This layer displays per capita personal income by county. This measure of income is calculated as the total personal income of the residents of an area divided by the population of the area. Per capita personal income is often used as an indicator of consumers’ purchasing power and of the economic well-being of the residents of an area. Information used in this map layer is acquired from the US Bureau of Economic Analysis Regional Economic Accounts: Economic Profile (CA30).
New Data! New map of dominant spoken language by census tract!
Layer displays information about languages spoken at home at the neighborhood (census tract) level. Each area on the map is shaded to reflect the dominant spoken language, or the language spoken by the majority of people in the area. Toggle between map layers to display the dominant language excluding English, and the dominant language excluding English and excluding Spanish. Census tracts in which there is no population, or in which less than 100 individuals or one percent of the population speak the dominant language are excluded from categorization.
Places of Worship, 2016
This layer displays locations of places of worship. Address-level data are acquired from the September 2016 IRS Exempt Organization Business Master File Extract (EO BMF) based on filing requirement code.
New Data! The Community Commons Maproom now provides access to 27 maps layers covering data from the 500 Cities Project!
Map data topics include preventative health, risk behaviors, and clinical care. Estimates from the 500 Cities Project are available at the state, city, and census tract level. For more map layers from this series, search the Map Room for the terms 500 Cities.
National Hydrography Dataset (Waterbody)
The National Hydrography Dataset (NHD) is used to portray surface water. The NHD represents the drainage network with features such as rivers, streams, canals, lakes, ponds, coastline, etc. The principal components of the NHD are:
- NHDFlowline: This is the fundamental flow network consisting predominantly of stream/river and artificial path vector features. It represents the spatial geometry, carries the attributes, models the water flow, and contains linear referencing measures for locating events on the network. Additional NHDFlowline features are canal/ditch, pipeline, connector, underground conduit, and coastline.
- NHDArea: This feature class contains many additional features of water polygons. One of the more important is the stream/river feature. It represents the aerial extent of the water in a wide stream/river with a basic set of attributes. They typically contain NHDFlowline artificial paths that are used to model the stream/river. Artificial path carries the critical attributes of the stream/river, whereas NHDArea represents the geometric extent.
- NHDWaterbody: Basic waterbodies such as lake/pond features are represented here. They portray the spatial geometry and the attributes of the feature. These water polygons may contain NHDFlowline artificial paths to allow the representation of water flow. Other NHDWaterbody features are swamp/marsh, reservoir, playa, estuary, and ice mass.
Access to Primary Care Providers
Layers display county-level information about the number and rate of physicians based on data from the Health Resources and Services Administration (HRSA) 2015-16 Area Health Resource File (AHRF).
National Hydrography Dataset (Flowline)
The National Hydrography Dataset (NHD) is used to portray surface water. The NHD represents the drainage network with features such as rivers, streams, canals, lakes, ponds, coastline, etc. The principal components of the NHD are:
- NHDFlowline: This is the fundamental flow network consisting predominantly of stream/river and artificial path vector features. It represents the spatial geometry, carries the attributes, models the water flow, and contains linear referencing measures for locating events on the network. Additional NHDFlowline features are canal/ditch, pipeline, connector, underground conduit, and coastline.
- NHDArea: This feature class contains many additional features of water polygons. One of the more important is the stream/river feature. It represents the aerial extent of the water in a wide stream/river with a basic set of attributes. They typically contain NHDFlowline artificial paths that are used to model the stream/river. Artificial path carries the critical attributes of the stream/river, whereas NHDArea represents the geometric extent.
- NHDWaterbody: Basic waterbodies such as lake/pond features are represented here. They portray the spatial geometry and the attributes of the feature. These water polygons may contain NHDFlowline artificial paths to allow the representation of water flow. Other NHDWaterbody features are swamp/marsh, reservoir, playa, estuary, and ice mass.
EPA Climate Change Indicators – Change in Extreme Temperatures
This indicator displays changes in the number of days with unusually (>95th percentile) cold temperatures in the contiguous 48 United States. Indicator data are acquired from the EPA’s Climate Change Indicators in the United States, Fourth Edition, published in 2016.
Hydrography – Waterbodies
Hydrography depicts surface water, including rivers and streams, lakes and ponds, canals, coastlines, and many other water features. The Hydrography layer combines two data sets: the 2014 National Map Hydrographic Geodatabase (1:1,000,000 scale) for small to medium scales, and the 2016 National Hydrography Datataset (NHD) (1:24,000 scale) for large scale mapping. Hydrography is depicted in two layers. Rivers & Streams depicts linear hydrography, including rivers, streams, canals, pipes, and artificial paths (line networks through larger water bodies). Waterbodies depicts area hydrography, including larger rivers, lakes, ponds, seas, bays, estuaries, etc.
EPA Climate Change Indicators – Change in Surface Temperatures
This indicator describes trends in average surface temperature for the United States. Indicator data are acquired from the EPA’s Climate Change Indicators in the United States, Fourth Edition, published in 2016.