Address point data was developed for location and geocoding purposes. The attributes of the address point data are in the MetroGIS Standard format.

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.

A Feature web service of the Address Point file of buildings and properties in New York State. Please note that, due to the large size, the NYS Address Point statewide layer cannot be downloaded in shapefile format. A map service of the Street and Address Maintenance (SAM) Program Address Point file is available here: https://gisservices.its.ny.gov/arcgis/rest/services.SAM Address Points Data Dictionary: https://gis.ny.gov/system/files/documents/2024/02/address-points-data-dictionary.pdf. If the purpose of accessing the address points service is for geocoding, NYS ITS has a publicly available geocoding service which includes the address points along with other layers. For more information about the geocoding service, please visit: https://gis.ny.gov/address-geocoder. For more information about the SAM Program, please visit: https://gis.ny.gov/streets-addresses.Please contact NYS ITS Geospatial Services at nysgis@its.ny.gov if you have any questions. Publication Date: See Update Frequency. Current as of Date: 2 business days prior to Publication Date. Update frequency: Second and fourth Friday of each month. Spatial Reference of Source Data: NAD_1983_UTM_Zone_18N. Spatial Reference of Map Service: WGS 1984 Web Mercator Auxiliary.This feature service is available to the public.

Updated Continually

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.

This dataset contains address points from the Countywide Address Management System, a collaborative program between the County’s Registrar/Recorder, Chief Information Officer, Public Works Department, Department of Regional Planning, and many local cities to manage addresses and street centerlines for the purposes of geocoding and cartography. More information about this layer can be found on the https://cams-lacounty.hub.arcgis.com/ What this data is (and isn’t)This dataset contains the best available information, with close to 3 million primary and secondary addresses in the County of Los Angeles. It does NOT include information about every unit, suite, building, and sub-address. With probably over 7 million addresses, we have a ways to go.DescriptionThis dataset includes over 2.9 million individual points for addresses in the County. Data has been compiled from best available sources, including city databases, LA County Assessor parcels, and the County’s House Numbering maps. Please see the Source field for information.Street Name information has been split into multiple fields to support the County’s specifically designed geocoders – please see the entry on LA County Specific Locators and Matching rules for more information.Multi-address ParcelsSome of our data sources (LA City, LA County, for example) have mapped each individual address in their city. These may also show unit information for an address point. A property with multiple addresses will show a point for each address. For some cities where this has not happened, the data source is the Assessor, where the primary address of the property may be the only address shown. We invite cities and sources with more detailed information to join the CAMS consortium to continue to improve the data.Legal vs. Postal CitiesMany users confuse the name the Post Office delivers main to (e.g. Van Nuys, Hollywood) as a legal city (in this case Los Angeles), when they are a postal city. The County contains 88 legal cities, and over 400 postal names that are tied to the zipcodes. To support useability and geocoding, we have attached the first 3 postal cities to each address, based upon its zipcocode.

This dataset contains the address points within Scott County, in MetroGIS format. The attributes of the data allow for accurate geocoding.

(Link to Metadata) EmergencyE911_RDS was originally derived from RDSnn (now called TransRoad_RDS). "Zero-length ranges" in the ROADS layer pertain to grand-fathered towns that have not yet provided the Enhanced 9-1-1 Board road segment range information. RDSnn was originally developed using a combination of paper and RC Kodak RF 5000 orthophotos (visual image interpretation and manual digitizing of centerlines). Road attributes (RTNO and CLASS) were taken from the official VT Agency of Transportation (VTrans) highway maps. New roads not appearing on the photos were digitized with locations approximated from the VTrans highway maps. State Forest maps were used to determine both location and attributes of state forest roads. Some data updates have used RF 2500 or RF 1250 orthophotos and GPS, or other means for adding new roads and improving road locations. The Enhanced E911 program added new roads from GPS and orthos between 1996-1998. Also added road name and address geocoding. VCGI PROCESSING (Tiling and Added items); E911 provides the EmergencyE911_RDS data to VCGI in a statewide format. It lacks FIPS6 coding, making it difficult to extract data on the basis of town/county boundaries. As a result, VCGI has added FIPS6 to the attribute table. This field was originally populated by extracting MCODE value from RDNAME and relating to TBPOLY.PAT to bring over matching MCODE values. FIPS6 problems along the interstates and "Gores & Grants" in the Northeast Kingdom, were corrected. All features with an MCODE equal to 200 or 579 were assigned a FIPS6 equal to 0. The center point of these arcs were then intersected with BoundaryTown_TBHASH to assign a FIPS6 value. This information was then transfered back into the RDS.AAT file via a relate. A relate was established between the ROADNAMES.DBF file (road name lookup table) and the RDS.AAT file. The RDFLNAME attribute was populated by transfering the NAME value in the ROADNAMES.DBF table. The RDFLNAME item was then parsed into SUF.DIR, STREET.NAME, STREET.TYPE, and PRE.DIR, making addressing matching functions a little easier. See the "VT Road Centerline Data FAQ" for more information about TransRoad_RDS and EmergencyE911_RDS. https://vcgi.vermont.gov/techres/?page=./white_papers/default_content.cfmField Descriptions:OBJECTID: Internal feature number, automatically generated by Esri software.SEGMENTID: Unique segment ID.ARCID: Arc identifier, unique statewide. The ARCID is a unique identifier for every ARC in the EmergencyE911_RDS data layer.PD: Prefix Direction, previously name PRE.DIR.PT: Prefix Type.SN: Street Name. Previously named STREET.ST: Street Type.SD: Suffix Direction, i.e., W for West, E for East, etc.GEONAMEID: Unique ID for each road name.PRIMARYNAME: Primary name.ALIAS1: Alternate road name 1.ALIAS2: Alternate road name 2.ALIAS3: Alternate road name 3.ALIAS4: Alternate road name 4.ALIAS5: Alternate road name 5.COMMENTS: Free text field for miscellaneous comments.ONEWAY: One-way street. Uses the Oneway domain*.NO_MSAG:MCODE: Municipal code.LESN: Left side of road Emergency Service Number.RESN: Right side of road Emergency Service Number.LTWN: Left side of road town.RTWN: Right side of road town.LLO_A: Low address for left side of road.RLO_A: Low address for right side of road.LHI_A: High address for left side of road.RHI_A: High address for right side of road.LZIP: Left side of road zip code.RZIP: Right side of road zip code.LLO_TRLO_TLHI_TRHI_TRTNAME: Route name.RTNUMBER: Route number.HWYSIGN: Highway sign.RPCCLASSAOTCLASS: Agency of Transportation class. Uses AOTClass domain**.ARCMILES: ESRI ArcGIS miles.AOTMILES: Agency of Transportation miles.AOTMILES_CALC:UPDACT:SCENICHWY: Scenic highway.SCENICBYWAY: Scenic byway.FORMER_RTNAME: Former route name.PROVISIONALYEAR: Provisional year.ANCIENTROADYEAR: Ancient road year.TRUCKROUTE: Truck route.CERTYEAR:MAPYEAR:UPDATEDATE: Update date.GPSUPDATE: Uses GPSUpdate domain***.GlobalID: GlobalID.STATE: State.GAP: Gap.GAPMILES: Gap miles.GAPSTREETID: Gap street ID.FIPS8:FAID_S:RTNUMBER_N:LCOUNTY:RCOUNTY:PRIMARYNAME1:SOURCEOFDATA: Source of data.COUNTRY: Country.PARITYLEFT:PARITYRIGHT:LFIPS:RFIPS:LSTATE:RSTATE:LESZ:RESZ:SPEED_SOURCE: Speed source.SPEEDLIMIT: Speed limit.MILES: Miles.MINUTES: Minutes.Shape: Feature geometry.Shape_Length: Length of feature in internal units. Automatically computed by Esri software.*Oneway Domain:N: NoY: Yes - Direction of arcX: Yes - Opposite direction of arc**AOTClass Domain:1: Town Highway Class 1 - undivided2: Town Highway Class 2 - undivided3: Town Highway Class 3 - undivided4: Town Highway Class 4 - undivided5: State Forest Highway6: National Forest Highway7: Legal Trail. Legal Trail Mileage Approved by Selectboard after the enactment of Act 178 (July 1, 2006). Due to the introduction of Act 178, the Mapping Unit needed to differentiate between officially accepted and designated legal trail versus trails that had traditionally been shown on the maps. Towns have until 2015 to map all Class 1-4 and Legal Trails, based on new changes in VSA Title 19.8: Private Road - No Show. Private road, but not for display on local maps. Some municipalities may prefer not to show certain private roads on their maps, but the roads may need to be maintained in the data for emergency response or other purposes.9: Private road, for display on local maps10: Driveway (put in driveway)11: Town Highway Class 1 - North Bound12: Town Highway Class 1 - South Bound13: Town Highway Class 1 - East Bound14: Town Highway Class 1 - West Bound15: Town Highway Class 1 - On/Off Ramp16: Town Highway Class 1 - Emergency U-Turn20: County Highway21: Town Highway Class 2 - North Bound22: Town Highway Class 2 - South Bound23: Town Highway Class 2 - East Bound24: Town Highway Class 2 - West Bound25: Town Highway Class 2 - On/Off Ramp30: State Highway31: State Highway - North Bound32: State Highway - South Bound33: State Highway - East Bound34: State Highway - West Bound35: State Highway - On/Off Ramp40: US Highway41: US Highway - North Bound42: US Highway - South Bound43: US Highway - East Bound44: US Highway - West Bound45: US Highway - On/Off Ramp46: US Highway - Emergency U-Turn47: US Highway - Rest Area50: Interstate Highway51: Interstate Highway - North Bound52: Interstate Highway - South Bound53: Interstate Highway - East Bound54: Interstate Highway - West Bound55: Interstate Highway - On/Off Ramp56: Interstate Highway - Emergency U-Turn57: Interstate Highway - Rest Area59: Interstate Highway - Other65: Ferry70: Unconfirmed Legal Trail71: Unidentified Corridor80: Proposed Highway Unknown Class81: Proposed Town Highway Class 182: Proposed Town Highway Class 283: Proposed Town Highway Class 384: Proposed State Highway85: Proposed US Highway86: Proposed Interstate Highway87: Proposed Interstate Highway - Ramp88: Proposed Non-Interstate Highway - Ramp89: Proposed Private Road91: New - Class Unknown92: Military - no public access93: Public - Class Unknown95: Class Under Review96: Discontinued Road97: Discontinued Now Private98: Not a Road99: Unknown***GPSUpdate Domain:Y: Yes - Needs GPS UpdateN: No - Does not need GPS UpdateG: GPS Update CompleteV: GPS Update Complete - New RoadX: Unresolved Segment

This layer contains voter polling locations utilized in past elections across the entire Commonwealth of Virginia. Data can be filtered by locality as well as election name, type, or date. Please note that the physical address and location information for each polling location is maintained by individual locality General Registrars. Addresses are geocoded using the VGIN Composite Geocoding Service.Please note that this layer currently only contains points for polling places dating back to the June 2024 Primary elections. Polling places for elections prior to the June 2024 Primaries can be found in tabular format on the Virginia Department of Elections website: https://www.elections.virginia.gov/resultsreports/registration-statistics/Individuals looking to confirm their assigned polling place for an upcoming election should refer to the Department's website for the most accurate, up-to-date information: Polling Place Lookup

This street centerline lines feature class represents current right of way in the City of Los Angeles. It shows the official street names and is related to the official street name data. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most current geographic information of the public right of way. The right of way information is available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works. Street Centerline layer was created in geographical information systems (GIS) software to display Dedicated street centerlines. The street centerline layer is a feature class in the LACityCenterlineData.gdb Geodatabase dataset. The layer consists of spatial data as a line feature class and attribute data for the features. City of LA District Offices use Street Centerline layer to determine dedication and street improvement requirements. Engineering street standards are followed to dedicate the street for development. The Bureau of Street Services tracks the location of existing streets, who need to maintain that road. Additional information was added to Street Centerline layer. Address range attributes were added make layer useful for geocoding. Section ID values from Bureau of Street Services were added to make layer useful for pavement management. Department of City Planning added street designation attributes taken from Community Plan maps. The street centerline relates to the Official Street Name table named EASIS, Engineering Automated Street Inventory System, which contains data describing the limits of the street segment. A street centerline segment should only be added to the Street Centerline layer if documentation exists, such as a Deed or a Plan approved by the City Council. Paper streets are street lines shown on a recorded plan but have not yet come into existence on the ground. These street centerline segments are in the Street Centerline layer because there is documentation such as a Deed or a Plan for the construction of that street. Previously, some street line features were added although documentation did not exist. Currently, a Deed, Tract, or a Plan must exist in order to add street line features. Many street line features were edited by viewing the Thomas Bros Map's Transportation layer, TRNL_037 coverage, back when the street centerline coverage was created. When TBM and BOE street centerline layers were compared visually, TBM's layer contained many valid streets that BOE layer did not contain. In addition to TBM streets, Planning Department requested adding street line segments they use for reference. Further, the street centerline layer features are split where the lines intersect. The intersection point is created and maintained in the Intersection layer. The intersection attributes are used in the Intersection search function on NavigateLA on BOE's web mapping application NavigateLA. The City of Los Angeles Municipal code states, all public right-of-ways (roads, alleys, etc) are streets, thus all of them have intersections. Note that there are named alleys in the BOE Street Centerline layer. Since the line features for named alleys are stored in the Street Centerline layer, there are no line features for named alleys in those areas that are geographically coincident in the Alley layer. For a named alley , the corresponding record contains the street designation field value of ST_DESIG = 20, and there is a name stored in the STNAME and STSFX fields.List of Fields:SHAPE: Feature geometry.OBJECTID: Internal feature number.STNAME_A: Street name Alias.ST_SUBTYPE: Street subtype.SV_STATUS: Status of street in service, whether the street is an accessible roadway. Values: • Y - Yes • N - NoTDIR: Street direction. Values: • S - South • N - North • E - East • W - WestADLF: From address range, left side.ZIP_R: Zip code right.ADRT: To address range, right side.INT_ID_TO: Street intersection identification number at the line segment's end node. The value relates to the intersection layer attribute table, to the CL_NODE_ID field. The values are assigned automatically and consecutively by the ArcGIS software first to the street centerline data layer and then the intersections data layer, during the creation of new intersection points. Each intersection identification number is a unique value.SECT_ID: Section ID used by the Bureau of Street Services. Values: • none - No Section ID value • private - Private street • closed - Street is closed from service • temp - Temporary • propose - Proposed construction of a street • walk - Street line is a walk or walkway • known as - • numeric value - A 7 digit numeric value for street resurfacing • outside - Street line segment is outside the City of Los Angeles boundary • pierce - Street segment type • alley - Named alleySTSFX_A: Street suffix Alias.SFXDIR: Street direction suffix Values: • N - North • E - East • W - West • S - SouthCRTN_DT: Creation date of the polygon feature.STNAME: Street name.ZIP_L: Zip code left.STSFX: Street suffix. Values: • BLVD - BoulevardADLT: To address range, left side.ID: Unique line segment identifierMAPSHEET: The alpha-numeric mapsheet number, which refers to a valid B-map or A-map number on the Cadastral tract index map. Values: • B, A, -5A - Any of these alpha-numeric combinations are used, whereas the underlined spaces are the numbers.STNUM: Street identification number. This field relates to the Official Street Name table named EASIS, to the corresponding STR_ID field.ASSETID: User-defined feature autonumber.TEMP: This attribute is no longer used. This attribute was used to enter 'R' for reference arc line segments that were added to the spatial data, in coverage format. Reference lines were temporary and not part of the final data layer. After editing the permanent line segments, the user would delete temporary lines given by this attribute.LST_MODF_DT: Last modification date of the polygon feature.REMARKS: This attribute is a combination of remarks about the street centerline. Values include a general remark, the Council File number, which refers the street status, or whether a private street is a private driveway. The Council File number can be researched on the City Clerk's website http://cityclerk.lacity.org/lacityclerkconnect/INT_ID_FROM: Street intersection identification number at the line segment's start node. The value relates to the intersection layer attribute table, to the CL_NODE_ID field. The values are assigned automatically and consecutively by the ArcGIS software first to the street centerline data layer and then the intersections data layer, during the creation of new intersection points. Each intersection identification number is a unique value.ADRF: From address range, right side.

Access directly in the TEBS-GIS database in SDE.ADDRESSES, SDE.BARField name explanations:BLDG_ID – unique identifier for every footprintPS_LABEL – building labels for Public Safety (geoload) or a reference for map making (a concatenation of ADDRNUM and BLDG_NUM)BLDG_NUM – Unit number or letter on a building to distinguish same addrnum’sPREM_NUM – individual addresses that equal ADDRNUM and equal BLDG_CLASS (‘P’ and ‘Q’)but exclude footprint with a BLDG_CLASS = ‘S’ (used for individual address geocoding)BLDG_CLASS - ‘S’ represents footprints that are of the smallest square footage on a property that has multiple buildings(that are separated)of the same ADDRNUM, ‘P’ represents one footprint of the largest square footage on a property that has multiple buildings of the same ADDRNUM, ‘Q’ represents large square footage buildings (that are connected) with unit numbers or same ADDRNUM with a BLDG_NUMADDRNUM – all building individual address numbers, includes duplicatesPRE_DIR – n, s, e, wSTREET_NAME – value based on Clines data layerSUF_DIR – n, s, e, wSTREET_TYPE – ave, st, rd, dr, la, way, mews, etcBLDG_NAME – names based on Places of Interest data layerSOURCE – name of organization that digitized, edited, added value, corrected or changed the buildingBLDG_DATE – date that a footprint has been digitized, edited, added value, corrected or changedFTR_CODE – Park and Planning code to describe a building under construction or notX_COORD and Y_COORD – geographical reference, can be used for finding locations based on x,y valuesBLDG_TYPE – Land use code based on Park and Planning’s definitionsPREPLAN_URL – Fire Rescue’s .pdf files that represent some buildingsBLDG_URL – In researching a footprint for an address on the web, and there is not one to be found a www.site is given in this fieldSTATUS - information on irregular addressesCENSUS_ID – Id based on the buildings Street name cline census_idBLDG_PROP_TAX_ID – Account number based on Park and Planning property account number POSTAL_CITY- The city name given by DTSUNICORP_COMMUNITY- The city name given by USPSADDRNUM_NCR- The address number format used for NexGen911(NCR)BLDG_NCR_DATE- The date format used for NexGen911(NCR)

This dataset offers a detailed inventory of road intersections and their corresponding suburbs within Cape Town, meticulously curated to highlight instances of high pedestrian crash counts resulting in serious injuries observed in "high-high" cluster and "high-low" outlier fishnet grid cells across the years 2017, 2018 and 2019. To enhance its utility, the dataset meticulously colour-codes each month associated with elevated crash occurrences, providing a nuanced perspective. Furthermore, the dataset categorises road intersections based on their placement within "high-high" clusters (marked with pink tabs) or "high-low" outlier cells (indicated by red tabs). For ease of navigation, the intersections are further organised alphabetically by suburb name, ensuring accessibility and clarity.Data SpecificsData Type: Geospatial-temporal categorical data with numeric attributesFile Format: Word document (.docx)Size: 231 KBNumber of Files: The dataset contains a total of 245 road intersection records (7 "high-high" clusters and 238 "high-low" outliers)Date Created: 21st May 2024MethodologyData Collection Method: The descriptive road traffic crash data per crash victim involved in the crashes was obtained from the City of Cape Town Network InformationSoftware: ArcGIS Pro, Open Refine, Python, SQLProcessing Steps: The raw road traffic crash data underwent a comprehensive refining process using Python software to ensure its accuracy and consistency. Following this, duplicates were eliminated to retain only one entry per crash incident. Subsequently, the data underwent further refinement with Open Refine software, focusing specifically on isolating unique crash descriptions for subsequent geocoding in ArcGIS Pro. Notably, during this process, only the road intersection crashes were retained, as they were the only incidents with spatial definitions.Once geocoded, road intersection crashes that involved a pedestrian with a severe or fatal injury type were extracted so that subsequent spatio-temporal analyses would focus on these crashes only. The spatio-temporal analysis methods by which these pedestrian crashes were analysed included spatial autocorrelation, hotspot analysis, and cluster and outlier analysis. Leveraging these methods, road intersections with pedestrian crashes that resulted in a severe injury identified as either "high-high" clusters or "high-low" outliers were extracted for inclusion in the dataset.Geospatial InformationSpatial Coverage:West Bounding Coordinate: 18°20'EEast Bounding Coordinate: 19°05'ENorth Bounding Coordinate: 33°25'SSouth Bounding Coordinate: 34°25'SCoordinate System: South African Reference System (Lo19) using the Universal Transverse Mercator projectionTemporal InformationTemporal Coverage:Start Date: 01/01/2017End Date: 31/12/2019

This dataset offers a detailed inventory of road intersections and their corresponding suburbs within Cape Town, meticulously curated to highlight instances of high crash counts observed in "high-high" cluster and "high-low" outlier fishnet grid cells across the years 2017, 2018, 2019, and 2021. To enhance its utility, the dataset meticulously colour-codes each month associated with elevated crash occurrences, providing a nuanced perspective. Furthermore, the dataset categorises road intersections based on their placement within "high-high" clusters (marked with pink tabs) or "high-low" outlier cells (indicated by red tabs). For ease of navigation, the intersections are further organised alphabetically by suburb name, ensuring accessibility and clarity.Data SpecificsData Type: Geospatial-temporal categorical data with numeric attributesFile Format: Word document (.docx)Size: 602 KBNumber of Files: The dataset contains a total of 625 road intersection records (606 "high-high" cluster and 19 "high-low" outliers)Date Created: 21st May 2024MethodologyData Collection Method: The descriptive road traffic crash data per crash victim involved in the crashes was obtained from the City of Cape Town Network InformationSoftware: ArcGIS Pro, Open Refine, Python, SQLProcessing Steps: The raw road traffic crash data underwent a comprehensive refining process using Python software. Following this, duplicate crash records were eliminated to retain only one entry per crash. Subsequently, the data underwent further refinement with Open Refine software, focusing specifically on isolating unique crash descriptions for subsequent geocoding in ArcGIS Pro. Notably, during this process, only the road intersection crashes were retained, as they were the only crashes that were able to be spatially defined.Once geocoded, the road traffic crash data underwent rigorous spatio-temporal analyses, encompassing spatial autocorrelation, hotspot analysis, and cluster and outlier analysis. Leveraging these methods, road intersections identified as either "high-high" clusters or "high-low" outliers were extracted for inclusion in the dataset.Geospatial InformationSpatial Coverage:West Bounding Coordinate: 18°20'EEast Bounding Coordinate: 19°05'ENorth Bounding Coordinate: 33°25'SSouth Bounding Coordinate: 34°25'SCoordinate System: South African Reference System (Lo19) using the Universal Transverse Mercator projectionTemporal InformationTemporal Coverage:Start Date: 01/01/2017End Date: 31/12/2021 (2020 data omitted)

Road segments representing centerlines of all roadways or carriageways in a local government. Typically, this information is compiled from orthoimagery or other aerial photography sources. This representation of the road centerlines support address geocoding and mapping. It also serves as a source for public works and other agencies that are responsible for the active management of the road network. (From ESRI Local Government Model "RoadCenterline" Feature)**This dataset was significantly revised in August of 2014 to correct for street segments that were not properly split at intersections. There may be issues with using data based off of the original centerline file. ** The column Speed Limit was updated in November 2014 by the Transportation Intern and is believed to be accurate** The column One Way was updated in November of 2014 by core GIS and is believed to be accurate.[MAXIMOID] A unique id field used in a work order management software called Maximo by IBM. Maximo uses GIS CL data to assign locations to work orders using this field. This field is maintained by the Transportation GIS specialists and is auto incremented when new streets are digitized. For example, if the latest digitized street segment MAXIMOID = 999, the next digitized line will receive MAXIMOID = 1000, and so on. STREET NAMING IS BROKEN INTO THREE FIELDS FOR GEOCODING:PREFIX This field is attributed if a street name has a prefix such as W, N, E, or S.NAME Domain with all street names. The name of the street without prefix or suffix.ROAD_TYPE (Text,4) Describes the type of road aka suffix, if applicable. CAPCOG Addressing Guidelines Sec 504 U. states, “Every road shall have corresponding standard street suffix…” standard street suffix abbreviations comply with USPS Pub 28 Appendix C Street Abbreviations. Examples include, but are not limited to, Rd, Dr, St, Trl, Ln, Gln, Lp, CT. LEFT_LOW The minimum numeric address on the left side of the CL segment. Left side of CL is defined as the left side of the line segment in the From-To direction. For example, if a line has addresses starting at 101 and ending at 201 on its left side, this column will be attributed 101.LEFT_HIGH The largest numeric address on the left side of the CL segment. Left side of CL is defined as the left side of the line segment in the From-To direction. For example, if a line has addresses starting at 101 and ending at 201 on its left side, this column will be attributed 201.LOW The minimum numeric address on the RIGHT side of the CL segment. Right side of CL is defined as the right side of the line segment in the From-To direction. For example, if a line has addresses starting at 100 and ending at 200 on its right side, this column will be attributed 100.HIGHThe maximum numeric address on the RIGHT side of the CL segment. Right side of CL is defined as the right side of the line segment in the From-To direction. For example, if a line has addresses starting at 100 and ending at 200 on its right side, this column will be attributed 200.ALIAS Alternative names for roads if known. This field is useful for geocode re-matching. CLASSThe functional classification of the centerline. For example, Minor (Minor Arterial), Major (Major Arterial). THIS FIELD IS NOT CONSISTENTLY FILLED OUT, NEEDS AN AUDIT. FULLSTREET The full name of the street concatenating the [PREFIX], [NAME], and [SUFFIX] fields. For example, "W San Antonio St."ROWWIDTH Width of right-of-way along the CL segment. Data entry from Plat by Planning GIS Or from Engineering PICPs/ CIPs.NUMLANES Number of striped vehicular driving lanes, including turn lanes if present along majority of segment. Does not inlcude bicycle lanes. LANEMILES Describes the total length of lanes for that segment in miles. It is manually field calculated as follows (( [ShapeLength] / 5280) * [NUMLANES]) and maintained by Transportation GIS.SPEEDLIMIT Speed limit of CL segment if known. If not, assume 30 mph for local and minor arterial streets. If speed limit changes are enacted by city council they will be recorded in the Traffic Register dataset, and this field will be updating accordingly. Initial data entry made by CIP/Planning GIS and maintained by Transportation GIS.[YRBUILT] replaced by [DateBuilt] See below. Will be deleted. 4/21/2017LASTYRRECON (Text,10) Is the last four-digit year a major reconstruction occurred. Most streets have not been reconstructed since orignal construction, and will have values. The Transportation GIS Specialist will update this field. OWNER Describes the governing body or private entity that owns/maintains the CL. It is possible that some streets are owned by other entities but maintained by CoSM. Possible attributes include, CoSM, Hays Owned/City Maintained, TxDOT Owned/City Maintained, TxDOT, one of four counties (Hays, Caldwell, Guadalupe, and Comal), TxState, and Private.ST_FROM Centerline segments are split at their intersections with other CL segments. This field names the nearest cross-street in the From- direction. Should be edited when new CL segments that cause splits are added. ST_TO Centerline segments are split at their intersections with other CL segments. This field names the nearest cross-street in the To- direction. Should be edited when new CL segments that cause splits are added. PAV_WID Pavement width of street in feet from back-of-curb to back-of-curb. This data is entered from as-built by CIP GIS. In January 2017 Transportation Dept. field staff surveyed all streets and measured width from face-of-curb to face-of-curb where curb was present, and edge of pavement to edge of pavement where it was not. This data was used to field calculate pavement width where we had values. A value of 1 foot was added to the field calculation if curb and gutter or stand up curb were present (the face-of-curb to back-of-curb is 6 in, multiple that by 2 to find 1 foot). If no curb was present, the value enter in by the field staff was directly copied over. If values were already present, and entered from asbuilt, they were left alone. ONEWAY Field describes direction of travel along CL in relation to digitized direction. If a street allows bi-directional travel it is attributed "B", a street that is one-way in the From_To direction is attributed "F", a street that is one-way in the To_From direction is attributed "T", and a street that does not allow travel in any direction is attibuted "N". ROADLEVEL Field will be aliased to [MINUTES] and be used to calculate travel time along CL segments in minutes using shape length and [SPEEDLIMIT]. Field calculate using the following expression: [MINUTES] = ( ([SHAPE_LENGTH] / 5280) / ( [SPEEDLIMIT] / 60 ))ROWSTATUS Values include "Open" or "Closed". Describes whether a right-of-way is open or closed. If a street is constructed within ROW it is "Open". If a street has not yet been constructed, and there is ROW, it is "Cosed". UPDATE: This feature class only has CL geometries for "Open" rights-of-way. This field should be deleted or re-purposed. ASBUILT field used to hyper link as-built documents detailing construction of the CL. Field was added in Dec. 2016. DateBuilt Date field used to record month and year a road was constructed from Asbuilt. Data was collected previously without month information. Data without a known month is entered as "1/1/YYYY". When month and year are known enter as "M/1/YYYY". Month and Year from asbuilt. Added by Engineering/CIP. ACCEPTED Date field used to record the month, day, and year that a roadway was officially accepted by the City of San Marcos. Engineering signs off on acceptance letters and stores these documents. This field was added in May of 2018. Due to a lack of data, the date built field was copied into this field for older roadways. Going forward, all new roadways will have this date. . This field will typically be populated well after a road has been drawn into GIS. Entered by Engineering/CIP. ****In an effort to make summarizing the data more efficient in Operations Dashboard, a generic date of "1/1/1900" was assigned to all COSM owned or maintained roads that had NULL values. These were roads that either have not been accepted yet, or roads that were expcepted a long time ago and their accepted date is not known. WARRANTY_EXP Date field used to record the expiration date of a newly accepted roadway. Typically this is one year from acceptance date, but can be greater. This field was added in May of 2018, so only roadways that have been excepted since and older roadways with valid warranty dates within this time frame have been populated.

DATA LINKED FROM PIERCE COUNTY OPEN DATA PORTAL - Clipped by City of PuyallupSee the metadata and original layer hereAbstract:This is a comprehensive building address point layer for Pierce County, Washington. Every unique house number has a point located within the building footprint of the addressed structure (where possible). Multi-unit structures, mobile home parks, and buildings with the same street address are further identified by mailstop in the attribute table. Some vacant parcels may or may not have an assigned temporary address point. A permanent address will be assigned to a vacant parcel if a permitted structure is built on that parcel. In unincorporated Pierce County, the address points were created individually by a team of technicians based on scanned address maps from the Planning Department and Assessor-Treasurer's Department site address data. For incorporated areas, source data was gathered either in the form of address points, tabular data, or we visited the city and took photos of their paper maps, then created points based on those photographs. Pierce County began construction of this data in 2008, and in the intervening years the data has been constantly refined through field inspection and review using various imagery source such as Google StreetView. Please be aware this data is constantly being updated and is only a snapshot at any given time. Data is provided to Pierce County by many jurisdictional sources throughout the County, and it may be neither complete or 100% accurate. If an error is found please contact the jurisdiction first to discuss the error.Purpose:The Address Point dataset is intended to improve emergency response, County business applications and processes, and provide a dependable address source County-wide. This dataset will also be used to enhance geocoding services.

Can be downloaded from the GIS Data Portal here.Access directly in the TEBS-GIS database in SDE.ADDRESSES, SDE.BLDG_PSField name explanations:BLDG_ID – unique identifier for every footprintPS_LABEL – building labels for Public Safety (geoload) or a reference for map making (a concatenation of ADDRNUM and BLDG_NUM)BLDG_NUM – Unit number or letter on a building to distinguish same addrnum’sPREM_NUM – individual addresses that equal ADDRNUM and equal BLDG_CLASS (‘P’ and ‘Q’)but exclude footprint with a BLDG_CLASS = ‘S’ (used for individual address geocoding)BLDG_CLASS - ‘S’ represents footprints that are of the smallest square footage on a property that has multiple buildings(that are separated)of the same ADDRNUM, ‘P’ represents one footprint of the largest square footage on a property that has multiple buildings of the same ADDRNUM, ‘Q’ represents large square footage buildings (that are connected) with unit numbers or same ADDRNUM with a BLDG_NUMADDRNUM – all building individual address numbers, includes duplicatesPRE_DIR – n, s, e, wSTREET_NAME – value based on Clines data layerSUF_DIR – n, s, e, wSTREET_TYPE – ave, st, rd, dr, la, way, mews, etcBLDG_NAME – names based on Places of Interest data layerSOURCE – name of organization that digitized, edited, added value, corrected or changed the buildingBLDG_DATE – date that a footprint has been digitized, edited, added value, corrected or changedFTR_CODE – Park and Planning code to describe a building under construction or notX_COORD and Y_COORD – geographical reference, can be used for finding locations based on x,y valuesBLDG_TYPE – Land use code based on Park and Planning’s definitionsPREPLAN_URL – Fire Rescue’s .pdf files that represent some buildingsBLDG_URL – In researching a footprint for an address on the web, and there is not one to be found a www.site is given in this fieldSTATUS - information on irregular addressesCENSUS_ID – Id based on the buildings Street name cline census_idBLDG_PROP_TAX_ID – Account number based on Park and Planning property account number POSTAL_CITY- The city name given by DTSUNICORP_COMMUNITY- The city name given by USPSADDRNUM_NCR- The address number format used for NexGen911(NCR)BLDG_NCR_DATE- The date format used for NexGen911(NCR)

The Division of Water Ground Water Database has approximately 407,000 water well records, and of those, approximately 147,000 have been field located and have x, y (UTM) coordinates. Approximately 39,000 were located based on address geocoding. The remaining records have no utms and cannot be easily utilized in a GIS format. The purpose of this dataset was to include those wells with UTM coordinates and to approximate the UTM coordinates for the others based on the most precise of county, or Township, Range, Section, quarter sections (TRS) locations available from office locating, which is effectively the centroid of the smallest known section or quarter sections; thus, increasing the amount of data available for display and analysis in a GIS format. This dataset is combination of the located water well records and the water well records for which an estimated location was able to be determined using the methods described below. This leaves less than 15,000 records with no UTM's associated with them. This dataset and associated table has selected fields from the main digital water well database that are typically needed for most research. This file is a digital geospatial point feature class of both located water well records (which include UTM coordinates) and unlocated water well records. The estimated locations used for the unlocated wells were based on the polygon centroid values for the smallest indicated county, section, quarter, quarter-quarter, or quarter-quarter-quarter section (as indicated in the database) for over 221,000 water well records and for about 39,000 water well records the UTM's were obtained from address geocoding using the owners address, a generally more accurate method (see process steps below).

The FHA insured Multifamily Housing portfolio consists primarily of rental housing properties with five or more dwelling units such as apartments or town houses, but can also be nursing homes, hospitals, elderly housing, mobile home parks, retirement service centers, and occasionally vacant land. Please note that this dataset overlaps the Multifamily Properties Assisted layer. The Multifamily property locations represent the approximate location of the property. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes: ‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) ‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) ‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) ‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) ‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) ‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) Null - Could not be geocoded (does not appear on the map) For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. In an effort to protect Personally Identifiable Information (PII), the characteristics for each building are suppressed with a -4 value when the “Number_Reported” is equal to, or less than 10. To learn more about HUD Insured Multifamily Properties visit: https://www.hud.gov/program_offices/housing/mfh Data Dictionary: DD_HUD Insured Multifamilly Properties

US Postal Service ZIP Code boundaries. This layer was created by Los Angeles County eGIS to align with parcel boundaries.ZIP is an acronym for Zone Improvement Plan.Legal vs. Postal Cities: Many users confuse the name the Post Office delivers mail to (e.g. Van Nuys, Hollywood) as a legal city (in this case Los Angeles), when they are a postal city. The County contains 88 legal cities, and over 400 postal names that are tied to the ZIP Codes. To support usability and geocoding, we have attached the first 3 postal cities to each address, based upon its ZIP Code.The US Postal Service is the authoritative source for ZIP Code data. See their website for more information.