Facebook
TwitterStudents will explore U.S. census data to see the spatial differences in the United States’ population. The activity uses a web-based map and is tied to the AP Human Geography benchmarks.
Learning outcomes:
·
Unit 2, A1: Geographical analysis of population
(density, distribute and scale)·
Unit 2, A3: Geographical analysis of population
(composition: age, sex, income, education and ethnicity)·
Unit 2, A4: Geographical analysis of population
(patterns of fertility, mortality and health)
Find more advanced human geography geoinquiries and explore all geoinquiries at http://www.esri.com/geoinquiries
Facebook
TwitterThis dataset consists of cartographic data in digital line graph (DLG) form for the northeastern states (Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island and Vermont). Information is presented on two planimetric base categories, political boundaries and administrative boundaries, each available in two formats: the topologically structured format and a simpler format optimized for graphic display. These DGL data can be used to plot base maps and for various kinds of spatial analysis. They may also be combined with other geographically referenced data to facilitate analysis, for example the Geographic Names Information System.
Facebook
TwitterOpen Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This political map of United States of America shows state and national boundaries, state names and other features.
Facebook
TwitterThe Counties dataset was updated on October 31, 2023 from the United States Census Bureau (USCB) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. 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, 2023, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529015
Facebook
TwitterHydrologic landscape regions (HLRs) in the United States were delineated by using geographic information system (GIS) tools and statistical methods including principal components and cluster analyses. The GIS and statistical analyses were applied to land-surface form, geologic texture (permeability of the soil and bedrock), and climate variables that describe the physical and climatic setting of 43,931 small (roughly 200 square kilometers) watersheds in the United States. The analyses then grouped the watersheds into 20 noncontiguous regions (the HLRs) on the basis of similarities in land-surface form, geologic texture, and climate characteristics. This hydrologic landscape regions dataset contains for each of the 43,931 watersheds the (1) watershed identification number, (2) land-surface form, geologic texture, and climate characteristics for each watershed, and (3) hydrologic landscape region number for each watershed.
Facebook
TwitterThis point shapefile contains the proper names and locations of schools in the United States and its Territories using the Federal standard for geographic nomenclature. The U.S. Geological Survey developed the Geographic Names Information System (GNIS) for the U.S. Board on Geographic Names, a Federal inter-agency body chartered by public law to maintain uniform feature name usage throughout the Government and to promulgate standard names to the public. This layer is part of the 2014 ESRI Data and Maps collection for ArcGIS 10.2.
Facebook
TwitterAn automated inventory of the names and locations of physical and cultural geographic features located throughout the United States. To promote geographic feature name standardization and to serve as the Federal Government's repository of information regarding feature name spellings and applications for features in U.S. The names listed in the inventory can be published on Federal maps, charts, and in other documents. The feature locative information has been used in emergency preparedness, marketing, site-selection and analysis, genealogical and historical research, and transportation routing applications.The full Kansas geospatial catalog is administered by the Kansas Data Access & Support Center (DASC) and can be found at the following URL: https://hub.kansasgis.org/
Facebook
TwitterThis data set depicts land use and land cover from the 1970s and 1980s and has been previously published by the U.S. Geological Survey (USGS) in other file formats. This version has been reformatted to other file formats and includes minor edits applied by the U.S. Environmental Protection Agency (USEPA) and USGS scientists. This data set was developed to meet the needs of the USGS National Water-Quality Assessment (NAWQA) Program.
Facebook
Twitterhttps://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain
This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for states and equivalent entities in United States of America. Processors and tools are using this data. States and equivalent entities are the primary governmental divisions of the United States. In addition to the fifty States, the Census Bureau treats the District of Columbia, Puerto Rico, and each of the Island Areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands) as the statistical equivalents of States for the purpose of data presentation.Enhancements Add ISO 3166-3 codes. Simplify geometries to provide better performance across the services.
Facebook
TwitterU.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
This data release contains the GIS data supporting U.S. Geological Survey Open-File Report (OFR) 2005-1252, "The Geologic Map of Seattle—A Progress Report," published in 2005 by Kathy Goetz Troost, Derek B. Booth, Aaron P. Wisher, and Scott A. Shimel (https://doi.org/10.3133/ofr20051252). The OFR was prepared for the 2005 Washington Hydrogeology Symposium and describes the status of geologic mapping for Seattle, Washington, at the time. The map is the result of field mapping and compilation of subsurface geologic data during the years 1999–2004 and was funded by the City of Seattle and the U.S. Geological Survey. Data from more than 36,000 exploration points, geotechnical borings, monitoring wells, excavations, and outcrops were used in making the map. The northern part of the 2005 OFR and the supporting GIS data were subsequently published as two geologic maps: Booth, D.B., Troost, K.G., and Shimel, S.A., 2005, Geologic map of northwestern Seattle (part of the Seattle North 7.5’ ...
Facebook
TwitterTwo datasets provide geographic, land use and population data for US Counties within the contiguous US. Land area, water area, cropland area, farmland area, pastureland area and idle cropland area are given along with latitude and longitude of the county centroid and the county population. Variables in this dataset come from the US Dept. of Agriculture (USDA) Natural Resources Conservation Service (NRCS) and the US Census Bureau.
EOS-WEBSTER provides seven datasets which provide county-level data on agricultural management, crop production, livestock, soil properties, geography and population. These datasets were assembled during the mid-1990's to provide driving variables for an assessment of greenhouse gas production from US agriculture using the DNDC agro-ecosystem model [see, for example, Li et al. (1992), J. Geophys. Res., 97:9759-9776; Li et al. (1996) Global Biogeochem. Cycles, 10:297-306]. The data (except nitrogen fertilizer use) were all derived from publicly available, national databases. Each dataset has a separate DIF.
The US County data has been divided into seven datasets.
US County Data Datasets:
1) Agricultural Management 2) Crop Data (NASS Crop data) 3) Crop Summary (NASS Crop data) 4) Geography and Population 5) Land Use 6) Livestock Populations 7) Soil Properties
Facebook
TwitterU.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
This metadata record describes a series of tabular datasets containing metrics used to characterize drought for select United States Geological Survey (USGS) streamgages for the climate years (April 1 – March 31) 1981 to 2020. These streamgages are a subset of those used in Geospatial Attributes of Gages for Evaluating Streamflow, version 2 (GAGES-II, Falcone, 2011) in the conterminous United States (CONUS). These metrics include streamflow percentiles, identified drought events, annual low streamflow, and drought statistics for each event.
Facebook
TwitterGNIS contains point data derived from the federal Geographic Names Information System, depicting the locations of all named places in New Hampshire. Place name locations from the federal GNIS have been corrected and updated, based upon a variety of sources, including current and historic US Geological Survey topographic maps, aerial photography, New Hampshire state agency records, and current web sites.
Facebook
TwitterThis file was downloaded from https://simplemaps.com/data/us-cities Licence: Creative Commons Attribution 4.0
A simple, accurate and up-to-date database of United States cities and towns.
https://simplemaps.com/data/us-cities
Latitude and longitude data can be used for interactive maps.
Facebook
TwitterU.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
The GNIS contains information about physical and cultural geographic features in the United States and associated areas, both current and historical (not including roads and highways). The database holds the Federally recognized name of each feature and defines the location of the feature by state, county, USGS topographic map, and geographic coordinates.
Facebook
TwitterThis layer shows residence one year ago for those 1 year and older. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of people one year and over who lived in a different state one year ago. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B07204 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.
Facebook
Twitterhttp://www.gnu.org/licenses/old-licenses/gpl-2.0.en.htmlhttp://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html
Facebook
TwitterThe U.S. Geological Survey National Real-Time Water Quality (NRTWQ) Data Service (https://nrtwq.usgs.gov) provides computed concentrations and loads for sediment, nutrients, bacteria, and many additional constituents; uncertainty values and probabilities for exceeding drinking water or recreational criteria; frequency distribution curves; and all historical in-stream sensor measurements.
Facebook
TwitterCC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This coverage was identified on the USGS Water Resources NSDI Node site at https://www.usgs.gov/ngpo/. The coverage contains the state boundaries of the southern region of the continental United States. These boundaries were derived from the Digital Line Graph (DLG) files representing the 1:100,000 scale map in the National Atlas of the United States. The data was then modified by USDA Forest Service Personnel for use in the Southern Forest Resource Assessment and exported to a shapefile (please see Process Steps below).This shapefile is used as a base map for a variety of applications.Metadata modified on 6/08/2011 to include DOI and other minor modifications to the metadata. As of 6/08/2011 data were also available at: //www.srs.fs.usda.gov/sustain/data/. Minor metadata updates on 02/26/2013 and 08/13/2014. Minor metadata updates on 12/06/2016.
Facebook
TwitterThis dataset contains the names that correspond with the 1990 Census high-level geographic area codes contained in the Topologically Integrated Geographic Encoding and Referencing System, or TIGER/Line files. Included are the record type, defining code(s), and name for each geographic entity.
Facebook
TwitterStudents will explore U.S. census data to see the spatial differences in the United States’ population. The activity uses a web-based map and is tied to the AP Human Geography benchmarks.
Learning outcomes:
·
Unit 2, A1: Geographical analysis of population
(density, distribute and scale)·
Unit 2, A3: Geographical analysis of population
(composition: age, sex, income, education and ethnicity)·
Unit 2, A4: Geographical analysis of population
(patterns of fertility, mortality and health)
Find more advanced human geography geoinquiries and explore all geoinquiries at http://www.esri.com/geoinquiries