger local, subregional, regional, and major drainage basin areas. Connecticut Drainage Basins includes drainage areas for all Connecticut rivers, streams, brooks, lakes, reservoirs and ponds published on 1:24,000-scale 7.5 minute topographic quadrangle maps prepared by the USGS between 1969 and 1984. Data is compiled at 1:24,000 scale (1 inch = 2,000 feet). This information is not updated. Polygon and line features represent drainage basin areas and boundaries, respectively. Each basin area (polygon) feature is outlined by one or more major, regional, subregional, local, impoundment, or river reach boundary (line) feature. These data include 7,076 basin area (polygon) features and 20,945 basin boundary (line) features. Basin area (polygon) attributes include major, regional, subregional, local, (full) basin number, and feature size in acres and square miles. The full basin number (BASIN_NO) uniquely identifies individual basins and is up to 13 characters in length. There are 7,031 unique basin numbers. Examples include 6000-00-1+*, 4300-00-1+L1, and 6002-00-2-R1. The first digit (column 1) designates the major basin, the first two digits (columns 1-2) designate the regional basin, the first 4 digits (columns 1-4) designate the subregional basin, and the first seven digits (columns 1-7) designate the local basin. Note, there are slightly more basin polygon features (7,076) than unique basin numbers (7,031) primarily because a few water supply watershed boundaries split a basin into two polygon features at the location of a small dam or point of diversion along a stream. Basin boundary (line) attributes include a drainage divide type attribute (DIVIDE) used to cartographically represent the hierarchical drainage basin system. This divide type attribute is used to assign different line symbology to major, regional, subregional, local, stream reach, and lake impoundment drainage basin divides. For example, major basin drainage divides are more pronounced and shown with a wider line symbol than regional basin drainage divides. Connecticut Drainage Basins is the data source for other digital spatial data including the Connecticut Major Drainage Basins, Connecticut Regional Drainage Basins, Connecticut Subregional Drainage Basins, and Connectcut Local Drainage Basins. Purpose: The polygon features define the contributing drainage area for individual reservoirs, lakes, ponds and river and stream reaches in Connecticut. These are hydrologic land units where precipitation is collected. Rain falling in a basin may take two courses. It may both run over the land and quickly enter surface watercourses, or it may soak into the ground moving through the earth until it surfaces at a wetland or stream. In an undisturbed natural drainage basin, the surface and ground water arrive as precipitation and leave either by evaporation or as surface runoff at the basin's outlet. A basin is a self-contained hydrologic system, with a clearly defined water budget and cycle. The amount of water that flows into the basins equals the amount that leaves. A drainage divide is the topographic barrier along a ridge or line of hilltops separating adjacent drainage basins. For example, rain or snow melt draining down one side of a hill generally will flow into a different basin and stream than water draining down the other side of the hill. These hillsides are separated by a drainage divided that follows nearby hilltops and ridge lines. Use these basin data to identify where rainfall flows over land and downstream to a particular watercourse. Use these data to categorize and tabulate information according to drainage basin by identifying the basin number for individual reservoir, lake, pond, stream reach, or location of interest. Due to the hierarchical nature of the basin numbering system, a database that records the 13-digit basin number for individual geographic locations of interest will support tabulations by major, regional, subregional or local basin as well as document the unique 13-digit basin number. To identify either all upstream basins draining to a particular location or all downstream basins flowing from a particular location, refer to the Gazetteer of Drainage Basin Areas of Connecticut, Nosal, 1977, CT DEP Water Resources Bulletin 45, for the hydrologic sequence, headwater to outfall, of drainage basins available at http://cteco.uconn.edu/docs/wrb/wrb45_gazetteer_of_drainage_areas_of_connecticut.pdf Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.). Not intended for analysis with other digital data compiled at scales greater than or more detailed than 1:24,000 scale. Use these data with 1:24,000-scale hydrography data also available from the State of Connecticut, Department of Environmental Protection.

onnecticut Drainage Basins is 1:24,000-scale, polygon and line feature data that define natural drainage areas in Connecticut. These are small basin areas that average approximately 1 square mile in size and make up, in order of increasing size, the larger local, subregional, regional, and major drainage basin areas. Connecticut Drainage Basins includes drainage areas for all Connecticut rivers, streams, brooks, lakes, reservoirs and ponds published on 1:24,000-scale 7.5 minute topographic quadrangle maps prepared by the USGS between 1969 and 1984. Data is compiled at 1:24,000 scale (1 inch = 2,000 feet). This information is not updated. Polygon and line features represent drainage basin areas and boundaries, respectively. Each basin area (polygon) feature is outlined by one or more major, regional, subregional, local, impoundment, or river reach boundary (line) feature. These data include 7,076 basin area (polygon) features and 20,945 basin boundary (line) features. Basin area (polygon) attributes include major, regional, subregional, local, (full) basin number, and feature size in acres and square miles. The full basin number (BASIN_NO) uniquely identifies individual basins and is up to 13 characters in length. There are 7,031 unique basin numbers. Examples include 6000-00-1+*, 4300-00-1+L1, and 6002-00-2-R1. The first digit (column 1) designates the major basin, the first two digits (columns 1-2) designate the regional basin, the first 4 digits (columns 1-4) designate the subregional basin, and the first seven digits (columns 1-7) designate the local basin. Note, there are slightly more basin polygon features (7,076) than unique basin numbers (7,031) primarily because a few water supply watershed boundaries split a basin into two polygon features at the location of a small dam or point of diversion along a stream. Basin boundary (line) attributes include a drainage divide type attribute (DIVIDE) used to cartographically represent the hierarchical drainage basin system. This divide type attribute is used to assign different line symbology to major, regional, subregional, local, stream reach, and lake impoundment drainage basin divides. For example, major basin drainage divides are more pronounced and shown with a wider line symbol than regional basin drainage divides. Connecticut Drainage Basins is the data source for other digital spatial data including the Connecticut Major Drainage Basins, Connecticut Regional Drainage Basins, Connecticut Subregional Drainage Basins, and Connectcut Local Drainage Basins.

A broad and generalized selection of 2011-2015 US Census Bureau 2015 5-year American Community Survey housing data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico Census tracts). The selection is not comprehensive, but allows a first-level characterization of housing prices, years of construction, rental information, and occupancy versus vacancy. The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users.The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. While the ACS contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by Census tract boundaries in New Mexico. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. 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. State and county boundaries always are census tract boundaries in the standard census 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. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

Local Air Quality Management Areas (AQMA) in York. For further information on AQMAs please visit City of York Council's website. For more air quality related data please see the following datasets: • Air Quality Monitoring Stations Locations in York • York Air Quality Monitoring Stations Data • Diffusion Tubes (NO2) Locations in York • York Diffusion Tubes (NO2) Data *Please note that the data published within this dataset is a live API link to CYC's GIS server. Any changes made to the master copy of the data will be immediately reflected in the resources of this dataset.The date shown in the "Last Updated" field of each GIS resource reflects when the data was first published.

This report looks at people's views of their communities, their neighbourhoods, and their local areas using findings from the Citizenship Survey. This report has been re-packaged from previous years, and includes similar topic areas to the Community Cohesion Topic Report published in previous years.

Source agency: Communities and Local Government

Designation: National Statistics

Language: English

Alternative title: Citizenship Survey: Community Spirit Topic Report

A broad and generalized selection of 2014-2018 US Census Bureau 2018 5-year American Community Survey race, ethnicity and citizenship data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico Census tracts). The selection is not comprehensive, but allows a first-level characterization of the household income, median household income by race and by age group, Social Security income, the GINI Index, per capita income, median family income, and median household earnings by age, and by education level, in New Mexico. The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users.The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. While the ACS contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by Census tract boundaries in New Mexico. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. 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. State and county boundaries always are census tract boundaries in the standard census 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. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area. NOTE: A '-666666666' entry indicates that 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 boundaries are established from either Land Claims Final Agreement, Self Government Agreement, Memorandum of Understanding, Local Advisory Area, or from a signed document between Yukon Government and First Nation. An Order in Council is prepared and the new boundary comes into effect. Older LAP's and Community Plans were approved by YG Minister and Cabinet as a policy document. Newer plans are approved in the same manner which also include First Nation resolution by Chief and Council Some of these contain a Future Land Use Plan or Land Use Plan with area designations. Distributed from GeoYukon by the Government of Yukon . Discover more digital map data and interactive maps from Yukon's digital map data collection. For more information: geomatics.help@yukon.ca

The concepts and definitions underlying LAUS data come from the Current Population Survey (CPS), the household survey that is the source of the national unemployment rate. State monthly model-based estimates are controlled in "real time" to sum to national monthly employment and unemployment estimates from the CPS. These models combine current and historical data from the CPS, the Current Employment Statistics (CES) survey, and state unemployment insurance (UI) systems. Estimates for seven large areas and their respective balances of state also are model-based. Estimates for counties are produced through a building-block approach known as the "Handbook method." This procedure also uses data from several sources, including the CPS, the CES program, state UI systems, and the Census Bureau's American Community Survey (ACS), to create estimates that are adjusted to the statewide measures of employment and unemployment. Estimates for cities are prepared using disaggregation techniques based on inputs from the ACS, annual population estimates, and current UI data.

This is the complete dataset for the 500 Cities project 2016 release. This dataset includes 2013, 2014 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2013, 2014), Census Bureau 2010 census population data, and American Community Survey (ACS) 2009-2013, 2010-2014 estimates. More information about the methodology can be found at www.cdc.gov/500cities. Note: During the process of uploading the 2015 estimates, CDC found a data discrepancy in the published 500 Cities data for the 2014 city-level obesity crude prevalence estimates caused when reformatting the SAS data file to the open data format. . The small area estimation model and code were correct. This data discrepancy only affected the 2014 city-level obesity crude prevalence estimates on the Socrata open data file, the GIS-friendly data file, and the 500 Cities online application. The other obesity estimates (city-level age-adjusted and tract-level) and the Mapbooks were not affected. No other measures were affected. The correct estimates are update in this dataset on October 25, 2017.

These are the 3 Local Area Team (LAT) profiles containing information up to March 2020.

A Local Area Team (LAT) is a multi-agency team covering one of three defined geographical areas of York which are a key part of York’s early help response to working with children, young people and families.

The profiles are created annually by bringing various existing ward profiles in to a single dataset.

For further information about the LATs please visit the YorOK website.

Boundaries of various types of public agencies with responsibilities that include in part or primarily flood control, system maintenance, and improvement. In California, there are a variety of political entites that are granted self-taxation powers under various California codes in order to perform the basic goal of flood management within an area. This dataset compiles many of the various datasets together to provide the information in one location. It also includes districts that are no longer active political/management entities for archival or historical purposes. The primary type of flood agency in California are known as reclamation districts, and so represent the majority of the records in this database. The quality of the boundary accuracy is highly variable, due to a variety of reasons, including the fact that the original legal boundaries are frequently tied to Swamp Land Survey boundaries that themselves are poorly located by modern mapping standards. This set of boundary delineations represents the latest in a series of nearly 20 significant revisions primarily by DWR Delta Levees Program between 2000-2017 to a dataset first produced by Office of Emergency Services during the 1997 floods. The accuracy and completeness of the data are therefore higher in the Delta than elsewhere. The Division of Flood Management then stored the boundaries in their levee geodatabase that feeds the web mapping application known as FERIX. To produce this final dataset, in 2018 the Division of Engineering Geodetic Branch merged the data used by FERIX, along with other datasets used by the Delta Levees Program, and normalized the attribute table.

This is the complete dataset for the 500 Cities project 2017 release. This dataset includes 2015, 2014 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2015, 2014), Census Bureau 2010 census population data, and American Community Survey (ACS) 2011-2015, 2010-2014 estimates. Because some questions are only asked every other year in the BRFSS, there are 7 measures from the 2014 BRFSS that are the same in the 2017 release as the previous 2016 release. More information about the methodology can be found at www.cdc.gov/500cities.

This data is provided by compiling the notice information of each local government regarding the lifting and change of development restriction areas, including the notice management number, notice agency code, notice number, notice date, title, notice content, and region code. This data is constructed by procuring the notice text on the lifting and change of development restriction areas. The notice text is constantly procured and managed from related sites such as the Electronic Official Gazette registered daily (based on weekdays) and Land Information that manages notice information. The procured data is assigned a region code by metropolitan city/province and city/county/district, and is computerized by item such as notice management number, agency code, notice number, notice date, title, and content, and then collated and provided so that it can be registered and searched in the development restriction area management information system. The notice information is constructed in the form of attribute data, and is data linked to the graphic data (shp) displayed in the system.