The ArcGIS World Geocoding Service finds addresses and places in all supported countries around the world in a single geocoding service. The service can find point locations of addresses, cities, landmarks, business names, and other places. The output points can be visualized on a map, inserted as stops for a route, or loaded as input for a spatial analysis.The service is available as both a geosearch and geocoding service:Geosearch Services – The primary purpose of geosearch services is to locate a feature or point of interest and then have the map zoom to that location. The result might be displayed on the map, but the result is not stored in any way for later use. Requests of this type do not require a subscription or a credit fee. Geocoding Services – The primary purpose of geocoding services is to convert an address to an x,y coordinate and append the result to an existing record in a database. Mapping is not always involved, but placing the results on a map may be part of a workflow. Batch geocoding falls into this category. Geocoding requires a subscription. An ArcGIS Online Subscription, or ArcGIS Location Platform Subscription, will provide you access to the ArcGIS World Geocoding service for batch geocoding.The service can be used to find address and places for many countries around the world. For detailed information on this service, including a data coverage map, visit the ArcGIS World Geocoding service documentation.

It is an ArcGIS multirole locator with two roles:

1. Point Address - Generally more accurate results from rooftop location points. Includes a Subaddress if a unit number is located.
   
2. Street Address - Less accurate results from an estimated distance along a street centerline address range if a Point Address was not found.

Instructions for using the Geocoder via ArcGIS Pro, ArcGIS Online, and REST Services are below:

ArcGIS Pro
Web Services
ArcGIS Online

A comprehensive self-hosted geospatial database of street names, coordinates, and address data ranges for Enterprise use. The address data are georeferenced with industry-standard WGS84 coordinates (geocoding).

All geospatial data are provided in the official local languages. Names and other data in non-Roman languages are also made available in English through translations and transliterations.

Use cases for the Global Address Database (Geospatial data)

• Address capture and validation

• Parcel delivery

• Master Data Management

• Logistics and Shipping

• Sales and Marketing

Additional features

• Fully and accurately geocoded

• Multi-language support

• Address ranges for streets covered by several zip codes

• Comprehensive city definitions across countries

• Administrative areas with a level range of 0-4

• International Address Formats

For additional insights, you can combine the map data with:

• UNLOCODE and IATA codes (geocoded)

• Time zones and Daylight Saving Time (DST)

• Population data: Past and future trends

Data export methodology

Our location data packages are offered in CSV format. All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why companies choose our location databases

• Enterprise-grade service

• Reduce integration time and cost by 30%

• Frequent, consistent updates for the highest quality

Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

Regional Address Points with Latitude and Longitude

This Africa Geocoding locator is a view of the World Geocoding Service constrained to search for places in the countries of Africa. The World Geocoding Service finds addresses and places in all supported countries around the world in a single geocoding service. The service can find point locations of addresses, cities, landmarks, business names, and other places. The output points can be visualized on a map, inserted as stops for a route, or loaded as input for a spatial analysis.The service is available as both a geosearch and geocoding service:Geosearch Services – The primary purpose of geosearch services is to locate a feature or point of interest and then have the map zoom to that location. The result might be displayed on the map, but the result is not stored in any way for later use. Requests of this type do not require a subscription or a credit fee. Geocoding Services – The primary purpose of geocoding services is to convert an address to an x,y coordinate and append the result to an existing record in a database. Mapping is not always involved, but placing the results on a map may be part of a workflow. Batch geocoding falls into this category. Geocoding requires a subscription. An ArcGIS Online subscription will provide you access to the World Geocoding service for batch geocoding.The service can be used to find address and places for many countries around the world. For detailed information on this service, including a data coverage map, visit the World Geocoding service documentation.

A comprehensive self-hosted geospatial database of international address data, including street names, coordinates, and address data ranges for Enterprise use. The address data are georeferenced with industry-standard WGS84 coordinates (geocoding).

All address data are provided in the official local languages. Names and other data in non-Roman languages are also made available in English through translations and transliterations.

Use cases for the Global Address Database (Geospatial data/Map Data)

• Address Data Enrichment

• Address capture and validation

• Parcel delivery

• Master Data Management

• Logistics and Shipping

• Sales and Marketing

Product Features

• Fully and accurately geocoded

• Multi-language support

• Address ranges for streets covered by several zip codes

• Comprehensive city definitions across countries

• Administrative areas with a level range of 0-4

• International Address Formats

For additional insights, you can combine the map data with:

• UNLOCODE and IATA codes (geocoded)

• Time zones and Daylight Saving Time (DST)

• Population data: Past and future trends

Data export methodology

Our address data enrichment packages are offered in CSV format. All international address data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why do companies choose our location databases

• Enterprise-grade service

• Reduce integration time and cost by 30%

• Frequent, consistent updates for the highest quality

Note: Custom international address data packages are available. Please submit a request via the above contact button for more details.

The Street_and_Address_Composite will return a geographic coordinate when a street address is entered. A user can enter an address either manually or by bulk input from a database or other source.The geocoder returns a coordinate pair and standardized address for each input address it is able to match. The NYS ITS Geospatial Services geocoder uses a series of combinations of reference data and configuration parameters to optimize both the likelihood of a match and the quality of the results. The reference data supporting the geocoder is stored in Federal Geographic Data Committee (FGDC) standard.The first composite locator (Street_and_Address_Composite) is made up of the following set of locators which are most likely to return a high quality hit. The locators are listed in the order in which they will be accessed along with a brief description of the locator's source data. These six locators will generate the majority of the results when geocoding addresses.Locator NameSource DataDescription1A_SAM_AP_ZipNameSAM Address PointsSAM address points using the postal zip code name for the city name in the locator.1B_SAM_AP_CTNameSAM Address PointsSAM address points. The city or town name is used for the city name in the locator.1C_SAM_AP_PlaceNameSAM Address PointsSAM address points. The city name is populated using the NYS Villages and Indian Reservations, the Census Designated Places and Alternate Acceptable Zip Code Names from the USPS. These names do not exist everywhere so there will be a limited number of points in this locator.3A_SS_ZipNameNYS Street SegmentsNYS Street Segments dataset using the postal zip code name for the city name in the locator. The location is interpolated from an address range on the street segment. The city name can be different for the left and right sides of the streets.3B_SS_CTNameNYS Street SegmentsNYS Street Segments using the city or town name for the city name in the locator. The location is interpolated from an address range on the street segment.3C_SS_PlaceNameNYS Street SegmentsNYS Street Segments using an alternate place name for the city field. This field is populated using the NYS Villages and Indian Reservations, the Census Designated Places and Alternate Acceptable Zip Code Names from the USPS. These areas do not exist everywhere so there will be a limited number of segments with this attribute. The location is interpolated from an address range on the street segment.For more information about the geocoding service, please visit: https://gis.ny.gov/address-geocoder.For documentation on how to add these locators to ArcGIS, please reference Adding the Statewide Geocoding Web Service. If you would like these locators to be your default locators in ArcGIS, copy DefaultLocators.xml to C:\Users<username>\AppData\Roaming\ESRI\Desktop10.X\Locators, where

The Taichung City 113 GIS address number 1 to each month's version, due to the large file size, a total of about 14.4 million data per month, here is to obtain the explanatory file (field including: file name, description, file format, map URL, county city code, data description, usage instructions, scope description, etc.) From the "map URL" field of this explanatory file, download the original CSV file of the address, including provincial and city county codes, township town area codes, villages, lanes, streets, areas, lanes, alleys, numbers, TWD97 horizontal coordinates, TWD97 vertical coordinates, WGS84 longitude, WGS84 latitude.

Address Points (Secondary) is a Point FeatureClass representing secondary address points in the City of Cupertino. Secondary address points contain data for suites, units, apartments, etc. It is primarily used as a reference layer. The layer is updated as needed by the GIS Department. Address Points (Secondary) has the following fields: It is primarily used as a reference layer. The layer is updated as needed by the GIS division. Address Points (Secondary) has the following fields:

OBJECTID: Unique identifier automatically generated by Esri type: OID, length: 4, domain: none

APN: The Assessor's Parcel Number where the secondary address point is located type: String, length: 10, domain: none

Location: Further description of the location type: String, length: 36, domain: none

Address: The address of the feature type: String, length: 56, domain: none

House Number: The house number associated with the address type: String, length: 11, domain: none

Street Prefix: Prefix for the street nametype: String, length: 7, domain: AddressPrefix domain values:['S', 'E', 'W', 'N']

Street Name: Name of the street on which the address point is located type: String, length: 23, domain: none

Street Suffix: The suffix for the street name type: String, length: 7, domain: AddressSuffix domain values:['CMN', 'EXPY', 'LN', 'SQ', 'PLZ', 'PKWY', 'RD', 'CIR', 'LOOP', 'WAY', 'BLVD', 'AVE', 'TER', 'ST', 'DR', 'PL', 'CT']

Street Suffix Direction: The suffix for the direction of the street name type: String, length: 11, domain: AddressPrefix domain values:['S', 'E', 'W', 'N']

Unit Number: The unit number associated with the secondary address point type: String, length: 8, domain: none

City: The city in which the address is located type: String, length: 11, domain: AddressCity domain values:[]

State: The State in which the feature is located type: String, length: 7, domain: none

Comments: Any relevant comments relating to the feature type: String, length: 50, domain: none

Zip: The zip code associated with the feature type: String, length: 10, domain: none

Last Update: The date the database row was last updated type: Date, length: 8, domain: none

X: The X coordinate of the secondary address point type: Double, length: 8, domain: none

Y: The Y coordinate of the secondary address point type: Double, length: 8, domain: none

Floor: Floor number associated with the secondary address point type: SmallInteger, length: 2, domain: Floor domain values:['1', '2', '3', '4', '5', '6', '7', '8', '9', '10']

SHAPE: Field that stores geographic coordinates associated with feature type: Geometry, length: 4, domain: none

GlobalID: Unique identifier automatically generated for features in enterprise database type: GlobalID, length: 38, domain: none

AssetID: Cupertino maintained GIS primary key type: String, length: 50, domain: none

PlaceType: The use type of the facility at the address point type: String, length: 50, domain: AddressPlaceType domain values:['Educational', 'Transportation', 'Business', 'Government', 'Hospital', 'Recreational', 'Miscellaneous', 'Residential Single Family', 'Residential Multi Family']

Unit Type: The type of unit found at the secondary address point type: String, length: 5, domain: UNITS domain values:['STE', 'ELEC', 'VILLA', 'BLDG', 'APT', 'UNIT']

last_edited_date:

The date the database row was last updated type: Date, length: 8, domain: none

created_date:

The date the database row was initially created type: Date, length: 8, domain: none

Address, position and school form for the public schools of Skövde municipality.

Crowther_Nature_Files.zip This description pertains to the original download. Details on revised (newer) versions of the datasets are listed below. When more than one version of a file exists in Figshare, the original DOI will take users to the latest version, though each version technically has its own DOI. -- Two global maps (raster files) of tree density. These maps highlight how the number of trees varies across the world. One map was generated using biome-level models of tree density, and applied at the biome scale. The other map was generated using ecoregion-level models of tree density, and applied at the ecoregion scale. For this reason, transitions between biomes or between ecoregions may be unrealistically harsh, but large-scale estimates are robust (see Crowther et al 2015 and Glick et al 2016). At the outset, this study was intended to generate reliable estimates at broad spatial scales, which inherently comes at the cost of fine-scale precision. For this reason, country-scale (or larger) estimates are generally more robust than individual pixel-level estimates. Additionally, due to data limitations, estimates for Mangroves and Tropical coniferous forest (as identified by WWF and TNC) were generated using models constructed from Topical moist broadleaf forest data and Temperate coniferous forest data, respectively. Because we used ecological analogy, the estimates for these two biomes should be considered less reliable than those of other biomes . These two maps initially appeared in Crowther et al (2015), with the biome map being featured more prominently. Explicit publication of the data is associated with Glick et al (2016). As they are produced, updated versions of these datasets, as well as alternative formats, will be made available under Additional Versions (see below).

Methods: We collected over 420,000 ground-sources estimates of tree density from around the world. We then constructed linear regression models using vegetative, climatic, topographic, and anthropogenic variables to produce forest tree density estimates for all locations globally. All modeling was done in R. Mapping was done using R and ArcGIS 10.1.

Viewing Instructions: Load the files into an appropriate geographic information system (GIS). For the original download (ArcGIS geodatabase files), load the files into ArcGIS to view or export the data to other formats. Because these datasets are large and have a unique coordinate system that is not read by many GIS, we suggest loading them into an ArcGIS dataframe whose coordinate system matches that of the data (see File Format). For GeoTiff files (see Additional Versions), load them into any compatible GIS or image management program.

Comments: The original download provides a zipped folder that contains (1) an ArcGIS File Geodatabase (.gdb) containing one raster file for each of the two global models of tree density – one based on biomes and one based on ecoregions; (2) a layer file (.lyr) for each of the global models with the symbology used for each respective model in Crowther et al (2015); and an ArcGIS Map Document (.mxd) that contains the layers and symbology for each map in the paper. The data is delivered in the Goode homolosine interrupted projected coordinate system that was used to compute biome, ecoregion, and global estimates of the number and density of trees presented in Crowther et al (2015). To obtain maps like those presented in the official publication, raster files will need to be reprojected to the Eckert III projected coordinate system. Details on subsequent revisions and alternative file formats are list below under Additional Versions.----------

Additional Versions: Crowther_Nature_Files_Revision_01.zip contains tree density predictions for small islands that are not included in the data available in the original dataset. These predictions were not taken into consideration in production of maps and figures presented in Crowther et al (2015), with the exception of the values presented in Supplemental Table 2. The file structure follows that of the original data and includes both biome- and ecoregion-level models.

Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip contains Revision_01 of the biome-level model, but stored in WGS84 and GeoTiff format. This file was produced by reprojecting the original Goode homolosine files to WGS84 using nearest neighbor resampling in ArcMap. All areal computations presented in the manuscript were computed using the Goode homolosine projection. This means that comparable computations made with projected versions of this WGS84 data are likely to differ (substantially at greater latitudes) as a product of the resampling. Included in this .zip file are the primary .tif and its visualization support files.

References:

Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., Smith, J. R., Hintler, G., Duguid, M. C., Amatulli, G., Tuanmu, M. N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S. J., Wiser, S. K., Huber, M. O., Hengeveld, G. M., Nabuurs, G. J., Tikhonova, E., Borchardt, P., Li, C. F., Powrie, L. W., Fischer, M., Hemp, A., Homeier, J., Cho, P., Vibrans, A. C., Umunay, P. M., Piao, S. L., Rowe, C. W., Ashton, M. S., Crane, P. R., and Bradford, M. A. 2015. Mapping tree density at a global scale. Nature, 525(7568): 201-205. DOI: http://doi.org/10.1038/nature14967Glick, H. B., Bettigole, C. B., Maynard, D. S., Covey, K. R., Smith, J. R., and Crowther, T. W. 2016. Spatially explicit models of global tree density. Scientific Data, 3(160069), doi:10.1038/sdata.2016.69.

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"

The dataset contains locations and attributes of above ground permits applied for and approved by the District Department of Transportation. They are newly occupied constructions and events. Examples include: moving truck, roll off debris container, moving storage container, construction staging area, mobile crane work zone, other reserved parking. The public space permit process is described on the DDOT website https://ddot.dc.gov.These data are shared via an automated process where addresses are batch matched (geocoded) to the District's Master Address Repository. Users may find that some data points will contain 0,0 for X,Y coordinates resulting in inconsistent spatial locations. Addresses for these data points could not be automatically geocoded and will need to be manually geocoded to 'best fit' locations in DC. Use the MAR Geocoderto help complete this.

what3words is an addressing and location reference system based on a global grid of 57 trillion squares of 3mx3m; each square has a unique pre-assigned 3 word address. For example, crayon.giants.liking is a perfect spot in the Grand Canyon to take a picture of the Kaibab Suspension Bridge across the Colorado River. Poor addressing is frustrating & costly in developed countries, and it hampers the growth and development of many nations around the world. Street addressing is irregular and incomplete; finding an address and communicating it to others is still a very imperfect science. Whilst coordinates work well for many GIS professionals, they are error-prone and badly understood by non-GIS users, which prohibits their more widespread use.

Addressing just got easier “Geographical information is a fundamental business tool. A simple way to communicate location is essential to unleash its full potential for everyone, what3words has solved a major aspect of that, particularly in geographies that are disadvantaged with lack of addressing and place name description data.” said Jack Dangermond, President of Esri. “Addressing has just got easier.” Technically flexible The simple what3words system is now available as a locator, accessible via the industry-leading ArcGIS platform from Esri. The locator allows ArcGIS platform users to display the 3 word address for any location or search for a 3 word address, either individually or via batch conversion to and from coordinates. It makes full use of the Esri Geoinformation Model and is accessible online or offline, anywhere in the world. The what3words locator can be configured at an organization level, whatever the ArcGIS deployment model, so that any roles and users can access it across the entire ArcGIS platform.

Words beat alphanumeric codes “Using 3 words instead of long sequences of coordinates or complicated alphanumeric codes means that people can identify any location accurately and communicate it more quickly, more easily and with less ambiguity.” Chris Sheldrick, CEO what3words. “Our conversations with Esri partners and users have been overwhelmingly positive and those who have participated in our beta trials are keen to introduce what3words throughout their workflow.” Human communication The what3words system is non-sequential and non-hierarchical to ensure human communication errors are intercepted. The system distributes similar 3 word addresses far apart, often in different countries, to allow manual or automated error detection in real time.

Better addressing for everyone Better addressing can significantly improve customer experiences for the navigation, logistics, post, utilities, census and data collection sectors where inaccuracies and friction towards coordinates cause erroneous data, incomplete data and ambiguity. Municipalities and governments exchanging geographic data with their citizens will also benefit by introducing a system which can be easily understood by the general population. The human-friendly nature of 3 word addresses combined with the scale and reach of ArcGIS means not only that everywhere now has a simple address, but that absolutely everyone can use it. Learn more and access the locator at what3words.com/esri.

Note: This dataset is updated weekly. Dry Cleaning Facilities are points representing the locations of dry cleaning facilities regulated by NJDEP. The NJDEP New Jersey Environmental Management System (NJEMS) serves as the database that supplies coordinates and descriptive attributes from several tables used to generate this GIS layer. This layer is produced primarily for the NJDEP i-MapNJ ArcIMS interactive mapping web application and ArcGIS (ArcView, ArcInfo) users. Program interests included in NJEMS are: Air, Communications Center, Discharge Prevention, Exams and Licensing, Fish Game and Wildlife, Green Acres, Hazardous Waste, Lab Certification, Land Use, Landscape Irrigation, Parks and Forestry, Pesticides, Pinelands, Planning, Radiation, Right-to-Know, Site Remediation, Soil Conservation, Solid Waste, TCPA, Water Quality, Water Supply, and Watershed Management. The locations derived using GPS represent main entrance or front door locations for the sites. Users should note that not every site in NJEMS presently (as of June 2009) has an established coordinate (GPS or otherwise). NJDEP is continually working to acquire these with GPS, location data submitted to permitting programs, and through address matching techniques.

The dataset contains locations and attributes of building construction and alteration permits applied for and approved by the District of Columbia Department of Buildings. These data are shared via an automated process where addresses are batch matched (geocoded) to the District's Master Address Repository. Users may find that some data points will contain 0,0 for X,Y coordinates resulting in inconsistent spatial locations. Addresses for these data points could not be automatically geocoded and will need to be manually geocoded to 'best fit' locations in DC.

The State of Ohio Location Based Response System (LBRS) Address Points data provides for a spatially accurate placement of addresses within a given parcel in Delaware County. The data was created through a partnership between the State of Ohio and Delaware County. The data is maintained by Delaware County Auditor's GIS Office. The Address Points indicate the location of the building centroid as best as possible. The Address Points layer is intended to support appraisal mapping, 911 Emergency Response, accident reporting, geocoding, and disaster management. The layer provides the capability to reverse geocode a set of coordinates to determine the closest valid address and is intended to provide 911 agencies with information needed to comply with Phase II 911 requirements.

The Address Points layer offers precise geographic coordinates for address locations throughout Montgomery County. Each address point is associated with its respective latitude and longitude coordinates, enabling accurate spatial referencing and geolocation. Address points from this dataset are integrated into 9-1-1 Computer-Aided Dispatch (CAD) systems, enhancing navigation capabilities for emergency responders and facilitating rapid and efficient emergency response.This dataset is sourced from the Montgomery County Emergency Communications District (MCECD) and is updated monthly to ensure accuracy.Access Requirements: Access to the Address Points layer is restricted to authorized public safety agencies, emergency responders, and other stakeholders involved in public safety operations within Montgomery County, Texas.Data source: Montgomery County Emergency Communication District

APN: Assessor Parcel NumberASMT: Assessment numberREALUSE: Assessor Real Use CodePrimary code "C" = CommercialPrimary code "A" or "P" = AgriculturalAll other Primary codes = ResidentialDESCRIPTION: Open description field for notes regarding address, if anyDIR: Directional prefix for site address. N, S, E, or WHOUSE NUMBER: Site address numberSTREET NAME: Site address street nameSTREET TYPE: Site address street suffixUNIT: Unit number, if anyCITY: Site address city locationZIP: Site address zip codeNUMBER OF UNITS: The number of units. 0 is assigned to metersADDRESS TYPE: 1. Single Family Residence2. Residential 2-3 unit3. Condo4. Mobile Home5. Apartment6. Commercial7. Second Unit8. Meter9. Cell Tower10. TentativeLOT: Legal lot numberLEGAL: Recorded documentADDRESS: Concatenated site address field created from DIR, HOUSE NUMBER, STREET NAME and STREET TYPE fieldsDATE EDITED: Internal attributeGlobalID: Internal attributeINCORPORATED: Internal attribute for tracking County or City addressesADDRESS_ID: Unique ID for database purposes.X_COORDINATE: X coordinate in State Plane.Y_COORDINATE: Y coordinate in State Plane.LAT_COORDINATE: Lattitude coordinate. LONG_COORDINATE: Longitude coordinate.

This feature data layer contains points representing the location of issued property addresses in the City of Pueblo, Colorado and greater Pueblo County. Unless otherwise specified the assigned geographic coordinate system and longitude, latitude coordinates documented in this GIS data layer file is presented in NAD_1983_StatePlane_Colorado_South_FIPS_0503. This data layer is maintained by the City of Pueblo, Geographic Information Systems Division.