Abstract

A crosswalk table from US postal ZIP codes to geo-points (latitude, longitude)

Documentation

Data source: public.opendatasoft.

The ZIP code database contained in 'zipcode.csv' contains 43204 ZIP codes for the continental United States, Alaska, Hawaii, Puerto Rico, and American Samoa. The database is in comma separated value format, with columns for ZIP code, city, state, latitude, longitude, timezone (offset from GMT), and daylight savings time flag (1 if DST is observed in this ZIP code and 0 if not).

This database was composed using ZIP code gazetteers from the US Census Bureau from 1999 and 2000, augmented with additional ZIP code information The database is believed to contain over 98% of the ZIP Codes in current use in the United States. The remaining ZIP Codes absent from this database are entirely PO Box or Firm ZIP codes added in the last five years, which are no longer published by the Census Bureau, but in any event serve a very small minority of the population (probably on the order of .1% or less). Although every attempt has been made to filter them out, this data set may contain up to .5% false positives, that is, ZIP codes that do not exist or are no longer in use but are included due to erroneous data sources. The latitude and longitude given for each ZIP code is typically (though not always) the geographic centroid of the ZIP code; in any event, the location given can generally be expected to lie somewhere within the ZIP code's "boundaries".The ZIP code database contained in 'zipcode.csv' contains 43204 ZIP codes for the continental United States, Alaska, Hawaii, Puerto Rico, and American Samoa. The database is in comma separated value format, with columns for ZIP code, city, state, latitude, longitude, timezone (offset from GMT), and daylight savings time flag (1 if DST is observed in this ZIP code and 0 if not). This database was composed using ZIP code gazetteers from the US Census Bureau from 1999 and 2000, augmented with additional ZIP code information The database is believed to contain over 98% of the ZIP Codes in current use in the United States. The remaining ZIP Codes absent from this database are entirely PO Box or Firm ZIP codes added in the last five years, which are no longer published by the Census Bureau, but in any event serve a very small minority of the population (probably on the order of .1% or less). Although every attempt has been made to filter them out, this data set may contain up to .5% false positives, that is, ZIP codes that do not exist or are no longer in use but are included due to erroneous data sources. The latitude and longitude given for each ZIP code is typically (though not always) the geographic centroid of the ZIP code; in any event, the location given can generally be expected to lie somewhere within the ZIP code's "boundaries".

The database and this README are copyright 2004 CivicSpace Labs, Inc., and are published under a Creative Commons Attribution-ShareAlike license, which requires that all updates must be released under the same license. See http://creativecommons.org/licenses/by-sa/2.0/ for more details. Please contact schuyler@geocoder.us if you are interested in receiving updates to this database as they become available.The database and this README are copyright 2004 CivicSpace Labs, Inc., and are published under a Creative Commons Attribution-ShareAlike license, which requires that all updates must be released under the same license. See http://creativecommons.org/licenses/by-sa/2.0/ for more details. Please contact schuyler@geocoder.us if you are interested in receiving updates to this database as they become available.

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 denotes ZIP Code centroid locations weighted by population. Population weighted centroids are a common tool for spatial analysis, particularly when more granular data is unavailable or researchers lack sophisticated geocoding tools. The ZIP Code Population Weighted Centroids allows researchers and analysts to estimate the center of population in a given geography rather than the geometric center.

This data package has the purpose to offer data for demographic indicators, part of 5-years American Community Census, that could be needed in the analysis made along with health-related data or as stand-alone. The American Community Survey based on 5-years estimates is, according to U.S Census Bureau, the most reliable, because the samples used are the largest and the data collected cover all country areas, regardless of the population number.

The 2005 First Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on the latest available governmental unit boundaries. The Census TIGER database represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The 2005 First Edition TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The files contain information distributed over a series of record types for the spatial objects of a county. There are 19 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, and area boundaries.

Java Tool to extrapolate latitude and longitude from US Postal Service database

The purpose of this tool is to estimate latitude and longitude from a user inputted zip code. This tool has been useful in collecting latitude and longitude data for users within the US that may not have known their corresponding latitude and longitude information.

User Input :

The sole input from the user is the zip code. The program searches the database and then displays the corresponding geographical latitude and longitude. This model was developed as an aid to gather latitude and longitude data from user of our other software tools.

This model was developed in JAVA, is simple to use, and runs on multiple platforms (e.g. Mac, PC, Sun).

Java Tool to extrapolate latitude and longitude from US Postal Service database The purpose of this tool is to estimate latitude and longitude from a user inputted zip code. This tool has been useful in collecting latitude and longitude data for users within the US that may not have known their corresponding latitude and longitude information. User Input : The sole input from the user is the zip code. The program searches the database and then displays the corresponding geographical latitude and longitude. This model was developed as an aid to gather latitude and longitude data from user of our other software tools. This model was developed in JAVA, is simple to use, and runs on multiple platforms (e.g. Mac, PC, Sun). Resources in this dataset:Resource Title: Zip Search Version 0.9. File Name: Web Page, url: https://www.ars.usda.gov/research/software/download/?softwareid=156&modecode=50-60-05-00 download page

About this Dataset

Contains All US Zipcodes along with the Latigude and Longitude estimated center of zip

Category

Location Lists

Keywords

Zipcode

Row Count

43841

Price

$49.99

The Daily and Annual PM2.5, O3, and NO2 Concentrations at ZIP Codes for the Contiguous U.S., 2000-2016, v1.0 data set contains daily and annual concentration predictions for Fine Particulate Matter (PM2.5), Ozone (O3), and Nitrogen Dioxide (NO2) pollutants at ZIP Code-level for the years 2000 to 2016. Ensemble predictions of three machine-learning models were implemented (Random Forest, Gradient Boosting, and Neural Network) to estimate the daily PM2.5, O3, and NO2 at the centroids of 1km x 1km grid cells across the contiguous U.S. for 2000 to 2016. The predictors included air monitoring data, satellite aerosol optical depth, meteorological conditions, chemical transport model simulations, and land-use variables. The ensemble models demonstrated excellent predictive performance with 10-fold cross-validated R-squared values of 0.86 for PM2.5, 0.86 for O3, and 0.79 for NO2. These high-resolution, well-validated predictions allow for estimates of ZIP Code-level pollution concentrations with a high degree of accuracy. For general ZIP Codes with polygon representations, pollution levels were estimated by averaging the predictions of grid cells whose centroids lie inside the polygon of that ZIP Code; for other ZIP Codes such as Post Offices or large volume single customers, they were treated as a single point and predicted their pollution levels by assigning the predictions using the nearest grid cell. The polygon shapes and points with latitudes and longitudes for ZIP Codes were obtained from Esri and the U.S. ZIP Code Database and were updated annually. The data include about 31,000 general ZIP Codes with polygon representations, and about 10,000 ZIP Codes as single points. The aggregated ZIP Code-level, daily predictions are applicable in research such as epidemiology, public health, and political science, by linking with ZIP Code-level demographic and medical data sets, including national inpatient care records, medical claims data, census data, and U.S. Census Bureau American Community Survey (ACS). The data are particularly useful for studies on rural populations who may lack air monitoring sites. Compared with the 1km grid data, the ZIP Code-level predictions are much smaller in size and are manageable in personal computing environments. This greatly improves the inclusion of scientists in different fields by making it easier to use these data in air pollution research. The Units are ug/m^3 for PM2.5 and ppb for O3 and NO2.

For many countries lat/lng are determined with an algorithm that searches the place names in the main geonames database using administrative divisions and numerical vicinity of the postal codes as factors in the disambiguation of place names. For postal codes and place name for which no corresponding toponym in the main geonames database could be found an average lat/lng of 'neighbouring' postal codes is calculated. Please let us know if you find any errors in the data set. ThanksFor Canada we have only the first letters of the full postal codes (for copyright reasons)For Ireland we have only the first letters of the full postal codes (for copyright reasons)For Malta we have only the first letters of the full postal codes (for copyright reasons)The Argentina data file contains 4-digit postal codes which were replaced with a new system in 1999.For Brazil only major postal codes are available (only the codes ending with -000 and the major code per municipality).For India the lat/lng accuracy is not yet comparable to other countries.Update frequency: 1 month

The Daily and Annual PM2.5, O3, and NO2 Concentrations at ZIP Codes for the Contiguous U.S., 2000-2016, v1.0 data set contains daily and annual concentration predictions for Fine Particulate Matter (PM2.5), Ozone (O3), and Nitrogen Dioxide (NO2) pollutants at ZIP Code-level for the years 2000 to 2016. Ensemble predictions of three machine-learning models were implemented (Random Forest, Gradient Boosting, and Neural Network) to estimate the daily PM2.5, O3, and NO2 at the centroids of 1km x 1km grid cells across the contiguous U.S. for 2000 to 2016. The predictors included air monitoring data, satellite aerosol optical depth, meteorological conditions, chemical transport model simulations, and land-use variables. The ensemble models demonstrated excellent predictive performance with 10-fold cross-validated R-squared values of 0.86 for PM2.5, 0.86 for O3, and 0.79 for NO2. These high-resolution, well-validated predictions allow for estimates of ZIP Code-level pollution concentrations with a high degree of accuracy. For general ZIP Codes with polygon representations, pollution levels were estimated by averaging the predictions of grid cells whose centroids lie inside the polygon of that ZIP Code; for other ZIP Codes such as Post Offices or large volume single customers, they were treated as a single point and predicted their pollution levels by assigning the predictions using the nearest grid cell. The polygon shapes and points with latitudes and longitudes for ZIP Codes were obtained from Esri and the U.S. ZIP Code Database and were updated annually. The data include about 31,000 general ZIP Codes with polygon representations, and about 10,000 ZIP Codes as single points. The aggregated ZIP Code-level, daily predictions are applicable in research such as environmental epidemiology, environmental justice, health equity, and political science, by linking with ZIP Code-level demographic and medical data sets, including national inpatient care records, medical claims data, census data, U.S. Census Bureau American CommUnity Survey (ACS), and Area Deprivation Index (ADI). The data are particularly useful for studies on rural populations who are under-represented due to the lack of air monitoring sites in rural areas. Compared with the 1km grid data, the ZIP Code-level predictions are much smaller in size and are manageable in personal computing environments. This greatly improves the inclusion of scientists in different fields by lowering the key barrier to participation in air pollution research. The Units are ug/m^3 for PM2.5 and ppb for O3 and NO2.

TIGER road data for the MSA. When compared to high-resolution imagery and other transportation datasets positional inaccuracies were observed. As a result caution should be taken when using this dataset. TIGER, TIGER/Line, and Census TIGER are registered trademarks of the U.S. Census Bureau. ZCTA is a trademark of the U.S. Census Bureau. The Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States, Puerto Rico, and the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The boundary information in the TIGER/Line files are for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement. The Census 2000 TIGER/Line files do NOT contain the Census 2000 urban areas which have not yet been delineated. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

Longitude and latitude, state, address, name, and zip code of Farmers Markets in the United States, converted to RDF format.

References 154 URIs in DBPedia, GovTrack, and Geonames.

7,223 farmers market URIs dereference to RDF/XML (e.g., see vapour report for farmersMarket_1019).

TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

Summary

Rail Crossings is a spatial file maintained by the Federal Railroad Administration (FRA) for use by States and railroads.

Description

FRA Grade Crossings is a spatial file that originates from the National Highway-Rail Crossing, Inventory Program. The program is to provide information to Federal, State, and local governments, as well as the railroad industry for the improvements of safety at highway-rail crossing.

Credits

Federal Railroad Administration (FRA)

Use limitations

There are no access and use limitations for this item.

Extent

West -79.491008 East -75.178954 North 39.733500 South 38.051719

Scale Range Maximum (zoomed in) 1:5,000 Minimum (zoomed out) 1:150,000,000

ArcGIS Metadata ▼►Topics and Keywords ▼►Themes or categories of the resource  transportation

* Content type  Downloadable Data Export to FGDC CSDGM XML format as Resource Description No

Temporal keywords  2013

Theme keywords  Rail

Theme keywords  Grade Crossing

Theme keywords  Rail Crossings

Citation ▼►Title rr_crossings Creation date 2013-03-15 00:00:00

Presentation formats  * digital map

Citation Contacts ▼►Responsible party  Individual's name Raquel Hunt Organization's name Federal Railroad Administration (FRA) Contact's position GIS Program Manager Contact's role  custodian

Responsible party  Organization's name Research and Innovative Technology Administration/Bureau of Transportation Statistics Individual's name National Transportation Atlas Database (NTAD) 2013 Contact's position Geospatial Information Systems Contact's role  distributor

Contact information  ▼►Phone  Voice 202-366-DATA

Address  Type  Delivery point 1200 New Jersey Ave. SE City Washington Administrative area DC Postal code 20590 e-mail address answers@BTS.gov

Resource Details ▼►Dataset languages  * English (UNITED STATES) Dataset character set  utf8 - 8 bit UCS Transfer Format

Spatial representation type  * vector

* Processing environment Microsoft Windows 7 Version 6.1 (Build 7600) ; Esri ArcGIS 10.2.0.3348

Credits Federal Railroad Administration (FRA)

ArcGIS item properties  * Name USDOT_RRCROSSINGS_MD * Size 0.047 Location withheld * Access protocol Local Area Network

Extents ▼►Extent  Geographic extent  Bounding rectangle  Extent type  Extent used for searching * West longitude -79.491008 * East longitude -75.178954 * North latitude 39.733500 * South latitude 38.051719 * Extent contains the resource Yes

Extent in the item's coordinate system  * West longitude 611522.170675 * East longitude 1824600.445629 * South latitude 149575.449134 * North latitude 752756.624659 * Extent contains the resource Yes

Resource Points of Contact ▼►Point of contact  Individual's name Raquel Hunt Organization's name Federal Railroad Administration (FRA) Contact's position GIS Program Manager Contact's role  custodian

Resource Maintenance ▼►Resource maintenance  Update frequency  annually

Resource Constraints ▼►Constraints  Limitations of use There are no access and use limitations for this item.

Spatial Reference ▼►ArcGIS coordinate system  * Type Projected * Geographic coordinate reference GCS_North_American_1983_HARN * Projection NAD_1983_HARN_StatePlane_Maryland_FIPS_1900_Feet * Coordinate reference details  Projected coordinate system  Well-known identifier 2893 X origin -120561100 Y origin -95444400 XY scale 36953082.294548117 Z origin -100000 Z scale 10000 M origin -100000 M scale 10000 XY tolerance 0.0032808333333333331 Z tolerance 0.001 M tolerance 0.001 High precision true Latest well-known identifier 2893 Well-known text PROJCS["NAD_1983_HARN_StatePlane_Maryland_FIPS_1900_Feet",GEOGCS["GCS_North_American_1983_HARN",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",1312333.333333333],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-77.0],PARAMETER["Standard_Parallel_1",38.3],PARAMETER["Standard_Parallel_2",39.45],PARAMETER["Latitude_Of_Origin",37.66666666666666],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2893]]

Reference system identifier  * Value 2893 * Codespace EPSG * Version 8.1.1

Spatial Data Properties ▼►Vector  ▼►* Level of topology for this dataset  geometry only

Geometric objects  Feature class name USDOT_RRCROSSINGS_MD * Object type  point * Object count 1749

ArcGIS Feature Class Properties  ▼►Feature class name USDOT_RRCROSSINGS_MD * Feature type Simple * Geometry type Point * Has topology FALSE * Feature count 1749 * Spatial index TRUE * Linear referencing FALSE

Data Quality ▼►Scope of quality information  ▼►Resource level  attribute Scope description  Attributes The States and railroads maintain their own file and get updated to the FRA. The information is reported to the FRA on the U.S. DOT-ARR Crossing inventory form.

Attributes The quality of the inventory can vary because a record of grade crossing location is being maintained by each state and railroad that is responsible for maintaining its respective information.

Lineage ▼►Lineage statement The data was downloaded from the HWY-Rail Crossing Inventory Files. All crossings that were closed or abandon were queried out of the data. All of the crossings with a zero within the latitude or longitude were queried out. Any crossing outside a bounding box of box ((Latitude >= 18 & Latitude <= 72) AND (Longitude >= -171 & Longitude <= -63)) were queried out.

Geoprocessing history ▼►Process  Date 2013-08-14 10:41:15 Tool location c:\program files (x86)\arcgis\desktop10.0\ArcToolbox\Toolboxes\Data Management Tools.tbx\Project Command issued Project RR_CROSSINGS_MD_USDOT \shagbfs\gis_projects\Railroad_Crossings_MD\Railroad_Crossings_MD.gdb\RR_CROSSINGS_MD_USDOT_83FTHARN PROJCS['NAD_1983_HARN_StatePlane_Maryland_FIPS_1900_Feet',GEOGCS['GCS_North_American_1983_HARN',DATUM['D_North_American_1983_HARN',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Lambert_Conformal_Conic'],PARAMETER['False_Easting',1312333.333333333],PARAMETER['False_Northing',0.0],PARAMETER['Central_Meridian',-77.0],PARAMETER['Standard_Parallel_1',38.3],PARAMETER['Standard_Parallel_2',39.45],PARAMETER['Latitude_Of_Origin',37.66666666666666],UNIT['Foot_US',0.3048006096012192]] WGS_1984_(ITRF00)_To_NAD_1983_HARN GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.25722356]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]] Include in lineage when exporting metadata No

Distribution ▼►Distributor  ▼►Contact information  Individual's name Office of Geospatial Information Systems Organization's name Research and Innovative Technology Administration's Bureau of Transportation Statistics (RITA/BTS) Contact's role  distributor

Contact information  ▼►Phone  Voice 202-366-DATA

Address  Type  Delivery point 1200 New Jersey Ave. SE City Washington Administrative area DC Postal code 20590 Country US e-mail address answers@bts.gov

Available format  Name Shapefile Version 2013 File decompression technique no compression applied

Ordering process  Instructions Call (202-366-DATA), or E-mail (answers@bts.gov) RITA/BTS to request the National Transportation Atlas Databases (NTAD) 2013 DVD. The NTAD DVD can be ordered from the online bookstore at www.bts.gov. Individual datasets from the NTAD can also be downloaded from the Office of Geospatial Information Systems website at http://www.bts.gov/programs/geographic_information_services/

Transfer options  Transfer size 6.645

Medium of distribution  Medium name  DVD

How data is written  iso9660 (CD-ROM) Recording density 650 Density units of measure Megabytes

Transfer options  Online source  Description  National Transportation Atlas Databases (NTAD) 2013

Distribution format  * Name Shapefile Version 2013

Transfer options  * Transfer size 0.047

Online source  Location http://www.bts.gov/programs/geographic_information_services/

Fields ▼►Details for object USDOT_RRCROSSINGS_MD ▼►* Type Feature Class * Row count 1749

Field FID ▼►* Alias FID * Data type OID * Width 4 * Precision 0 * Scale 0 * Field description Internal feature number.

* Description source ESRI

* Description of values Sequential unique whole numbers that are automatically generated.

Field Shape ▼►* Alias Shape * Data type Geometry * Width 0 * Precision 0 * Scale 0 * Field description Feature geometry.

* Description source ESRI

* Description of values Coordinates defining the features.

Field OBJECTID ▼►* Alias OBJECTID * Data type Integer * Width 9 * Precision 9 * Scale 0

Field CROSSING ▼►* Alias CROSSING * Data type String * Width 7 * Precision 0 * Scale 0 Field description US DOT Valid Crossing ID Number

Description source FRA

Field RAILROAD ▼►* Alias RAILROAD * Data type String * Width 4 * Precision 0 * Scale 0 Field description The

Longitude and latitude, state, address, name, and zip code of Farmers Markets in the United States