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TwitterThis dataset is a compilation of address point data for the City of Tempe. The dataset contains a point location, the official address (as defined by The Building Safety Division of Community Development) for all occupiable units and any other official addresses in the City. There are several additional attributes that may be populated for an address, but they may not be populated for every address. Contact: Lynn Flaaen-Hanna, Development Services Specialist Contact E-mail Link: Map that Lets You Explore and Export Address Data Data Source: The initial dataset was created by combining several datasets and then reviewing the information to remove duplicates and identify errors. This published dataset is the system of record for Tempe addresses going forward, with the address information being created and maintained by The Building Safety Division of Community Development.Data Source Type: ESRI ArcGIS Enterprise GeodatabasePreparation Method: N/APublish Frequency: WeeklyPublish Method: AutomaticData Dictionary
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Maintaining accurate data is a concern of all GIS users. The geodatabase offers you the ability to create geographic features that represent the real world. As the real world changes, you must update these features and their attributes. When creating or updating data, you can add behavior to your features and other objects to minimize the potential for errors.After completing this course, you will be able to:Define the two types of attribute domains and discuss how they differ.Create attribute domains and use them when editing data.Create subtypes and use them when editing data.Explain the difference between an attribute domain and a subtype.
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TwitterThis is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.
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TwitterThe FDOT GIS Roads with Median Types feature class provides spatial information on Florida Median Types distinguishing between lawn, paved, painted, and curbed medians. It also notes where a fence, guardrail, or barrier wall divides the two sides of a divided road. A median is defined as a barrier or other physical separation between two lanes of traffic traveling in opposite directions, which can either be raised, painted, or paved. This information is required for all functionally classified roadways On or Off the SHS. This dataset is maintained by the Transportation Data & Analytics office (TDA). The source spatial data for this hosted feature layer was created on: 11/08/2025.For more details please review the FDOT RCI Handbook Download Data: Enter Guest as Username to download the source shapefile from here: https://ftp.fdot.gov/file/d/FTP/FDOT/co/planning/transtat/gis/shapefiles/median_type.zip
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TwitterThis layer shows Households by Type. This is shown by state and county boundaries. This service contains the 2018-2022 release of data from the 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 Average Household Size and the Total Households in a bi-variate map. 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: 2018-2022ACS Table(s): B11001, B25010, B25044, DP02, DP04Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 18, 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. 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:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. 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 Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. 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.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.
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Twitterhttps://data.syrgov.net/pages/termsofusehttps://data.syrgov.net/pages/termsofuse
Urban Tree Canopy Assessment. This was created using the Urban Tree Canopy Syracuse 2010 (All Layers) file HERE.The data for this map was created using LIDAR and other spatial analysis tools to identify and measure tree canopy in the landscape. This was a collaboration between the US Forest Service Northern Research Station (USFS), the University of Vermont Spatial Laboratory, and SUNY ESF. Because the full map is too large to be viewed in ArcGIS Online, this has been reduced to a vector tile layer to allow it to be viewed online. To download and view the shapefiles and all of the layers, you can download the data HERE and view this in either ArcGIS Pro or QGIS.Data DictionaryDescription source USDA Forest ServiceList of values Value 1 Description Tree CanopyValue 2 Description Grass/ShrubValue 3 Description Bare SoilValue 4 Description WaterValue 5 Description BuildingsValue 6 Description Roads/RailroadsValue 7 Description Other PavedField Class Alias Class Data type String Width 20Geometric objects Feature class name landcover_2010_syracusecity Object type complex Object count 7ArcGIS Feature Class Properties Feature class name landcover_2010_syracusecity Feature type Simple Geometry type Polygon Has topology FALSE Feature count 7 Spatial index TRUE Linear referencing FALSEDistributionAvailable format Name ShapefileTransfer options Transfer size 163.805Description Downloadable DataFieldsDetails for object landcover_2010_syracusecityType Feature Class Row count 7 Definition UTCField FIDAlias FID Data type OID Width 4 Precision 0 Scale 0Field descriptionInternal feature number.Description source ESRIDescription of valueSequential unique whole numbers that are automatically generated.Field ShapeAlias Shape Data type Geometry Width 0 Precision 0 Scale 0Field description Feature geometry.Description source ESRIDescription of values Coordinates defining the features.Field CodeAlias Code Data type Number Width 4Overview Description Metadata DetailsMetadata language English Metadata character set utf8 - 8 bit UCS Transfer FormatScope of the data described by the metadata dataset Scope name datasetLast update 2011-06-02ArcGIS metadata properties Metadata format ArcGIS 1.0 Metadata style North American Profile of ISO19115 2003Created in ArcGIS for the item 2011-06-02 16:48:35 Last modified in ArcGIS for the item 2011-06-02 16:44:43Automatic updates Have been performed Yes Last update 2011-06-02 16:44:43Item location history Item copied or moved 2011-06-02 16:48:35 From T:\TestSites\NY\Syracuse\Temp\landcover_2010_syracusecity To \T7500\F$\Export\LandCover_2010_SyracuseCity\landcover_2010_syracusecity
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TwitterThe files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. were derived from the NVC. NatureServe developed a preliminary list of potential vegetation types. These data were combined with existing plot data (Cully 2002) to derive an initial list of potential types. Additional data and information were gleaned from a field visit and incorporated into the final list of map units. Because of the park’s small size and the large amount of field data, the map units are equivalent to existing vegetation associations or local associations/descriptions (e.g., Prairie Dog Colony). In addition to vegetation type, vegetation structures were described using three attributes: height, coverage density, and coverage pattern. In addition to vegetation structure and context, a number of attributes for each polygon were stored in the associated table within the GIS database. Many of these attributes were derived from the photointerpretation; others were calculated or crosswalked from other classifications. Table 2.7.2 shows all of the attributes and their sources. Anderson Level 1 and 2 codes are also included (Anderson et al. 1976). These codes should allow for a more regional perspective on the vegetation types. Look-up tables for the names associated with the codes is included within the geodatabase and in Appendix D. The look-up tables contain all the NVC formation information as well as alliance names, unique IDs, and the ecological system codes (El_Code) for the associations. These El_Codes often represent a one-to-many relationship; that is, one association may be related to more than one ecological system. The NatureServe conservation status is included as a separate item. Finally, slope (degrees), aspect, and elevation were calculated for each polygon label point using a digital elevation model and an ArcView script. The slope figure will vary if one uses a TIN (triangulated irregular network) versus a GRID (grid-referenced information display) for the calculation (Jenness 2005). A grid was used for the slope figure in this dataset. Acres and hectares were calculated using XTools Pro for ArcGIS Desktop.
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TwitterMore Metadata This feature class contains the basic expected land uses, or place types, for specific areas for all of Loudoun County. The place type approach concentrates on the context of any area instead of typical land use categories and corresponding specific uses. Each place type category defines the basis expected land use for an area, but also the preferred development patterns, streetscapes, and design features to make each area visually distinctive and functional. Place types also provide greater flexibility in development than the previous planned land use approach.This purpose of this feature class is to reference the planned place types, or expected land uses in certain areas, as reflected by the Loudoun County 2019 Comprehensive Plan, which was adopted on June 20, 2019. The data is used extensively by both the Department of Planning, Building and Development but is administered by the Department of Planning. This place type layer is to be used in place of the previous planned land use layer that was retired with the adoption of the 2019 Comprehensive Plan.
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TwitterSnake River Plain Play Fairway Analysis - Phase 1 CRS Raster Files. This dataset contains raster files created in ArcGIS. These raster images depict Common Risk Segment (CRS) maps for HEAT, PERMEABILITY, AND SEAL, as well as selected maps of Evidence Layers. These evidence layers consist of either Bayesian krige functions or kernel density functions, and include: (1) HEAT: Heat flow (Bayesian krige map), Heat flow standard error on the krige function (data confidence), volcanic vent distribution as function of age and size, groundwater temperature (equivalue interval and natural breaks bins), and groundwater T standard error. (2) PERMEABILTY: Fault and lineament maps, both as mapped and as kernel density functions, processed for both dilational tendency (TD) and slip tendency (ST), along with data confidence maps for each data type. Data types include mapped surface faults from USGS and Idaho Geological Survey data bases, as well as unpublished mapping; lineations derived from maximum gradients in magnetic, deep gravity, and intermediate depth gravity anomalies. (3) SEAL: Seal maps based on presence and thickness of lacustrine sediments and base of SRP aquifer. Raster size is 2 km. All files generated in ArcGIS.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This feature contains vector lines representing the shoreline and coastal habitats of California. Line segments are classified according to the Environmental Sensitivity Index (ESI) classification system and are a compilation of the ESI data from the most recent ESI atlas publications. The ESI data includes information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. This California dataset contains only the ESI shoreline data layer and is a merged set of individual ESI data sets to cover the entire California coast. For many parts of the California shoreline, the NOAA-ESI database lists several shoreline types present at a given location, described from landward to seaward. A simplified singular classification [Map_Class] was created to generalize the most dominant features of the multiple shore type attributes present in the raw data. More information can be found at the source citation at ESI Guidelines | response.restoration.noaa.gov Attributes: Line: Type of geographic feature (H: Hydrography, P: Pier, S: Shoreline) Most_sensitive: If multiple shoreline types appear in ESI classification, this field represents the highest value (most sensitive type); otherwise it is the same value as the ESI field. Shore_code: The ESI shoreline type. In many cases shorelines are ranked with multiple codes, such as "6B/3A" (listed landward to seaward). Source: Original year of ESI data. Esi_description: Concatenation of shore type descriptions (listed landward to seaward) Shoretype_1: Numeric classification for the first (most landward) ESI type. Shoretype_1_name: Physical description for the first ESI type. Shoretype_2: Numeric classification for the second ESI type. Shoretype_2_name: Physical description for the second ESI type Shoretype_3: Numeric classification for the third (most seaward) ESI type. Shoretype_3_name: Physical description for the third ESI type. Map_class: Generalized ESI shoreline type for simplified sym
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TwitterThis dataset contains soil type and soil classification, by area.
This dataset is harvested on a weekly basis from Allegheny County’s GIS data portal. The full metadata record for this dataset can also be found on Allegheny County's GIS portal. You can access the metadata record and other resources on the GIS portal by clicking on the "Explore button (and choosing the "Go to resource" option) to the right of the "ArcGIS Open Dataset" text below.
Category: Environment
Department: Geographic Information Systems Group; Department of Administrative Services
Development Notes: This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties. The soil map and data used in the SSURGO product were prepared by soil scientists as part of the National Cooperative Soil Survey.
Related Documents: Data Dictionary for SOIL_CODE, https://www.nrcs.usda.gov/Internet/FSE_MANUSCRIPTS/pennsylvania/PA003/0/legends.pdf (the last page includes the soil legend for this dataset)
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TwitterThe Spatiotemporal Big Data Store Tutorial introduces you the the capabilities of the spatiotemporal big data store in ArcGIS Data Store, available with ArcGIS Enterprise. Observation data can be moving objects, changing attributes of stationary sensors, or both. The spatiotemporal big data store enables archival of high volume observation data, sustains high velocity write throughput, and can run across multiple machines (nodes). Adding additional machines adds capacity, enabling you to store more data, implement longer retention policies of your data, and support higher data write throughput.
After completing this tutorial you will:
Understand the concepts and best practices for working with the spatiotemporal big data store available with ArcGIS Data Store. Have configured the appropriate security settings and certificates on a enterprise server, real-time server, and a data server which are necessary for working with the spatiotemporal big data store. Have learned how to process and archive large amounts of observational data in the spatiotemporal big data store. Have learned how to visualize the observational data that is stored in the spatiotemporal big data store.
Releases
Each release contains a tutorial compatible with the version of GeoEvent Server listed. The release of the component you deploy does not have to match your version of ArcGIS GeoEvent Server, so long as the release of the component is compatible with the version of GeoEvent Server you are using. For example, if the release contains a tutorial for version 10.6; this tutorial is compatible with ArcGIS GeoEvent Server 10.6 and later. Each release contains a Release History document with a compatibility table that illustrates which versions of ArcGIS GeoEvent Server the component is compatible with.
NOTE: The release strategy for ArcGIS GeoEvent Server components delivered in the ArcGIS GeoEvent Server Gallery has been updated. Going forward, a new release will only be created when
a component has an issue,
is being enhanced with new capabilities,
or is not compatible with newer versions of ArcGIS GeoEvent Server.
This strategy makes upgrades of these custom
components easier since you will not have to
upgrade them for every version of ArcGIS GeoEvent Server
unless there is a new release of
the component. The documentation for the
latest release has been
updated and includes instructions for updating
your configuration to align with this strategy.
Latest
Release 4 - February 2, 2017 - Compatible with ArcGIS GeoEvent Server 10.5 and later.
Previous
Release 3 - July 7, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.
Release 2 - May 17, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.
Release 1 - March 18, 2016 - Compatible with ArcGIS GeoEvent Server 10.4 thru 10.8.
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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
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This file contains the 65 cities and towns in Massachusetts for which MBTA bus or rapid transit service is provided. This data is based off of the 2010 census. The legislative intent for some boundaries could not be mapped. Boundaries where that is true are identified in the attribute information. Name Description Data Type Example town_name Full name for the MA town or city identification. String Boston town_id MassGIS Town-ID Code (alphabetical, 1-351) Numeric 34 sum_acres Area covered by the town or city in acres. Double 31304.22 sum_square Area covered by the town or city in square miles. Double 48.91 Use constraints: This data set, like all other cartographic products may contain inherent aberrations in geography or thematical errors. The boundaries included in this data set were developed using accepted GIS methodology. Cartographic products can never truly represent real-world conditions due to several factors. These factors can include, but are not limited to: human error upon digitizing, computational tolerance of the computer, or the distortion of map symbology. Because of these factors MassGIS cannot be held legally responsible for personal or property damages resulting from any type of use of the data set. These boundaries are suitable for map display and planning purposes. They cannot be used as a substitute for the work of a professional land surveyor.MassDOT/MBTA shall not be held liable for any errors in this data. This includes errors of omission, commission, errors concerning the content of the data, and relative and positional accuracy of the data. This data cannot be construed to be a legal document. Primary sources from which this data was compiled must be consulted for verification of information contained in this data.
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TwitterThis dataset represents the road density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. This data set is derived from TIGER/Line Files of roads in the conterminous United States. Road density describes how many kilometers of road exist in a square kilometer. A raster was produced using the ArcGIS Line Density Tool to form the landscape layer for analysis. The (kilometer of road/square kilometer) was summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The purpose of this dataset is to display the extent of existing Terrestrial Ecological Unit inventory (TEUI) data internally to facilitate inter-agency collaboration. The feature class for this dataset will display polygons of the ecological unit plots, acreages, and percent coverages of National Forest and Grassland administrative boundaries using their common names, with a percent coverage for Land Type and acres of forest per plot.Metadata and DownloadsThis record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService OGC WMS CSV Shapefile GeoJSON KML For complete information, please visit https://data.gov.
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TwitterThis table maps subproject ID to type of allocation (Round 1 Projects, Revenue Replacement Projects, or Program Delivery). -- Additional Information: Category: ARPA Update Frequency: As necessary-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=60940
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TwitterThe files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. ArcGIS software was used as the GIS platform for the onscreen digital mapping. Because the 3D images were viewed directly in the GIS environment, vegetation could be mapped directly into ArcGIS. The polygon vector data were stored using an ArcGIS file geodatabase, which was projected in in Universal Transverse Mercator (UTM), Zone 15, by using the North American Datum of 1983 (NAD 83). The NPS VIP standard MMU of 0.5 ha was applied to mapping forest and cultural types. For shrub, herbaceous, and sparsely vegetated types, as well as non-vegetation features, a MMU of 0.25 ha was applied. This smaller MMU was applied because these vegetation types were comparatively rare across the park, the degree of vegetation diversity over small areas was higher, and the isolated patches across MISS were more prevalent. For woodlands, a MMU of 0.5 ha was applied to deciduous woodlands and a MMU of 0.25 ha was applied to conifer woodlands due to the individual circumstances surrounding these woodlands. Also, when vegetation types were found unique to their immediate surroundings (e.g., an herbaceous wetland within an upland forest), mapping below the MMU was allowed. All geospatial products for the MISS vegetation mapping project have been projected in UTM, Zone 15, by using the NAD 83.
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TwitterField Name Data Type Description
Statefp Number US Census Bureau unique identifier of the state
Countyfp Number US Census Bureau unique identifier of the county
Countynm Text County name
Tractce Number US Census Bureau unique identifier of the census tract
Geoid Number US Census Bureau unique identifier of the state + county + census tract
Aland Number US Census Bureau defined land area of the census tract
Awater Number US Census Bureau defined water area of the census tract
Asqmi Number Area calculated in square miles from the Aland
MSSAid Text ID of the Medical Service Study Area (MSSA) the census tract belongs to
MSSAnm Text Name of the Medical Service Study Area (MSSA) the census tract belongs to
Definition Text Type of MSSA, possible values are urban, rural and frontier.
TotalPovPop Number US Census Bureau total population for whom poverty status is determined of the census tract, taken from the 2020 ACS 5 YR S1701
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TwitterLocations of structures at and beneath the water surface used for the purpose of exploration and resource extraction. Only platforms in federal Outer Continental Shelf (OCS) waters are included. A database of platforms and rigs is maintained by BSEE.
© MarineCadastre.gov This layer is a component of BOEMRE Layers.
This Map Service contains many of the primary data types created by both the Bureau of Ocean Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) within the Department of Interior (DOI) for the purpose of managing offshore federal real estate leases for oil, gas, minerals, renewable energy, sand and gravel. These data layers are being made available as REST mapping services for the purpose of web viewing and map overlay viewing in GIS systems. Due to re-projection issues which occur when converting multiple UTM zone data to a single national or regional projected space, and line type changes that occur when converting from UTM to geographic projections, these data layers should not be used for official or legal purposes. Only the original data found within BOEM/BSEE’s official internal database, federal register notices or official paper or pdf map products may be considered as the official information or mapping products used by BOEM or BSEE. A variety of data layers are represented within this REST service are described further below. These and other cadastre information the BOEM and BSEE produces are generated in accordance with 30 Code of Federal Regulations (CFR) 256.8 to support Federal land ownership and mineral resource management.
For more information – Contact: Branch Chief, Mapping and Boundary Branch, BOEM, 381 Elden Street, Herndon, VA 20170. Telephone (703) 787-1312; Email: mapping.boundary.branch@boem.gov
The REST services for National Level Data can be found here:
http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE/MMC_Layers/MapServer
REST services for regional level data can be found by clicking on the region of interest from the following URL:
http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE
Individual Regional Data or in depth metadata for download can be obtained in ESRI Shape file format by clicking on the region of interest from the following URL:
http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx
Currently the following layers are available from this REST location:
OCS Drilling Platforms -Locations of structures at and beneath the water surface used for the purpose of exploration and resource extraction. Only platforms in federal Outer Continental Shelf (OCS) waters are included. A database of platforms and rigs is maintained by BSEE.
OCS Oil and Natural Gas Wells -Existing wells drilled for exploration or extraction of oil and/or gas products. Additional information includes the lease number, well name, spud date, the well class, surface area/block number, and statistics on well status summary. Only wells found in federal Outer Continental Shelf (OCS) waters are included. Wells information is updated daily. Additional files are available on well completions and well tests. A database of wells is maintained by BSEE.
OCS Oil & Gas Pipelines -This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.
Unofficial State Lateral Boundaries - The approximate location of the boundary between two states seaward of the coastline and terminating at the Submerged Lands Act Boundary. Because most State boundary locations have not been officially described beyond the coast, are disputed between states or in some cases the coastal land boundary description is not available, these lines serve as an approximation that was used to determine a starting point for creation of BOEM’s OCS Administrative Boundaries. GIS files are not available for this layer due to its unofficial status.
BOEM OCS Administrative Boundaries - Outer Continental Shelf (OCS) Administrative Boundaries Extending from the Submerged Lands Act Boundary seaward to the Limit of the United States OCS (The U.S. 200 nautical mile Limit, or other marine boundary)For additional details please see the January 3, 2006 Federal Register Notice.
BOEM Limit of OCSLA ‘8(g)’ zone - The Outer Continental Shelf Lands Act '8(g) Zone' lies between the Submerged Lands Act (SLA) boundary line and a line projected 3 nautical miles seaward of the SLA boundary line. Within this zone, oil and gas revenues are shared with the coastal state(s). The official version of the ‘8(g)’ Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction described below.
Submerged Lands Act Boundary - The SLA boundary defines the seaward limit of a state's submerged lands and the landward boundary of federally managed OCS lands. The official version of the SLA Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction Diagrams described below.
Atlantic Wildlife Survey Tracklines(2005-2012) - These data depict tracklines of wildlife surveys conducted in the Mid-Atlantic region since 2005. The tracklines are comprised of aerial and shipboard surveys. These data are intended to be used as a working compendium to inform the diverse number of groups that conduct surveys in the Mid-Atlantic region.The tracklines as depicted in this dataset have been derived from source tracklines and transects. The tracklines have been simplified (modified from their original form) due to the large size of the Mid-Atlantic region and the limited ability to map all areas simultaneously.The tracklines are to be used as a general reference and should not be considered definitive or authoritative. This data can be downloaded from http://www.boem.gov/uploadedFiles/BOEM/Renewable_Energy_Program/Mapping_and_Data/ATL_WILDLIFE_SURVEYS.zip
BOEM OCS Protraction Diagrams & Leasing Maps - This data set contains a national scale spatial footprint of the outer boundaries of the Bureau of Ocean Energy Management’s (BOEM’s) Official Protraction Diagrams (OPDs) and Leasing Maps (LMs). It is updated as needed. OPDs and LMs are mapping products produced and used by the BOEM to delimit areas available for potential offshore mineral leases, determine the State/Federal offshore boundaries, and determine the limits of revenue sharing and other boundaries to be considered for leasing offshore waters. This dataset shows only the outline of the maps that are available from BOEM.Only the most recently published paper or pdf versions of the OPDs or LMs should be used for official or legal purposes. The pdf maps can be found by going to the following link and selecting the appropriate region of interest.
http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx Both OPDs and LMs are further subdivided into individual Outer Continental Shelf(OCS) blocks which are available as a separate layer. Some OCS blocks that also contain other boundary information are known as Supplemental Official Block Diagrams (SOBDs.) Further information on the historic development of OPD's can be found in OCS Report MMS 99-0006: Boundary Development on the Outer Continental Shelf: http://www.boemre.gov/itd/pubs/1999/99-0006.PDF Also see the metadata for each of the individual GIS data layers available for download. The Official Protraction Diagrams (OPDs) and Supplemental Official Block Diagrams (SOBDs), serve as the legal definition for BOEM offshore boundary coordinates and area descriptions.
BOEM OCS Lease Blocks - Outer Continental Shelf (OCS) lease blocks serve as the legal definition for BOEM offshore boundary coordinates used to define small geographic areas within an Official Protraction Diagram (OPD) for leasing and administrative purposes. OCS blocks relate back to individual Official Protraction Diagrams and are not uniquely numbered. Only the most recently published paper or pdf versions of the OPDs or LMs or SOBDs should be used for official or legal purposes. The pdf
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TwitterThis dataset is a compilation of address point data for the City of Tempe. The dataset contains a point location, the official address (as defined by The Building Safety Division of Community Development) for all occupiable units and any other official addresses in the City. There are several additional attributes that may be populated for an address, but they may not be populated for every address. Contact: Lynn Flaaen-Hanna, Development Services Specialist Contact E-mail Link: Map that Lets You Explore and Export Address Data Data Source: The initial dataset was created by combining several datasets and then reviewing the information to remove duplicates and identify errors. This published dataset is the system of record for Tempe addresses going forward, with the address information being created and maintained by The Building Safety Division of Community Development.Data Source Type: ESRI ArcGIS Enterprise GeodatabasePreparation Method: N/APublish Frequency: WeeklyPublish Method: AutomaticData Dictionary