This statistic shows the total land and water area of the United States by state and territory. Alabama covers an area of 52,420 square miles.

The Geographic Names Information System (GNIS) was developed by the United States Geological Survey (USGS) to meet major national needs regarding geographic names and their standardization and dissemination. This dataset consists of standard report files written from the National Geographic Names Data Base, one of five data bases maintained in the GNIS. A standard format data file containing Michigan place names and geographic features such as towns, schools, reservoirs, parks, streams, valleys, springs and ridges is accompanied by a file that provides a Cross-Reference to USGS 7.5 x 7.5 minute quadrangle maps for each feature. The records in the data files are organized alphabetically by place or feature name. The other variables available in the dataset include: Federal Information Processing Standard (FIPS) state/county codes, Geographic Coordinates -- latitude and longitude to degrees, minutes, and seconds followed by a single digit alpha directional character, and a GNIS Map Code that can be used with the Cross-Reference file to provide the name of the 7.5 x 7.5 minute quadrangle map that contains that geographic feature.

Summary data of fixed broadband coverage by geographic area. License and Attribution: Broadband data from FCC Form 477, and data from the U.S. Census Bureau that are presented on this site are offered free and not subject to copyright restriction. Data and content created by government employees within the scope of their employment are not subject to domestic copyright protection under 17 U.S.C. § 105. See, e.g., U.S. Government Works. While not required, when using content, data, documentation, code and related materials from fcc.gov or broadbandmap.fcc.gov in your own work, we ask that proper credit be given. Examples include: • Source data: FCC Form 477 • Map layer based on FCC Form 477 • Code data based on broadbandmap.fcc.gov The geography look ups are created from the US census shapefiles, which are in Global Coordinate System North American Datum of 1983 (GCS NAD83). The coordinates do not get reprojected during processing. The "centroid_lng", "centroid_lat" columns in the lookup table are the exact values from the US census shapefile (INTPTLON, INTPTLAT). The "bbox_arr" column is calculated from the bounding box/extent of the original geometry in the shapefile; no reprojection or transformations are done to the geometry.

Census geographic areas are used by the Census Bureau to collect, tabulate, and aggregate decennial census data, and are also used in more frequent demographics reports like the annual American Community Survey (ACS). Three levels of areal geography are available from MassGIS (with layer name in parentheses): Blocks, Block Groups, and Tracts

Tree City USA is a national program that recognizes municipal commitment to community forestry. In return for meeting program requirements, Tree City USA participants expect social, economic, and/or environmental benefits. Understanding the geographic distribution and socioeconomic characteristics of Tree City USA communities at the national scale can offer insights into the motivations or barriers to program participation, and provide context for community forestry research at finer scales. In this study, researchers assessed patterns in Tree City USA participation for all U.S. communities with more than 2,500 people according to geography, community population size, and socioeconomic characteristics, such as income, education, and race. Nationally, 23.5% of communities studied were Tree City USA participants, and this accounted for 53.9% of the total population in these communities. Tree City USA participation rates varied substantially by U.S. region, but in each region participation rates were higher in larger communities, and long-term participants tended to be larger communities than more recent enrollees. In logistic regression models, owner occupancy rates were significant negative predictors of Tree City USA participation, education and percent white population were positive predictors in many U.S. regions, and inconsistent patterns were observed for income and population age. The findings indicate that communities with smaller populations, lower education levels, and higher minority populations are underserved regionally by Tree City USA, and future efforts should identify and overcome barriers to participation in these types of communities. This dataset is associated with the following publication: Berland , A., D. Herrmann , and M. Hopton. National Assessment of Tree City USA Participation According to Geography andSocioeconomic Characteristics. Arboriculture & Urban Forestry. International Society of Arboriculture, Champaign, IL, USA, 42(2): 120-130, (2016).

A text database of named places in the United States. The US Board on Geographic Names controls the database of official names of places in the US, and the US Geological Survey (USGS) maintains the database. This is a copy of the 2017-06-01 database, which I am using to create an R package for textual analyses of geographic content, to ensure this version remains. The original source was from: https://geonames.usgs.gov/domestic/download_data.htm (which is a very slow server).I have chosen CC0 for the license because, as a creation of the US government, I don't think the database can be copyrighted (and CC0 is the closest match).

This activity will no longer be maintained after June 16, 2025. Current lessons are available in the K-12 Classroom Activities Gallery.

This activity uses Map Viewer and is designed for intermediate users. We recommend MapMaker when getting started with maps in the classroom - see this StoryMap for the same activity in MapMaker.ResourcesMapTeacher guide Student worksheetVocabulary and puzzlesSelf-check questionsGet startedOpen the map.Use the teacher guide to explore the map with your class or have students work through it on their own with the worksheet.New to GeoInquiriesTM? See Getting to Know GeoInquiries.Social Studies standardsC3: D2.Geo.5.6-8 – Analyze the combinations of cultural and environmental characteristics that make places both similar to and different from other places.C3: D2.Geo.2.6-8 – Use maps, satellite images, photographs, and other representations to explain relationships between the locations of places and regions and changes in their environmental characteristics.Learning outcomesExplore trade through exports and imports in North America.Integrate satellite imagery of a hurricane with a plot of the hurricane’s path. More activitiesAll World Geography GeoInquiriesAll GeoInquiries

This map is for human geography classrooms and tied to the AP benchmarks. Learn more about GeoInquiries at www.esri.com/geoinquiries

Us Map .json data from OSU CSE 5544 class

Outline of the USA, low resolution world data

Students 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

Easy access to census data in map, KML, shapefile, and other formats. Could be used for GIS mapping.

Key Table Information.Table Title.Annual Geographic Information Table.Table ID.GEOINFO2023.GEOINFO.Survey/Program.Geography.Year.2023.Dataset.GEO Geography Information.Source.U.S. Census Bureau, 2023 Geography.Release Date.August 15, 2024.Dataset Universe.Geographic information available in data.census.gov for year 2023.Methodology.Data Items and Other Identifying Records.Geographic Area Name Area (Land, in square meters) Area (Land, in square miles) Area (Water, in square meters) Area (Water, in square miles) Internal Point (Latitude) Internal Point (Longitude) For full list of all the variables including those available in the API refer to the following link: https://api.census.gov/data/2023/geoinfo/variables.html.Unit(s) of Observation.Geographic entity.Geography Coverage.For a full list defining the geographies covered go to https://api.census.gov/data/2023/geoinfo/geography.html.Technical Documentation/Methodology.https://www.census.gov/programs-surveys/geography/about/glossary.html.Table Information.API Information.https://api.census.gov/data/2023/geoinfo.html.Data-Specific Notes.The Geography Information dataset (GEOINFO) contains all the geographies that are disseminated by the U.S Census Bureau during a calendar year. The dataset combines all these disseminated geographies into one centralized location to allow for easy user access. The Geography Information dataset includes spatial attributes for the disseminated geographies, such as a point of internal latitude, a point of internal longitude, and the area of the water and land both in square meters and square miles. The geographies contained in the Geography Information dataset are the geographies disseminated for surveys and programs such as the American Community Survey, Community Resilience Estimates, Current Population Survey, Decennial Census, Economic Census, Economic Surveys, Household Pulse Survey, International Database, Population Estimates, Secondary Employment Outcomes, Public Sector, and Survey of Market Absorption. The Geography Information dataset does include island area geographies but does not contain any international geographies. The Geography Information dataset will be created annually for the calendar year prior once all of the Geographic Information Tables for the various surveys and programs are received for the year. The Geography Information dataset will be released around the early summer every year. The program will first produce a Geography Information dataset for data year 2023 and eventually produce datasets going backwards to data year 2020. The program will also produce a Geography Information dataset for every subsequent year after data year 2023. Note: The Geography Information dataset contains the geographies disseminated for the Population Estimates Program but does not currently support the release of the population estimates. Please refer to the following URL for population estimates: https://www.census.gov/programs-surveys/popest/data.html Note: The Geography Information dataset for 2023 does not include any island area geographies..Additional Information.Contact Information.census.data@census.gov.Suggested Citation.U.S. Census Bureau. "Annual Geographic Information Table" Geography, GEO Geography Information, Table GEOINFO, -1, https://data.census.gov/table/GEOINFO2023.GEOINFO?q=GEOINFO: Accessed on June 24, 2025..

Analysis of ‘Geography Lookup Table’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/801e1bd7-e19b-4cb9-8959-b34b8fc61ab7 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

Summary data of fixed broadband coverage by geographic area. License and Attribution: Broadband data from FCC Form 477, and data from the U.S. Census Bureau that are presented on this site are offered free and not subject to copyright restriction. Data and content created by government employees within the scope of their employment are not subject to domestic copyright protection under 17 U.S.C. § 105. See, e.g., U.S. Government Works.

While not required, when using content, data, documentation, code and related materials from fcc.gov or broadbandmap.fcc.gov in your own work, we ask that proper credit be given. Examples include: • Source data: FCC Form 477 • Map layer based on FCC Form 477 • Code data based on broadbandmap.fcc.gov

The geography look ups are created from the US census shapefiles, which are in Global Coordinate System North American Datum of 1983 (GCS NAD83). The coordinates do not get reprojected during processing. The "centroid_lng", "centroid_lat" columns in the lookup table are the exact values from the US census shapefile (INTPTLON, INTPTLAT). The "bbox_arr" column is calculated from the bounding box/extent of the original geometry in the shapefile; no reprojection or transformations are done to the geometry.

--- Original source retains full ownership of the source dataset ---

The Census data utilized for developing the Community Layer used 2010 TIGER/Line shapefile datasets (TIGER = Topologically Integrated Geographic Encoding and Referencing). TIGER/Line shapefiles are available for free download from the US Census Bureau and include various legal and statistical geographic areas for which the Census tabulates data. The shapefiles are designed to be used in a GIS environment, with the ability to directly link the geographic areas to Census data via a unique GEOID number.The following TIGER/Line datasets should be used: - Counties and Equivalent Entities –primary legal divisions within each state (counties, parishes, etc)- County Subdivisions –includes both legal areas (Minor Civil Divisions or MCDs) and various statistical areas- Places –includes both legal areas (Incorporated Places) and statistical areas (Census Designated Places or CDPs)- Blocks –the smallest geographical area for which Census population counts are recorded; blocks never cross boundaries of any entity for which the Census Bureau tabulates data, including counties, county subdivisions, places, and American Indian, Alaska Native, and Native Hawaiian (AIANNH) areas- American Indian, Alaska Native, and Native Hawaiian (AIANNH) AreasExtracting and Formatting CIS DataA key component of the community layer is the ability to link CIS information spatially. Data from CIS cannot directly be joined with Census data. The two datasets have community name discrepancies which impede an exact match. Therefore, CIS data needs to be formatted to match Census community names. A custom report can be obtained from CIS to include a CID number, Community Name, County, State, Community Status, and Tribal status for all CIS records. Make sure all CID numbers are six digits and you follow the CIS community naming convention outlined in Table 4.2.1.1 in the Community Layer Update Technical Guide 20131206. Converting the CIS name“ADDISON, VILLAGE OF” to “ADDISON TOWN”involves removing unneeded spaces, comma, and preposition to make the join successful to the Census data. Using a comprehensive report at a national level gains efficiencies as bulk edits can be made. Data for each state should be extracted as needed by separating the CIS data into each type of community corresponding to the Census geography layers used, and a new JoinID column (e.g. ADDISON TOWN) can be created for each dataset allowing the CIS data to be joined to the Census data.

Comprehensive dataset of 3 Institute of Geography and Statistics in California, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The TIGER/Line Shapefiles are an extract of selected geographic and cartographic information from the Census MAF/TIGER database. The Census MAF/TIGER database 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 the shapefiles can be combined to cover the whole nation.

Two 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

US Geographic Codes Dataset

This code is used to generate a combined data set of US ZIP, FIPS, and County data for most ZIP Codes in the U.S. (41,867 to be exact).

Code to generate the data set from the government files listed below can be found here.

The Data

The dataset is organized as follows:

• Zip Code: USPS ZIP code from here
• State Name: Full state name (E.g. Michigan)
• State Abrv: USPS abbreviated state name (E.g: MI)
• State Code: FIPS State Code from here
• County Name: County in which ZIP is located
• County Code: FIPS County Code
• FIPS Code: FIPS State Code + FIPS County Code from here
• ANSI Code: American National Standards Institute Code
• Centroid Lat: Latitude value of the county center
• Centroid Long: Longitude value of the county center

Sources

The data used to create this data set was taken from several recent government data sets.

These are:

• 2017 US Gazetteer FIPS Dataset
• 2017 US Census County Polygons Dataset
• 2015 Department of Labor GPCI Dataset
• General Census State Code Reference Document

Disclaimers

The final csv is in 'latin1' encoding to preserve the Spanish county names in Puerto Rico.

This data is from, and shall remain in the public domain, and the onus of responsibility lies with the user of this data.

2019 US Census All Counties and County Equivalents geospatial data

U.S. Census Bureau; TIGER/Line Shapefiles 2019 Data accessed from: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2019.html

TIGER/Line Shapefiles do not include demographic data, but they do contain geographic entity codes (GEOIDs) that can be linked to the Census Bureau’s demographic data.

The Geographic Areas Reference Manual (GARM) describes in great detail the basic geographic entities the Census Bureau uses (https://www.census.gov/programs-surveys/acs/geography-acs.html).

TIGER Data Products Guide (https://www.census.gov/programs-surveys/geography/guidance/tiger-data-products-guide.html)