Assists investigators in determining whether persons in their studies have died and, if so, provide the names of the states in which those deaths occurred, the dates of death, and the corresponding death certificate numbers. Investigators can then make arrangements with the appropriate state offices to obtain copies of death certificates or specific statistical information such as manner of death or educational level. Cause of death codes may also be obtained using the NDI Plus service.
Records from 1979 through 2011 are currently available and contain a standard set of identifying information on each death. Death records are added to the NDI file annually, approximately 12 months after the end of a particular calendar year. 2012 should be available summer 2014. Early Release Program for 2013 is now available.
The NDI service is available to investigators solely for statistical purposes in medical and health research. The service is not accessible to organizations or the general public for legal, administrative, or genealogy purposes.' description_attribution: http://www.cdc.gov/nchs/ndi.htm doi: ~ end_time: 2010-12-31T19:00:00 href: https://data.globalchange.gov/dataset/cdc-national-death-index.yaml identifier: cdc-national-death-index lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: National Death Index native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1978-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-national-death-index url: http://www.cdc.gov/nchs/ndi/index.htm variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The National Environmental Public Health Tracking Network is a system of integrated health, exposure, and hazard information and data from a variety of national, state, and city sources. On the Tracking Network, you can explore information and view maps, tables, and charts about health and environment across the country.' description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdc-national-environmental-public-health-tracking-network-tracking-network.yaml identifier: cdc-national-environmental-public-health-tracking-network-tracking-network lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: CDC National Environmental Public Health Tracking Network (Tracking Network) native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-national-environmental-public-health-tracking-network-tracking-network url: http://www.cdc.gov/ephtracking/ variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: Interactive online tool for creating and manipulating tables based on birth and perinatal (fetal and infant death) data files. Tabulated data can be graphed or mapped within VitalStats or exported to Excel for further analysis. description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdc-vitalstats.yaml identifier: cdc-vitalstats lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: VitalStats native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-vitalstats url: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The United States Cancer Statistics (USCS) online databases in WONDER provide cancer incidence and mortality data for the United States for the years since 1999, by year, state and metropolitan areas (MSA), age group, race, ethnicity, gender, childhood cancer classifications and cancer site. Report case counts, deaths, crude and age-adjusted incidence and death rates, and 95% confidence intervals for rates. The USCS data are the official federal statistics on cancer incidence from registries having high-quality data and cancer mortality statistics for 50 states and the District of Columbia. USCS are produced by the Centers for Disease Control and Prevention (CDC) and the National Cancer Institute (NCI), in collaboration with the North American Association of Central Cancer Registries (NAACCR). Mortality data are provided by the Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), National Vital Statistics System (NVSS).' description_attribution: http://wonder.cdc.gov/cancer.html doi: ~ end_time: 2006-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-cancer-statistics.yaml identifier: cdc-wonder-cancer-statistics lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Cancer Statistics' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1998-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-cancer-statistics url: http://wonder.cdc.gov/cancer.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The CDC WONDER Mortality - Underlying Cause of Death online database is a county-level national mortality and population database spanning the years since 1979 -2008. The number of deaths, crude death rates, age-adjusted death rates, standard errors and 95% confidence intervals for death rates can be obtained by place of residence (total U.S., Census region, Census division, state, and county), age group (including infant age groups), race (years 1979-1998: White, Black, and Other; years 1999-2008: American Indian or Alaska Native, Asian or Pacific Islander, Black or African American, and White), Hispanic origin (years 1979-1998: not available; years 1999-present: Hispanic or Latino, not Hispanic or Latino, Not Stated), gender, year of death, and underlying cause of death (years 1979-1998: 4-digit ICD-9 code and 72 cause-of-death recode; years 1999-present: 4-digit ICD-10 codes and 113 cause-of-death recode, as well as the Injury Mortality matrix classification for Intent and Mechanism), and urbanization level of residence (2006 NCHS urban-rural classification scheme for counties). The Compressed Mortality data are produced by the National Center for Health Statistics.' description_attribution: http://wonder.cdc.gov/wonder/help/cmf.html doi: ~ end_time: 2009-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-compressed-mortality-underlying-cause-death.yaml identifier: cdc-wonder-compressed-mortality-underlying-cause-death lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Compressed Mortality - Underlying Cause of Death' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1967-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-compressed-mortality-underlying-cause-death url: http://wonder.cdc.gov/mortSQL.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The Daily Air Temperature and Heat Index data available on CDC WONDER are county-level daily average air temperatures and heat index measures spanning the years 1979-2010. Temperature data are available in Fahrenheit or Celsius scales. Reported measures are the average temperature, number of observations, and range for the daily maximum and minimum air temperatures, and also percent coverage for the daily maximum heat index. Data are available by place (combined 48 contiguous states, region, division, state, county), time (year, month, day) and specified maximum and minimum air temperature, and heat index value. The data are derived from the North America Land Data Assimilation System (NLDAS) through NLDAS Phase 2, a collaboration project among several groups: the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC), the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), Princeton University, the National Weather Service (NWS) Office of Hydrological Development (OHD), the University of Washington, and the NCEP Climate Prediction Center (CPC). In a study funded by the NASA Applied Sciences Program/Public Health Program, scientists at NASA Marshall Space Flight Center/ Universities Space Research Association developed the analysis to produce the data available on CDC WONDER.' description_attribution: http://wonder.cdc.gov/wonder/help/nldas.html doi: ~ end_time: 2010-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-daily-air-temperatures-and-heat-index.yaml identifier: cdc-wonder-daily-air-temperatures-and-heat-index lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Daily Air Temperatures and Heat Index' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1978-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-daily-air-temperatures-and-heat-index url: http://wonder.cdc.gov/nasa-nldas.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The Detailed Mortality - Underlying Cause of Death data on CDC WONDER are county-level national mortality and population data spanning the years 1999-2009. Data are based on death certificates for U.S. residents. Each death certificate contains a single underlying cause of death, and demographic data. The number of deaths, crude death rates, age-adjusted death rates, standard errors and 95% confidence intervals for death rates can be obtained by place of residence (total U.S., region, state, and county), age group (including infants and single-year-of-age cohorts), race (4 groups), Hispanic ethnicity, gender, year of death, and cause-of-death (4-digit ICD-10 code or group of codes, injury intent and mechanism categories, or drug and alcohol related causes), year, month and week day of death, place of death and whether an autopsy was performed. The data are produced by the National Center for Health Statistics.' description_attribution: http://wonder.cdc.gov/wonder/help/ucd.html doi: ~ end_time: 2009-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-detailed-mortality-underlying-cause-death.yaml identifier: cdc-wonder-detailed-mortality-underlying-cause-death lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Detailed Mortality - Underlying Cause of Death' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1998-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-detailed-mortality-underlying-cause-death url: http://wonder.cdc.gov/ucd-icd10.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "The Mortality - Infant Deaths (from Linked Birth / Infant Death Records) online databases on CDC WONDER provide counts and rates for deaths of children under 1 year of age, occuring within the United States to U.S. residents. Information from death certificates has been linked to corresponding birth certificates. Data are available by county of mother's residence, child's age, underlying cause of death, gender, birth weight, birth plurality, birth order, gestational age at birth, period of prenatal care, maternal race and ethnicity, maternal age, maternal education and marital status. Data are available since 1995. The data are produced by the National Center for Health Statistics." description_attribution: http://wonder.cdc.gov/wonder/help/lbd.html doi: ~ end_time: 2005-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-mortality-infant-deaths.yaml identifier: cdc-wonder-mortality-infant-deaths lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Mortality - Infant Deaths' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1994-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-mortality-infant-deaths url: http://wonder.cdc.gov/lbd.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The Mortality - Multiple Cause of Death data on CDC WONDER are county-level national mortality and population data spanning the years 1999-2009. Data are based on death certificates for U.S. residents. Each death certificate contains a single underlying cause of death, up to twenty additional multiple causes (Boolean set analysis), and demographic data. The number of deaths, crude death rates, age-adjusted death rates, standard errors and 95% confidence intervals for death rates can be obtained by place of residence (total U.S., region, state, and county), age group (including infants and single-year-of-age cohorts), race (4 groups), Hispanic ethnicity, gender, year of death, and cause-of-death (4-digit ICD-10 code or group of codes, injury intent and mechanism categories, or drug and alcohol related causes), year, month and week day of death, place of death and whether an autopsy was performed. The data are produced by the National Center for Health Statistics.' description_attribution: http://wonder.cdc.gov/wonder/help/mcd.html doi: ~ end_time: 2009-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-mortality-multiple-cause-death.yaml identifier: cdc-wonder-mortality-multiple-cause-death lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Mortality - Multiple Cause of Death' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1998-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-mortality-multiple-cause-death url: http://wonder.cdc.gov/mcd.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The CDC WONDER Mortality - Underlying Cause of Death online database is a county-level national mortality and population database spanning the years since 1979. Data are updated annually. The number of deaths, crude death rates, age-adjusted death rates, standard errors and confidence intervals for death rates can be obtained by place of residence (total U.S., Census region, Census division, state, and county), age group (including infant age groups), race (years 1979-1998: White, Black, and Other; years 1999-present: American Indian or Alaska Native, Asian or Pacific Islander, Black or African American, and White), Hispanic origin (years 1979-1998: not available; years 1999-present: Hispanic or Latino, not Hispanic or Latino, Not Stated), gender, year of death, and underlying cause ofdeath (years 1979-1998: 4-digit ICD-9 code and 72 cause-of-death recode; years 1999-present: 4-digit ICD-10 codes and 113 cause-of-death recode, as well as the Injury Mortality matrix classification for Intent and Mechanism), and urbanization level of residence (2006 NCHS urban-rural classification scheme for counties). The data are produced by the National Center for Health Statistics.' description_attribution: http://wonder.cdc.gov/wonder/help/cmf.html doi: ~ end_time: 2007-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-mortality-underlying-cause-death.yaml identifier: cdc-wonder-mortality-underlying-cause-death lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Mortality - Underlying Cause of Death' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1998-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-mortality-underlying-cause-death url: http://wonder.cdc.gov/mortSQL.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The Population - Bridged-Race July 1st Estimates online databases report bridged-race population estimates of the July 1st resident population of the United States, based on Census 2000 counts, for use in calculating vital rates. These estimates result from "bridging" the 31 race categories used in Census 2000, as specified in the 1997 Office of Management and Budget (OMB) standards for the collection of data on race and ethnicity, to the four race categories specified under the 1977 standards (Asian or Pacific Islander, Black or African American, American Indian or Alaska Native, White). Many data systems, such as vital statistics, are continuing to use the 1977 OMB standards during the transition to full implementation of the 1997 OMB standards. Postcensal estimates are available for year 2000 - 2009; intercensal estimates are available for the years 1990-1999. Obtain population counts by Year, State, County, Race (4-categories), Ethnicity, Sex and Age (1-year or 5-year groups). The data are released by the National Center for Health Statistics.' description_attribution: http://wonder.cdc.gov/wonder/help/bridged-race.html doi: ~ end_time: 2009-12-30T19:00:00 href: https://data.globalchange.gov/dataset/cdc-wonder-population-bridged-race-july-1st-estimates.yaml identifier: cdc-wonder-population-bridged-race-july-1st-estimates lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDC WONDER: Population - Bridged-Race July 1st Estimates' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1989-12-31T19:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdc-wonder-population-bridged-race-july-1st-estimates url: http://wonder.cdc.gov/bridged-race-population.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: ~ description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdec-water-storage-levels-shasta-dam-reservoir.yaml identifier: cdec-water-storage-levels-shasta-dam-reservoir lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Storage Levels in the Shasta Dam Reservoir native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdec-water-storage-levels-shasta-dam-reservoir url: http://cdec.water.ca.gov/resapp/ResDetail?resid=SHA variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: 'Houghton, R.A. 2008. Carbon Flux to the Atmosphere from Land-Use Changes: 1850-2005. In TRENDS: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A.' data_qualifier: ~ description: 'The methods and data sources used to derive this time series of flux estimates are described in Houghton (1999, 2003), Houghton and Hackler (1995), and Houghton et al. (1983). In summary, this database provides estimates of regional and global net carbon fluxes, on a year-by-year basis from 1850 through 2005, resulting from changes in land use (such as harvesting of forest products and clearing for agriculture), taking into account not only the initial removal and oxidation of the carbon in the vegetation, but also subsequent regrowth and changes in soil carbon. The net flux of carbon to the atmosphere from changes in land use from 1850 to 2005 was modeled as a function of documented land-use change and changes in aboveground and belowground carbon following changes in land use. Annual rates of land-use change (for example, conversion of forest to cropland) and per hectare changes in carbon stocks (vegetation, slash, wood products, and soils) as a result of changes in land use were used in a carbon accounting model to calculate the annual net flux of carbon between land and the atmosphere that results from land management. The net flux includes both emissions of carbon from deforestation and sinks of carbon in forests recovering from harvests or agricultural abandonment. Changes in land use included the expansion and contraction of croplands and pastures, plantation establishment, and harvest of wood. Carbon budgeting included only those ecosystems converted to other uses or harvested; unmanaged ecosystems were not considered. Further, rates of growth and decomposition were ecosystem specific and did not vary in response to variations in climatic factors, CO2 concentrations, or other elements of environmental change. The analyses were spatially aggregated. Two to six types of ecosystems, with average carbon stocks, were considered for each of ten world regions.' description_attribution: https://cdiac.ess-dive.lbl.gov/trends/landuse/houghton/houghton.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdiac-carbon-flux-atmosphere-land-use-changes-1850-2005.yaml identifier: cdiac-carbon-flux-atmosphere-land-use-changes-1850-2005 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Carbon flux to the atmosphere from land-use changes 1850-2005 native_id: ~ processing_level: ~ publication_year: 2008 release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/cdiac-carbon-flux-atmosphere-land-use-changes-1850-2005 url: https://cdiac.ess-dive.lbl.gov/trends/landuse/houghton/1850-2005.txt variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: 'Marland, G., T.A. Boden, and R.J. Andres. 2008. Global, Regional, and National Fossil Fuel CO2 Emissions. In Trends: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A.' data_qualifier: ~ description: "Publications containing historical energy statistics make it possible to estimate fossil fuel CO2 emissions back to 1751. Etemad et al. (1991) published a summary compilation that tabulates coal, brown coal, peat, and crude oil production by nation and year. Footnotes in the Etemad et al.(1991) publication extend the energy statistics time series back to 1751. Summary compilations of fossil fuel trade were published by Mitchell (1983, 1992, 1993, 1995). Mitchell's work tabulates solid and liquid fuel imports and exports by nation and year. These pre-1950 production and trade data were digitized and CO2 emission calculations were made following the procedures discussed in Marland and Rotty (1984) and Boden et al. (1995). Further details on the contents and processing of the historical energy statistics are provided in Andres et al. (1999). The 1950 to present CO2 emission estimates are derived primarily from energy statistics published by the United Nations (2006), using the methods of Marland and Rotty (1984). The energy statistics were compiled primarily from annual questionnaires distributed by the U.N. Statistical Office and supplemented by official national statistical publications. As stated in the introduction of the Statistical Yearbook, \"in a few cases, official sources are supplemented by other sources and estimates, where these have been subjected to professional scrutiny and debate and are consistent with other independent sources.\" Data from the U.S. Department of Interior's Geological Survey (USGS 2007) were used to estimate CO2 emitted during cement production. Values for emissions from gas flaring were derived primarily from U.N. data but were supplemented with data from the U.S. Department of Energy's Energy Information Administration (1994), Rotty (1974), and data provided by G. Marland. Greater details about these methods are provided in Marland and Rotty (1984), Boden et al. (1995), and Andres et al. (1999)." description_attribution: https://cdiac.ess-dive.lbl.gov/trends/emis/overview.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cdiac-global-regional-national-fossil-fuel-co2-emissions.yaml identifier: cdiac-global-regional-national-fossil-fuel-co2-emissions lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'CDIAC Global, Regional, and National Fossil-Fuel CO2 Emissions' native_id: ~ processing_level: ~ publication_year: 2008 release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1751-01-01/2005-12-31 temporal_resolution: ~ type: ~ uri: /dataset/cdiac-global-regional-national-fossil-fuel-co2-emissions url: https://cdiac.ess-dive.lbl.gov/trends/emis/overview.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: '2010 Census Summary File 1 [name of state1 or United States]/prepared by the U.S. Census Bureau, 2011. 2010 Census Summary File 1 Urban/Rural Update [name of state1 or United States]/prepared by the U.S. Census Bureau, 2012' data_qualifier: ~ description: 'Summary File 1 (SF 1) contains the data compiled from the questions asked of all people and about every housing unit. Population items include sex, age, race, Hispanic or Latino origin, household relationship, household type, household size, family type, family size, and group quarters. Housing items include occupancy status, vacancy status, and tenure (whether a housing unit is owner-occupied or renter-occupied). There are 177 population tables (identified with a ‘‘P’’) and 58 housing tables (identified with an ‘‘H’’) shown down to the block level; 82 population tables (identified with a ‘‘PCT’’) and 4 housing tables (identified with an “HCT”) shown down to the census tract level; and 10 population tables (identified with a “PCO”) shown down to the county level, for a total of 331 tables. The SF 1 Urban/Rural Update added 2 PCT tables, increasing the total number to 333 tables. There are 14 population tables and 4 housing tables shown down to the block level and 5 population tables shown down to the census tract level that are repeated by the major race and Hispanic or Latino groups. SF 1 includes population and housing characteristics for the total population, population totals for an extensive list of race (American Indian and Alaska Native tribes, Asian, and Native Hawaiian and Other Pacific Islander) and Hispanic or Latino groups, and population and housing characteristics for a limited list of race and Hispanic or Latino groups. Population and housing items may be cross-tabulated. Selected aggregates and medians also are provided. A complete listing of subjects in this file is found in the “Subject Locator” chapter' description_attribution: https://www.census.gov/data/datasets/2010/dec/summary-file-1.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-2010-summary-file-1-2011.yaml identifier: census-2010-summary-file-1-2011 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'U.S. Census 2010 Census Summary File 1 - 2011' native_id: ~ processing_level: ~ publication_year: 2011 release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-2010-summary-file-1-2011 url: https://www.census.gov/prod/cen2010/doc/sf1.pdf variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "The 2014 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Alaska Native Regional Corporations (ANRCs) were created pursuant to the Alaska Native Claims Settlement Act (ANCSA), which is federal legislation (Pub. L. 92-203, 85 Stat. 688 (1971); 43 U.S.C. 1602 et seq. (2000)) enacted in 1971, as a \"Regional Corporation\" and organized under the laws of the State of Alaska to conduct both the for-profit and non-profit affairs of Alaska Natives within a defined region of Alaska. For the Census Bureau, ANRCs are considered legal geographic entities. Twelve ANRCs cover the entire state of Alaska except for the area within the Annette Island Reserve (a federally recognized American Indian reservation under the governmental authority of the Metlakatla Indian Community). A thirteenth ANRC represents Alaska Natives who do not live in Alaska and do not identify with any of the twelve corporations. The Census Bureau does not provide data for this thirteenth ANRC because it has no defined geographic extent and thus it does not appear in the Cartographic Boundary Files. The Census Bureau offers representatives of the twelve non-profit ANRCs in Alaska the opportunity to review and update the ANRC boundaries before each decennial census." description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-2014-cartographic-boundary-file-state-alaska-native-regional-corporation-alaska-1-500000.yaml identifier: census-2014-cartographic-boundary-file-state-alaska-native-regional-corporation-alaska-1-500000 lat_max: 71.365162 lat_min: 51.214183 lon_max: 179.77847 lon_min: -179.148909 name: '2014 Cartographic Boundary File, State-Alaska Native Regional Corporation for Alaska, 1:500,000' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-2014-cartographic-boundary-file-state-alaska-native-regional-corporation-alaska-1-500000 url: http://www2.census.gov/geo/tiger/GENZ2014/shp/cb_2014_02_anrc_500k.zip variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The cartographic boundary files are simplified representations of selected geographic areas from the Census Bureau’s MAF/TIGER geographic database. These boundary files are specifically designed for small scale thematic mapping. Generalized boundary files are clipped to a simplified version of the U.S. outline. As a result, some off-shore areas may be excluded from the generalized files.' description_attribution: https://www.census.gov/geo/maps-data/data/cbf/cbf_counties.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-cartographic-boundary-shapefiles-counties.yaml identifier: census-cartographic-boundary-shapefiles-counties lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'U.S. Census 2010 Cartographic Boundary Shapefiles - Counties' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-cartographic-boundary-shapefiles-counties url: https://www.census.gov/cgi-bin/geo/shapefiles/index.php variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The cartographic boundary files are simplified representations of selected geographic areas from the Census Bureau’s MAF/TIGER geographic database. These boundary files are specifically designed for small scale thematic mapping. Generalized boundary files are clipped to a simplified version of the U.S. outline. As a result, some off-shore areas may be excluded from the generalized files.' description_attribution: https://www.census.gov/geo/maps-data/data/cbf/cbf_state.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-cartographic-boundary-shapefiles-states.yaml identifier: census-cartographic-boundary-shapefiles-states lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'U.S. Census Bureau Cartographic Boundary Shapefiles - States' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-cartographic-boundary-shapefiles-states url: https://www.census.gov/cgi-bin/geo/shapefiles/index.php variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The Commodity Flow Survey provides information on commodities shipped, their value, weight, and mode of transportation, as well as the origin and destination of shipments of commodities from manufacturing, mining, wholesale, and selected retail and services establishments. It is undertaken through a partnership between the Bureau of the Census, U.S. Department of Commerce, and the Bureau of Transportation Statistics, Research and Innovative Technology Administration.' description_attribution: http://www.census.gov/econ/cfs/definitions.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-commodity-flow-survey.yaml identifier: census-commodity-flow-survey lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Commodity Flow Survey native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-commodity-flow-survey url: https://www.census.gov/programs-surveys/cfs.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: This layer represents locations of American Indian reservations in Alaska. description_attribution: https://edg.epa.gov/metadata/catalog/search/resource/details.page?uuid=%7BE37B0B2C-EB0B-436C-B993-C18D8895E522%7D doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-epa-tribal-areas-3-of-4-alaska-reservations.yaml identifier: census-epa-tribal-areas-3-of-4-alaska-reservations lat_max: 55.300967 lat_min: 54.985892 lon_max: -131.293888 lon_min: -131.667861 name: 'EPA Tribal Areas (3 of 4): Alaska Reservations' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-epa-tribal-areas-3-of-4-alaska-reservations url: https://edg.epa.gov/data/Public/OEI/OIAA/Tribes/EPAtribes.zip variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'Each year, the United States Census Bureau produces and publishes estimates of the population for the nation, states, counties, state/county equivalents, and Puerto Rico. 1 We estimate the resident population for each year since the most recent decennial census by using measures of population change. The resident population includes all people currently residing in the United States. With each annual release of population estimates, the Population Estimates program revises and updates the entire time series of estimates from April 1, 2010 to July 1 of the current year, which we refer to as the vintage year. We use the term “vintage” to denote an entire time series created with a consistent population starting point and methodology. The release of a new vintage of estimates supersedes any previous series and incorporates the most up-to-date input data and methodological improvements.' description_attribution: https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2010-2017/2017-natstcopr-meth.pdf?# doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-metropolitan-micropolitan-statistical-areas-population-totals-2010-2017.yaml identifier: census-metropolitan-micropolitan-statistical-areas-population-totals-2010-2017 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'U.S. Census Metropolitan and Micropolitan Statistical Areas Population Totals: 2010-2017' native_id: ~ processing_level: ~ publication_year: 2017 release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-metropolitan-micropolitan-statistical-areas-population-totals-2010-2017 url: https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "Census population estimates by year\r\n\r\nEach year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census and produce a time series of estimates of population, demographic components of change, and housing units." description_attribution: http://www.census.gov/popest/data/datasets.html doi: ~ end_time: 2014-07-01T23:59:59 href: https://data.globalchange.gov/dataset/census-population-estimates.yaml identifier: census-population-estimates lat_max: 71.32 lat_min: 18.91 lon_max: -66.57 lon_min: -160.16 name: Annual Estimates of the Resident Population for the United States native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1900-07-01T00:00:01 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-population-estimates url: https://factfinder.census.gov/faces/nav/jsf/pages/searchresults.xhtml?refresh=t variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'First published in 1878, the Statistical Abstract serves as the official federal summary of statistics and provides over 1,400 tables of benchmark measures on the demographic, housing, social, political, and economic condition of the United States.' description_attribution: http://www.census.gov/library/publications/time-series/statistical_abstracts.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-statistical-abstract.yaml identifier: census-statistical-abstract lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Statistical Abstract of the United States native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-statistical-abstract url: http://www.census.gov/library/publications/time-series/statistical_abstracts.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "The American Indian/Alaska Native/Native Hawaiian (AIANNH) Areas Shapefile includes the following legal entities: federally recognized American Indian reservations and off-reservation trust land areas, state-recognized American Indian reservations, and Hawaiian home lands (HHLs). The statistical entities included are Alaska Native village statistical areas (ANVSAs), Oklahoma tribal statistical areas (OTSAs), tribal designated statistical areas (TDSAs), and state designated tribal statistical areas (SDTSAs). Joint use areas are also included in this shapefile refer to areas that are administered jointly and/or claimed by two or more American Indian tribes. The Census Bureau designates both legal and statistical joint use areas as unique geographic entities for the purpose of presenting statistical data. Note that tribal subdivisions and Alaska Native Regional Corporations (ANRCs) are additional types of American Indian/Alaska Native areas stored by the Census Bureau, but are displayed in separate shapefiles because of how they fall within the Census Bureau's geographic hierarchy. The State of Hawaii's Office of Hawaiian Home Lands provides the legal boundaries for the HHLs. The boundaries for ANVSAs, OTSAs, and TDSAs were delineated for the 2010 Census through the Tribal Statistical Areas Program (TSAP) by participants from the federally recognized tribal governments. The Bureau of Indian Affairs (BIA) within the U.S. Department of the Interior (DOI) provides the list of federally recognized tribes and only provides legal boundary information when the tribes need supporting records, if a boundary is based on treaty or another document that is historical or open to legal interpretation, or when another tribal, state, or local government challenges the depiction of a reservation or off-reservation trust land. The boundaries for federally recognized American Indian reservations and off-reservation trust lands are as of January 1, 2013, as reported by the federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries for state-recognized American Indian reservations and for SDTSAs were delineated by a state governor-appointed liaisons for the 2010 Census through the State American Indian Reservation Program and TSAP respectively." description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-tiger-line-shapefile-2014-series-information-file-for-the-current-american-indian-ala.yaml identifier: census-tiger-line-shapefile-2014-series-information-file-for-the-current-american-indian-ala lat_max: 71.441059 lat_min: -14.601813 lon_max: 179.859681 lon_min: -179.231086 name: 'TIGER/Line Shapefile, 2014, Series Information File for the Current American Indian/Alaska Native/Native Hawaiian Areas (AIANNH) National Shapefile' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-tiger-line-shapefile-2014-series-information-file-for-the-current-american-indian-ala url: http://www2.census.gov/geo/tiger/TIGER2014/AIANNH variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "Alaska Native Regional Corporations (ANRCs) were created pursuant to the Alaska Native Claims Settlement Act (ANCSA), which is federal legislation Pub. L. 92-203, 85 Stat. 688 (1971); 43 U.S.C. 1602 et seq. (2000)) enacted in 1971, as a 'Regional Corporation' and organized under the laws of the State of Alaska as \"Regional Corporations\" to conduct both the for profit and non profit affairs of Alaska Natives within defined regions of Alaska. Twelve ANRCs cover the entire State of Alaska except for the area within the Annette Island Reserve (an American Indian Reservation under the governmental authority of the Metlakatla Indian Community). There is a thirteenth ANRC that represents the eligible Alaska Natives living outside of Alaska that are not members of any of the twelve ANRCs within the State of Alaska. Because it has no defined geographic extent, this thirteenth ANRC does not appear in the TIGER/Line Shapefiles and the Census Bureau does not provide data for it. The Census Bureau offers representatives of the twelve ANRCs the opportunity to review and update the ANRC boundaries. ANRCs are represented by a 5 character FIPS code unique within Alaska and a nationally unique 8 character National Standard (GNIS) code." description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-tiger-line-shapefile-2014-series-information-for-the-current-alaska-native-regional-corporation844f0.yaml identifier: census-tiger-line-shapefile-2014-series-information-for-the-current-alaska-native-regional-corporation844f0 lat_max: 71.441059 lat_min: -14.601813 lon_max: 179.859681 lon_min: -179.231086 name: 'TIGER/Line Shapefile, 2014, Series Information for the Current Alaska Native Regional Corporation (ANRC) State-based Shapefiles' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-tiger-line-shapefile-2014-series-information-for-the-current-alaska-native-regional-corporation844f0 url: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2014.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "American Indian tribal subdivisions are administrative subdivisions of federally recognized American Indian reservations/off-reservation trust lands or Oklahoma tribal statistical areas (OTSAs). These entities are internal units of self-government and/or administration that serve social, cultural, and/or economic purposes for the American Indian tribe or tribes on the reservations/off-reservation trust lands or OTSAs. The Census Bureau obtains the boundary and attribute information for tribal subdivisions on federally recognized American Indian reservations and off-reservation trust lands from federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey (BAS) For the 2010 Census, the boundaries for tribal subdivisions on OTSAs were also obtained from federally recognized tribal governments through the Tribal Statistical Areas Program (TSAP). Note that tribal subdivisions do not exist on all reservations/off-reservation trust lands or OTSAs, rather only where they were submitted to the Census Bureau by the federally recognized tribal government for that area. The boundaries for American Indian tribal subdivisions are as of January 1, 2013, as reported by the federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries for tribal subdivisions on OTSAs are those reported as of January 1, 2010 through TSAP." description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-tiger-line-shapefile-2014series-information-for-the-current-american-indian-tribal-subdivision-.yaml identifier: census-tiger-line-shapefile-2014series-information-for-the-current-american-indian-tribal-subdivision- lat_max: 71.441059 lat_min: -14.601813 lon_max: 179.859681 lon_min: -179.231086 name: 'TIGER/Line Shapefile, 2014,Series Information for the Current American Indian Tribal Subdivision (AITS) National Shapefile' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-tiger-line-shapefile-2014series-information-for-the-current-american-indian-tribal-subdivision- url: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2014.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: "The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are mostly as of January 1, 2013, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS). However, some changes made after January 2013, including the addition and deletion of counties, are included." description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-tiger-line-shapefile-2014series-information-for-the-current-county-and-equivalent-national-shap.yaml identifier: census-tiger-line-shapefile-2014series-information-for-the-current-county-and-equivalent-national-shap lat_max: 71.441059 lat_min: -14.601813 lon_max: 179.859681 lon_min: -179.231086 name: 'TIGER/Line Shapefile, 2014,Series Information for the Current County and Equivalent National Shapefile' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-tiger-line-shapefile-2014series-information-for-the-current-county-and-equivalent-national-shap url: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2014.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'The TIGERweb application allows users to access and view geospatial features, geographic area information, and associated attributes from the U.S. Census Bureau Topologically Integrated Geographic Encoding and Referencing System (TIGER) geodatabase. The TIGERweb is intended to meet the needs of users inside and outside the Census Bureau for access to geospatial data contained within the TIGER geodatabase without requiring the use of a GIS. The TIGERweb map layers are grouped by the following geographies: Transportation (Roads and Railroads), Tribal Census Tracts and Block Groups, Census Tracts and Blocks, Military Installations, School Districts, Places and County Subdivisions, American Indian, Alaska Native, and Native Hawaiian Areas, Legislative Areas, Census Regions and Divisions, Urban Areas - Census 2000, Metropolitan and Micropolitan Statistical Areas and Related Statistical Areas, Hydrography, States and Counties. Labels are included for the map layers.' description_attribution: http://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_main.html doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/census-tigerweb-2010.yaml identifier: census-tigerweb-2010 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: TIGERweb 2010 native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/census-tigerweb-2010 url: http://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_main.html variables: ~ version: ~ vertical_extent: ~ - access_dt: 2013-04-15T00:00:00 attributes: 'Daily precipitation, daily maximum temperature, daily minimum temperature' cite_metadata: 'Hayhoe, K., Stoner, et al., (2013), Development and Dissemination of a High-Resolution National Climate Change Dataset. http://cida.usgs.gov/thredds/fileServer/dcp/files/Hayhoe_USGS_downscaled_database_final_report.pdf' data_qualifier: ~ description: 'In this project, we used an advanced statistical downscaling method that combines high-resolution observations with outputs from 16 different global climate models based on 4 future emission scenarios to generate the most comprehensive dataset of daily temperature and precipitation projections available for climate change impacts in the U.S. The gridded dataset covers the continental United States, southern Canada and northern Mexico at one-eighth degree resolution and Alaska at one-half degree resolution. The high-resolution projections produced by this work have been rigorously quality-controlled for both errors and biases in the global climate and statistical downscaling models. We also calculated projected future changes in a broad range of impact-relevant indicators, from seasonal temperature to extreme precipitation days. The results of the error and bias tests and the indicator calculations are made available as part of this database.' description_attribution: https://cida.usgs.gov/thredds/catalog.html?dataset=cida.usgs.gov/thredds/dcp/conus_pr doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/cida_usgs_gov_thredds_dcp_conus_pr.yaml identifier: cida_usgs_gov_thredds_dcp_conus_pr lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Eighth degree-CONUS Daily Downscaled Climate Projections native_id: 0bdee6a2-f677-4714-8d36-0ba570972aba processing_level: ~ publication_year: 2010 release_dt: 2013-12-05T20:42:39 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 51.68; minimum_latitude: 21.44; maximum_longitude: -65.74; minimum_longitude: -127.97;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1960-01-01T00:00:00 2099-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/cida_usgs_gov_thredds_dcp_conus_pr url: https://cida.usgs.gov/thredds/catalog.html?dataset=cida.usgs.gov/thredds/dcp/conus_pr variables: ~ version: N/A vertical_extent: ~ - access_dt: 2013-04-15T00:00:00 attributes: 'daily precipitation, maximum temperature, minimum temperature, wind speed' cite_metadata: "Daily gridded meteorological data obtained from the Surface Water Modeling group at the University of Washington from their web site at http://www.hydro.washington.edu/Lettenmaier/Data/gridded/, the development of which is described by Maurer et al. (2002):\r\n\r\nMaurer, E.P., A.W. Wood, J.C. Adam, D.P. Lettenmaier, and B. Nijssen, 2002, A Long-Term Hydrologically-Based Data Set of Land Surface Fluxes and States for the Conterminous United States, J. Climate 15, 3237-3251" data_qualifier: ~ description: 'A model-derived dataset of land surface states and fluxes is presented for the conterminous United States and portions of Canada and Mexico. The dataset spans the period 1950–2000, and is at a 3-h time step with a spatial resolution of ⅛ degree. The data are distinct from reanalysis products in that precipitation is a gridded product derived directly from observations, and both the land surface water and energy budgets balance at every time step. The surface forcings include precipitation and air temperature (both gridded from observations), and derived downward solar and longwave radiation, vapor pressure deficit, and wind. Simulated runoff is shown to match observations quite well over large river basins' description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/daily-1-8-degree-gridded-meteorological-data-1-jan-1949-31-december-2010.yaml identifier: daily-1-8-degree-gridded-meteorological-data-1-jan-1949-31-december-2010 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'Daily 1/8-degree gridded meteorological data [1 Jan 1949 - 31 Dec 2010]' native_id: 10.1175/1520-0442(2002)015<3237:ALTHBD>2.0.CO;2 processing_level: ~ publication_year: 2011 release_dt: 2011-03-11T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 51.68; minimum_latitude: 21.44; maximum_longitude: -65.74; minimum_longitude: -127.97;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1949-01-01T00:00:00 2000-07-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/daily-1-8-degree-gridded-meteorological-data-1-jan-1949-31-december-2010 url: http://www.engr.scu.edu/~emaurer/gridded_obs/index_gridded_obs.html variables: ~ version: TBD vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'This dataset, released by DoD, contains geographic information for major installations, ranges, and training areas in the United States and its territories. This release integrates site information about DoD installations, training ranges, and land assets in a format which can be immediately put to work in commercial geospatial information systems. Homeland Security/Homeland Defense, law enforcement, and readiness planners will benefit from immediate access to DoD site location data during emergencies. Land use planning and renewable energy planning will also benefit from use of this data. Users are advised that the point and boundary location datasets are intended for planning purposes only, and do not represent the legal or surveyed land parcel boundaries.' description_attribution: http://www.acq.osd.mil/ie/bei/opengov/release_notes.pdf doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/dod-2639.yaml identifier: dod-2639 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'Military Installations, Ranges, and Training Areas' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/dod-2639 url: https://www.acq.osd.mil/eie/BSI/BEI_DISDI.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'Comprehensive monthly and annual time series on all energy sources. Data on production, consumption, reserves, stocks, prices, imports, and exports. Monthly time series extend back to 1973 and annual time series extend back to 1949. National-level data on major end-use sectors ,i.e., residential, commercial, industrial, and transportation.' description_attribution: ~ doi: ~ end_time: 1970-01-01T00:33:33 href: https://data.globalchange.gov/dataset/doe-019-1295783927.yaml identifier: doe-019-1295783927 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Total Energy Data and Statistics native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1970-01-01T00:32:29 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/doe-019-1295783927 url: https://www.eia.gov/totalenergy/data/annual/ variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'Monthly, quarterly, and annual data on electricity generation, consumption, retail sales, price, revenue from retail sales, useful thermal output, fossil fuel stocks, fossil fuel receipts, and quality of fossil fuel. Data organized by fuel type, i.e., coal petroleum, natural gas, nuclear, hydroelectric, wind, solar, geothermal, and wood. Also, data organized by sector, i.e., electric power, electric utility, independent power producers, commercial, and industrial. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm' description_attribution: ~ doi: ~ end_time: 1970-01-01T00:33:34 href: https://data.globalchange.gov/dataset/doe-019-3299699499.yaml identifier: doe-019-3299699499 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Electricity Data and Statistics Application Programming Interface (API) native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1970-01-01T00:32:20 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/doe-019-3299699499 url: https://www.eia.gov/electricity/data.php variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'State-level data on all energy sources. Data include production, consumption, reserves, stocks, prices, imports, and exports. Data are collated from state-specific data reported elsewhere on the EIA website and are the most recent values available. The system provides data back from 1960. While some SEDS data series come directly from surveys conducted by EIA, many are estimated using other available information. These estimations are necessary for the compilation of "total energy" estimates. Users of the EIA API are required to obtain an API Key via this registration form: http://www.eia.gov/beta/api/register.cfm' description_attribution: ~ doi: ~ end_time: ~ href: https://data.globalchange.gov/dataset/doe-019-3988165895.yaml identifier: doe-019-3988165895 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: State Energy Data System (SEDS) Application Programming Interface (API) native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/doe-019-3988165895 url: https://www.eia.gov/state/seds/seds-data-fuel.php?sid=US variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'Data on uranium and nuclear fuel, nuclear power plants and reactors, radioactive waste, and nuclear power generation. International data on nuclear generation also available. Monthly, quarterly, and annual data available.' description_attribution: ~ doi: ~ end_time: 1970-01-01T00:34:00 href: https://data.globalchange.gov/dataset/doe-019-5291681930.yaml identifier: doe-019-5291681930 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Nuclear & Uranium Data and Statistics native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1970-01-01T00:33:33 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/doe-019-5291681930 url: https://www.eia.gov/nuclear/data.php variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'Annual data on proved reserves of crude oil, natural gas, and natural gas liquids in the U.S. Based on EIA Form-23L data. Proved reserves are estimated volumes of hydrocarbon resources that analysis of geologic and engineering data demonstrates with reasonable certainty are recoverable under existing economic and operating conditions. Reserves estimates change from year to year as new discoveries are made, existing fields are more thoroughly appraised, existing reserves are produced, and prices and technologies change.' description_attribution: http://www.eia.gov/survey/form/eia_23l/instructions.pdf doi: ~ end_time: 1970-01-01T00:33:32 href: https://data.globalchange.gov/dataset/doe-019-5404456523.yaml identifier: doe-019-5404456523 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'U.S. Crude Oil, Natural Gas, and Natural Gas Liquids Reserves 2012' native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1970-01-01T00:33:31 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/doe-019-5404456523 url: https://www.eia.gov/naturalgas/crudeoilreserves/archive/2012/ variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: Annual data on the number and production volumes of oil and natural gas wells by state. Annual time series extend back to 1919. description_attribution: ~ doi: ~ end_time: 2009-12-31T00:00:00 href: https://data.globalchange.gov/dataset/doe-019-5418154829.yaml identifier: doe-019-5418154829 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Annual Distribution and Production of Oil and Gas Wells by State From 1919-Latest Year Available native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 2009-01-01T00:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/doe-019-5418154829 url: https://www.eia.gov/naturalgas/archive/petrosystem/petrosysog.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'Monthly and yearly forecasts of energy production, consumption, and price at the national level and by energy type. Monthly forecasts extend 18 months and yearly forecasts extend to 2040. International yearly projections by region extend to 2040.' description_attribution: http://www.eia.gov/analysis/ doi: ~ end_time: 1970-01-01T00:33:34 href: https://data.globalchange.gov/dataset/doe-019-5492098884.yaml identifier: doe-019-5492098884 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Energy Analysis & Projections native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 1970-01-01T00:32:20 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/doe-019-5492098884 url: http://www.eia.gov/analysis/ variables: ~ version: ~ vertical_extent: ~