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 for each of the fifty States, the District of Columbia and the four Insular Territories of the United States is included, as well as a file that provides a Cross-Reference to USGS 7.5 x 7.5 minute quadrangle maps. The records in the data files are organized in an alphabetized listing of all of the names in a particular state or territory. 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.

This metadata record provides the latitude, longitude, and a unique ID value (PRISMID) for all raster cells used by the PRISM group at Oregon State University to characterize climate throughout the conterminous United States. The three column format of comma-separated data can be readily joined to the comma-separated climate and water-balance variables described in the associated metadata file "Water Balance Model Inputs and Outputs for the Conterminous United States".

This dataset represents States and equivalent entities, which are the primary governmental divisions of the United States. 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. 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.

A generic latitude and longitude for each county. These points are provided so a map layer can be developed using files with aggregated data grouped by county name. Use this generic latitude and longitude georeferenced point file and assign any information to the correct county showing on a boundary map layer. If totals are shown in a file for the Commonwealth of Pennsylvania and the desire is to show the total for the state on a map layer, there is a generic latitude and longitude point given for Pennsylvania that will show in the South East corner of the map visual actually landing in the state of Maryland. This is provided for visualizing and displaying the state information on the map layer along with county information.

Connecticut State Line includes the line features of a layer named Connecticut. Connecticut is a 1:24,000-scale, polygon and line feature-based layer that depicts the geographic area encompassed by and the boundary for the State of Connecticut. The State of Connecticut is represented as one polygon feature surrounded by linear boundary features. The layer is based on information from USGS topographic quadrangle maps published between 1969 and 1984 and latitude and longitude coordinates that define the boundary between the states of Connecticut and New York in Long Island Sound. Feature length and geographic area are encoded for linear and polygon features, respectively. This layer was originally published in 1994. Connecticut State Polygon includes the polygon features of a layer named Connecticut. Connecticut is a 1:24,000-scale, polygon and line feature-based layer that depicts the geographic area encompassed by and the boundary for the State of Connecticut. The State of Connecticut is represented as one polygon feature surrounded by linear boundary features. The layer is based on information from USGS topographic quadrangle maps published between 1969 and 1984 and latitude and longitude coordinates that define the boundary between the states of Connecticut and New York in Long Island Sound. Feature length and geographic area are encoded for linear and polygon features, respectively. This layer was originally published in 1994.

World Latitude and Longitude Grids represents five latitude-longitude grids covering the world. The grids are provided at intervals of 1, 5, 10, 15, and 30 degrees and have visibility and scale ranges set for each to provide continuous delivery of a grid at any scale. To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to World Latitude and Longitude Grids.

This dataset is part of the Geographical repository maintained by Opendatasoft. It's been built from the ground up using authoritative sources including the U.S. Postal Service™, U.S. Census Bureau, National Weather Service, American Community Survey, and the IRS.Contains most USPS zip codes (lat/long).

This dataset is about cities and is filtered where the country includes United States, featuring 7 columns including city, continent, country, latitude, and longitude. The preview is ordered by population (descending).

Data available online through the Arkansas Spatial Data Infrastructure (ASDI) at http://gis.arkansas.gov. AHTD 7.5' Latitude and Longitude Lines for year end 2000 information. This file contains location information for 7.5' Latitude and Longitude Lines in the state of Arkansas. These locations were extracted from the Arkansas Highway and Transportation Department county mapping files for the year 2000.

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 as of January 1, 2017, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

This dataset is about cities in the United States, featuring 5 columns: city, country, latitude, longitude, and population. The preview is ordered by population (descending).

This dataset provides geometric parameters for the regular 0.5-degree lat-lon grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Parameters include areas and lengths of grid cell sides and the horizontal and vertical coordinates of grid cell centers and corners. Additional information related to the global domain geometry (e.g., bathymetry and land/ocean masks) are also included. However, users should note these domain geometry fields are approximations because they have been interpolated from the ECCO lat-lon-cap 90 (llc90) native model grid. Users interested in exact budget closure calculations for volume, heat, salt, or momentum should use ECCO fields provided on the llc90 grid. Estimating the Circulation and Climate of the Ocean (ECCO) state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of a global, nominally 1-degree configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.

The datasets are split by census block, cities, counties, districts, provinces, and states. The typical dataset includes the below fields.

Column numbers, Data attribute, Description 1, device_id, hashed anonymized unique id per moving device 2, origin_geoid, geohash id of the origin grid cell 3, destination_geoid, geohash id of the destination grid cell 4, origin_lat, origin latitude with 4-to-5 decimal precision 5, origin_long, origin longitude with 4-to-5 decimal precision 6, destination_lat, destination latitude with 5-to-6 decimal precision 7, destination_lon, destination longitude with 5-to-6 decimal precision 8, start_timestamp, start timestamp / local time 9, end_timestamp, end timestamp / local time 10, origin_shape_zone, customer provided origin shape id, zone or census block id 11, destination_shape_zone, customer provided destination shape id, zone or census block id 12, trip_distance, inferred distance traveled in meters, as the crow flies 13, trip_duration, inferred duration of the trip in seconds 14, trip_speed, inferred speed of the trip in meters per second 15, hour_of_day, hour of day of trip start (0-23) 16, time_period, time period of trip start (morning, afternoon, evening, night) 17, day_of_week, day of week of trip start(mon, tue, wed, thu, fri, sat, sun) 18, year, year of trip start 19, iso_week, iso week of the trip 20, iso_week_start_date, start date of the iso week 21, iso_week_end_date, end date of the iso week 22, travel_mode, mode of travel (walking, driving, bicycling, etc) 23, trip_event, trip or segment events (start, route, end, start-end) 24, trip_id, trip identifier (unique for each batch of results) 25, origin_city_block_id, census block id for the trip origin point 26, destination_city_block_id, census block id for the trip destination point 27, origin_city_block_name, census block name for the trip origin point 28, destination_city_block_name, census block name for the trip destination point 29, trip_scaled_ratio, ratio used to scale up each trip, for example, a trip_scaled_ratio value of 10 means that 1 original trip was scaled up to 10 trips 30, route_geojson, geojson line representing trip route trajectory or geometry

The datasets can be processed and enhanced to also include places, POI visitation patterns, hour-of-day patterns, weekday patterns, weekend patterns, dwell time inferences, and macro movement trends.

The dataset is delivered as gzipped CSV archive files that are uploaded to your AWS s3 bucket upon request.

Dataset

This dataset was created by Gilberto Trindade

Contents

description: Geodetic Control Points dataset current as of 2004. Provide a base of reference for latitude, longitude and height throughout the United States..; abstract: Geodetic Control Points dataset current as of 2004. Provide a base of reference for latitude, longitude and height throughout the United States..

On the continental scale, climate is an important determinant of the distributions of plant taxa and ecoregions. To quantify and depict the relations between specific climate variables and these distributions, we placed modern climate and plant taxa distribution data on an approximately 25-kilometer (km) equal-area grid with 27,984 points that cover Canada and the continental United States (Thompson and others, 2015). The gridded climatic data include annual and monthly temperature and precipitation, as well as bioclimatic variables (growing degree days, mean temperatures of the coldest and warmest months, and a moisture index) based on 1961-1990 30-year mean values from the University of East Anglia (UK) Climatic Research Unit (CRU) CL 2.0 dataset (New and others, 2002), and absolute minimum and maximum temperatures for 1951-1980 interpolated from climate-station data (WeatherDisc Associates, 1989). As described below, these data were used to produce portions of the "Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America" (hereafter referred to as "the Atlas"; Thompson and others, 1999a, 1999b, 2000, 2006, 2007, 2012a, 2015). Evolution of the Atlas Over the 16 Years Between Volumes A & B and G: The Atlas evolved through time as technology improved and our knowledge expanded. The climate data employed in the first five Atlas volumes were replaced by more standard and better documented data in the last two volumes (Volumes F and G; Thompson and others, 2012a, 2015). Similarly, the plant distribution data used in Volumes A through D (Thompson and others, 1999a, 1999b, 2000, 2006) were improved for the latter volumes. However, the digitized ecoregion boundaries used in Volume E (Thompson and others, 2007) remain unchanged. Also, as we and others used the data in Atlas Volumes A through E, we came to realize that the plant distribution and climate data for areas south of the US-Mexico border were not of sufficient quality or resolution for our needs and these data are not included in this data release. The data in this data release are provided in comma-separated values (.csv) files. We also provide netCDF (.nc) files containing the climate and bioclimatic data, grouped taxa and species presence-absence data, and ecoregion assignment data for each grid point (but not the country, state, province, and county assignment data for each grid point, which are available in the .csv files). The netCDF files contain updated Albers conical equal-area projection details and more precise grid-point locations. When the original approximately 25-km equal-area grid was created (ca. 1990), it was designed to be registered with existing data sets, and only 3 decimal places were recorded for the grid-point latitude and longitude values (these original 3-decimal place latitude and longitude values are in the .csv files). In addition, the Albers conical equal-area projection used for the grid was modified to match projection irregularities of the U.S. Forest Service atlases (e.g., Little, 1971, 1976, 1977) from which plant taxa distribution data were digitized. For the netCDF files, we have updated the Albers conical equal-area projection parameters and recalculated the grid-point latitudes and longitudes to 6 decimal places. The additional precision in the location data produces maximum differences between the 6-decimal place and the original 3-decimal place values of up to 0.00266 degrees longitude (approximately 143.8 m along the projection x-axis of the grid) and up to 0.00123 degrees latitude (approximately 84.2 m along the projection y-axis of the grid). The maximum straight-line distance between a three-decimal-point and six-decimal-point grid-point location is 144.2 m. Note that we have not regridded the elevation, climate, grouped taxa and species presence-absence data, or ecoregion data to the locations defined by the new 6-decimal place latitude and longitude data. For example, the climate data described in the Atlas publications were interpolated to the grid-point locations defined by the original 3-decimal place latitude and longitude values. Interpolating the data to the 6-decimal place latitude and longitude values would in many cases not result in changes to the reported values and for other grid points the changes would be small and insignificant. Similarly, if the digitized Little (1971, 1976, 1977) taxa distribution maps were regridded using the 6-decimal place latitude and longitude values, the changes to the gridded distributions would be minor, with a small number of grid points along the edge of a taxa's digitized distribution potentially changing value from taxa "present" to taxa "absent" (or vice versa). These changes should be considered within the spatial margin of error for the taxa distributions, which are based on hand-drawn maps with the distributions evidently generalized, or represented by a small, filled circle, and these distributions were subsequently hand digitized. Users wanting to use data that exactly match the data in the Atlas volumes should use the 3-decimal place latitude and longitude data provided in the .csv files in this data release to represent the center point of each grid cell. Users for whom an offset of up to 144.2 m from the original grid-point location is acceptable (e.g., users investigating continental-scale questions) or who want to easily visualize the data may want to use the data associated with the 6-decimal place latitude and longitude values in the netCDF files. The variable names in the netCDF files generally match those in the data release .csv files, except where the .csv file variable name contains a forward slash, colon, period, or comma (i.e., "/", ":", ".", or ","). In the netCDF file variable short names, the forward slashes are replaced with an underscore symbol (i.e., "_") and the colons, periods, and commas are deleted. In the netCDF file variable long names, the punctuation in the name matches that in the .csv file variable names. The "country", "state, province, or territory", and "county" data in the .csv files are not included in the netCDF files. Data included in this release: - Geographic scope. The gridded data cover an area that we labelled as "CANUSA", which includes Canada and the USA (excluding Hawaii, Puerto Rico, and other oceanic islands). Note that the maps displayed in the Atlas volumes are cropped at their northern edge and do not display the full northern extent of the data included in this data release. - Elevation. The elevation data were regridded from the ETOPO5 data set (National Geophysical Data Center, 1993). There were 35 coastal grid points in our CANUSA study area grid for which the regridded elevations were below sea level and these grid points were assigned missing elevation values (i.e., elevation = 9999). The grid points with missing elevation values occur in five coastal areas: (1) near San Diego (California, USA; 1 grid point), (2) Vancouver Island (British Columbia, Canada) and the Olympic Peninsula (Washington, USA; 2 grid points), (3) the Haida Gwaii (formerly Queen Charlotte Islands, British Columbia, Canada) and southeast Alaska (USA, 9 grid points), (4) the Canadian Arctic Archipelago (22 grid points), and (5) Newfoundland (Canada; 1 grid point). - Climate. The gridded climatic data provided here are based on the 1961-1990 30-year mean values from the University of East Anglia (UK) Climatic Research Unit (CRU) CL 2.0 dataset (New and others, 2002), and include annual and monthly temperature and precipitation. The CRU CL 2.0 data were interpolated onto the approximately 25-km grid using geographically-weighted regression, incorporating local lapse-rate estimation and correction. Additional bioclimatic variables (growing degree days on a 5 degrees Celsius base, mean temperatures of the coldest and warmest months, and a moisture index calculated as actual evapotranspiration divided by potential evapotranspiration) were calculated using the interpolated CRU CL 2.0 data. Also included are absolute minimum and maximum temperatures for 1951-1980 interpolated in a similar fashion from climate-station data (WeatherDisc Associates, 1989). These climate and bioclimate data were used in Atlas volumes F and G (see Thompson and others, 2015, for a description of the methods used to create the gridded climate data). Note that for grid points with missing elevation values (i.e., elevation values equal to 9999), climate data were created using an elevation value of -120 meters. Users may want to exclude these climate data from their analyses (see the Usage Notes section in the data release readme file). - Plant distributions. The gridded plant distribution data align with Atlas volume G (Thompson and others, 2015). Plant distribution data on the grid include 690 species, as well as 67 groups of related species and genera, and are based on U.S. Forest Service atlases (e.g., Little, 1971, 1976, 1977), regional atlases (e.g., Benson and Darrow, 1981), and new maps based on information available from herbaria and other online and published sources (for a list of sources, see Tables 3 and 4 in Thompson and others, 2015). See the "Notes" column in Table 1 (https://pubs.usgs.gov/pp/p1650-g/table1.html) and Table 2 (https://pubs.usgs.gov/pp/p1650-g/table2.html) in Thompson and others (2015) for important details regarding the species and grouped taxa distributions. - Ecoregions. The ecoregion gridded data are the same as in Atlas volumes D and E (Thompson and others, 2006, 2007), and include three different systems, Bailey's ecoregions (Bailey, 1997, 1998), WWF's ecoregions (Ricketts and others, 1999), and Kuchler's potential natural vegetation regions (Kuchler, 1985), that are each based on distinctive approaches to categorizing ecoregions. For the Bailey and WWF ecoregions for North America and the Kuchler potential natural vegetation regions for the contiguous United States (i.e.,

This dataset contains gridded data of aragonite saturation state across the global oceans (spatial distributions with a resolution of 1x1 degree latitude and longitude) at depth levels of 0m, 50m, 100m, 200m, 500m, 1000m, 2000m, 3000m and 4000m. Ocean station data with at least dissolved inorganic carbon (DIC) and total alkalinity (TA) measurements were obtained from the Global Ocean Data Analysis Project (GLODAP), the Carbon Dioxide in the Atlantic Ocean (CARINA), the Pacific Ocean Interior Carbon (PACIFICA), and some recent cruise data sets. Aragonite saturation state was calculated using a Matlab version of CO2SYS from in-situ temperature, pressure, salinity, dissolved inorganic carbon (DIC), total alkalinity (TA), silicate and phosphate with the dissociation constants for carbonic acid of Lueker et al. [2000], potassium bisulfate (KHSO4-) of Dickson [1990a], boric acid of Dickson [1990b], and with the total borate concentration equations of Lee et al. [2010]. Aragonite saturation state was correct to January 1, 2000 before it was gridded to a world-wide grid with 1x1 degree latitude and longitude resolution. The Longitude values used in this dataset are from 20 to 380 degrees. For more information about the data set, please read the below paper: Jiang, L.-Q., R. A. Feely, B. R. Carter, D. J. Greeley, D. K. Gledhill, and K. M. Arzayus (2015), Climatological distribution of aragonite saturation state in the global oceans, Global Biogeochem. Cycles, 29, 1656-1673, https://doi.org/10.1002/2015GB005198.

An outline map showing the coastline, boundaries and major lakes and rivers for Canada and nearby countries. Included are the locations of capitals and selected places, and major latitude and longitude lines (the graticule).

[Metadatas] This layer represents the USGS topo quadrangle boundaries published in the Old Hawaiian Datum (OHD), prior to their being recast in the late 1990's. Source: Created by the Office of State Planning in the Old Hawaiian Datum using the latitude/longitude coordinates of the quadrangle boundaries, and the ARC GENERATE command.

For more information, see the full metadata at https://files.hawaii.gov/dbedt/op/gis/data/usgs_quads_ohd.pdf, or contact the Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

Connecticut Mainland Line includes the line features of a layer named Connecticut Mainland. Connecticut Mainland is a 1:24,000-scale, polygon and line feature-based layer that depicts the geographic area encompassed by and the boundary for the State of Connecticut with an additional linear shoreline feature separating the Connecticut mainland from the waters of Long Island Sound. The layer includes a polygon feature representing the Connecticut mainland, a polygon feature representing Connecticut waters in Long Island Sound and approximately 700 polygon features representing Connecticut islands in Long Island Sound. The layer is based on information from USGS topographic quadrangle maps published between 1969 and 1984 and latitude and longitude coordinates that define the boundary between the states of Connecticut and New York in Long Island Sound. Feature length and geographic area are encoded for linear and polygon features, respectively. This layer was originally published in 2005.

Connecticut Mainland Polygon includes the polygon features of a layer named Connecticut Mainland. Connecticut Mainland is a 1:24,000-scale, polygon and line feature-based layer that depicts the geographic area encompassed by and the boundary for the State of Connecticut with an additional linear shoreline feature separating the Connecticut mainland from the waters of Long Island Sound. The layer includes a polygon feature representing the Connecticut mainland, a polygon feature representing Connecticut waters in Long Island Sound and approximately 700 polygon features representing Connecticut islands in Long Island Sound. The layer is based on information from USGS topographic quadrangle maps published between 1969 and 1984 and latitude and longitude coordinates that define the boundary between the states of Connecticut and New York in Long Island Sound. Feature length and geographic area are encoded for linear and polygon features, respectively. This layer was originally published in 2005.