Webmap of Allegheny municipalities and parcel data. Zoom for a clickable parcel map with owner name, property photograph, and link to the County Real Estate website for property sales information.

Web App. Use the tabs provided to discover information about map features and capabilities. Link to Metadata. A variety of searches can be performed to find the parcel of interest. Use the Query Tool to build searches. Click Apply button at the bottom of the tool.Query by Name (Last First) (e.g. Bond James)Query by Address (e.g. 41 S Central)Query by Locator number (e.g. 21J411046)Search results will be listed under the Results tab. Click on a parcel in the list to zoom to that parcel. Click on the parcel in the map and scroll through the pop-up to see more information about the parcel. Click the ellipse in the Results tab or in the pop-up to view information in a table. Attribute information can be exported to CSV file. Build a custom Filter to select and map properties by opening the Parcels attribute table:1. Click the arrow tab at the bottom middle of the map to expand the attribute table window2. Click on the Parcels tab3. Check off Filter by map extent4. Open Options>Filter5. Build expressions as needed to filter by owner name or other variables6. Select the needed records from the returned list7. Click Zoom to which will zoom to the selected recordsPlease note that as the map zooms out detailed layers, such as the parcel boundaries will not display.In addition to Search capabilities, the following tools are provided:MeasureThe measure tool provides the capabilities to draw a point, line, or polygon on the map and specify the unit of measurement.DrawThe draw tool provides the capabilities to draw a point, line, or polygon on the map as graphics. PrintThe print tool exports the map to either a PDF or image file. Click Settings button to configure map or remove legend.Map navigation using mouse and keyboard:Drag to panSHIFT + CTRL + Drag to zoom outMouse Scroll Forward to zoom inMouse Scroll Backward to zoom outUse Arrow keys to pan+ key to zoom in a level- key to zoom out a levelDouble Click to Zoom inFAQsHow to select a parcel: Click on a parcel in the map, or use Query Tool to search for parcel by owner, address or parcel id.How to select more than one parcel: Go to Select Tool and choose options on Select button.How to clear selected parcel(s): Go to Select Tool and click Clear.

Parcels and property data maintained and provided by Lee County Property Appraiser. This dataset includes condominium units. Property attribute data joined to parcel GIS layer by Lee County Government GIS.Projected coordinate system name: NAD_1983_StatePlane_Florida_West_FIPS_0902_FeetGeographic coordinate system name: GCS_North_American_1983

 Name
 Type
 Length
 Description


 STRAP
 String
 25
 17-digit Property ID (Section, Township, Range, Area, Block, Lot)


 BLOCK
 String
 10
 5-digit portion of STRAP (positions 9-13)


 LOT
 String
 8
 Last 4-digits of STRAP


 FOLIOID
 Double
 8
 Unique Property ID


 MAINTDATE
 Date
 8
 Date LeePA staff updated record


 MAINTWHO
 String
 20
 LeePA staff who updated record


 UPDATED
 Date
 8
 Data compilation date


 HIDE_STRAP
 String
 1
 Confidential parcel ownership


 TRSPARCEL
 String
 17
 Parcel ID sorted by Township, Range & Section


 DORCODE
 String
 2
 Department of Revenue property classification code


 CONDOTYPE
 String
 1
 Type of condominium: C (commercial) or R (residential)


 UNITOFMEAS
 String
 2
 Type of Unit of Measure (ex: AC=acre, LT=lot, FF=frontage in feet)


 NUMUNITS
 Double
 8
 Number of Land Units (units defined in UNITOFMEAS)


 FRONTAGE
 Integer
 4
 Road Frontage in Feet


 DEPTH
 Integer
 4
 Property Depth in Feet


 GISACRES
 Double
 8
 Total Computed Acres from GIS


 TAXINGDIST
 String
 3
 Taxing District of Property


 TAXDISTDES
 String
 60
 Taxing District Description


 FIREDIST
 String
 3
 Fire District of Property


 FIREDISTDE
 String
 60
 Fire District Description


 ZONING
 String
 10
 Zoning of Property


 ZONINGAREA
 String
 3
 Governing Area for Zoning


 LANDUSECOD
 SmallInteger
 2
 Land Use Code


 LANDUSEDES
 String
 60
 Land Use Description


 LANDISON
 String
 5
 BAY,CANAL,CREEK,GULF,LAKE,RIVER & GOLF


 SITEADDR
 String
 55
 Lee County Addressing/E911


 SITENUMBER
 String
 10
 Property Location - Street Number


 SITESTREET
 String
 40
 Street Name


 SITEUNIT
 String
 5
 Unit Number


 SITECITY
 String
 20
 City


 SITEZIP
 String
 5
 Zip Code


 JUST
 Double
 8
 Market Value


 ASSESSED
 Double
 8
 Building Value + Land Value


 TAXABLE
 Double
 8
 Taxable Value


 LAND
 Double
 8
 Land Value


 BUILDING
 Double
 8
 Building Value


 LXFV
 Double
 8
 Land Extra Feature Value


 BXFV
 Double
 8
 Building Extra Feature value


 NEWBUILT
 Double
 8
 New Construction Value


 AGAMOUNT
 Double
 8
 Agriculture Exemption Value


 DISAMOUNT
 Double
 8
 Disability Exemption Value


 HISTAMOUNT
 Double
 8
 Historical Exemption Value


 HSTDAMOUNT
 Double
 8
 Homestead Exemption Value


 SNRAMOUNT
 Double
 8
 Senior Exemption Value


 WHLYAMOUNT
 Double
 8
 Wholly Exemption Value


 WIDAMOUNT
 Double
 8
 Widow Exemption Value


 WIDRAMOUNT
 Double
 8
 Widower Exemption Value


 BLDGCOUNT
 SmallInteger
 2
 Total Number of Buildings on Parcel


 MINBUILTY
 SmallInteger
 2
 Oldest Building Built


 MAXBUILTY
 SmallInteger
 2
 Newest Building Built


 TOTALAREA
 Double
 8
 Total Building Area


 HEATEDAREA
 Double
 8
 Total Heated Area


 MAXSTORIES
 Double
 8
 Tallest Building on Parcel


 BEDROOMS
 Integer
 4
 Total Number of Bedrooms


 BATHROOMS
 Double
 8
 Total Number of Bathrooms / Not For Comm


 GARAGE
 String
 1
 Garage on Property 'Y'


 CARPORT
 String
 1
 Carport on Property 'Y'


 POOL
 String
 1
 Pool on Property 'Y'


 BOATDOCK
 String
 1
 Boat Dock on Property 'Y'


 SEAWALL
 String
 1
 Sea Wall on Property 'Y'


 NBLDGCOUNT
 SmallInteger
 2
 Total Number of New Buildings on ParcelTotal Number of New Buildings on Parcel


 NMINBUILTY
 SmallInteger
 2
 Oldest New Building Built


 NMAXBUILTY
 SmallInteger
 2
 Newest New Building Built


 NTOTALAREA
 Double
 8
 Total New Building Area


 NHEATEDARE
 Double
 8
 Total New Heated Area


 NMAXSTORIE
 Double
 8
 Tallest New Building on Parcel


 NBEDROOMS
 Integer
 4
 Total Number of New Bedrooms


 NBATHROOMS
 Double
 8
 Total Number of New Bathrooms/Not For Comm


 NGARAGE
 String
 1
 New Garage on Property 'Y'


 NCARPORT
 String
 1
 New Carport on Property 'Y'


 NPOOL
 String
 1
 New Pool on Property 'Y'


 NBOATDOCK
 String
 1
 New Boat Dock on Property 'Y'


 NSEAWALL
 String
 1
 New Sea Wall on Property 'Y'


 O_NAME
 String
 30
 Owner Name


 O_OTHERS
 String
 120
 Other Owners


 O_CAREOF
 String
 30
 In Care Of Line


 O_ADDR1
 String
 30
 Owner Mailing Address Line 1


 O_ADDR2
 String
 30
 Owner Mailing Address Line 2


 O_CITY
 String
 30
 Owner Mailing City


 O_STATE
 String
 2
 Owner Mailing State


 O_ZIP
 String
 9
 Owner Mailing Zip


 O_COUNTRY
 String
 30
 Owner Mailing Country


 S_1DATE
 Date
 8
 Most Current Sale Date > $100.00


 S_1AMOUNT
 Double
 8
 Sale Amount


 S_1VI
 String
 1
 Sale Vacant or Improved


 S_1TC
 String
 2
 Sale Transaction Code


 S_1TOC
 String
 2
 Sale Transaction Override Code


 S_1OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_2DATE
 Date
 8
 Previous Sale Date > $100.00


 S_2AMOUNT
 Double
 8
 Sale Amount


 S_2VI
 String
 1
 Sale Vacant or Improved


 S_2TC
 String
 2
 Sale Transaction Code


 S_2TOC
 String
 2
 Sale Transaction Override Code


 S_2OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_3DATE
 Date
 8
 Next Previous Sale Date > $100.00


 S_3AMOUNT
 Double
 8
 Sale Amount


 S_3VI
 String
 1
 Sale Vacant or Improved


 S_3TC
 String
 2
 Sale Transaction Code


 S_3TOC
 String
 2
 Sale Transaction Override Code


 S_3OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_4DATE
 Date
 8
 Next Previous Sale Date > $100.00


 S_4AMOUNT
 Double
 8
 Sale Amount


 S_4VI
 String
 1
 Sale Vacant or Improved


 S_4TC
 String
 2
 Sale Transaction Code


 S_4TOC
 String
 2
 Sale Transaction Override Code


 S_4OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 LEGAL
 String
 255
 Full Legal Description (On Deed)


 GARBDIST
 String
 3
 County Garbage Hauling Area


 GARBTYPE
 String
 1
 County Garbage Pick-up Type


 GARBCOMCAT
 String
 1
 County Garbage Commercial Category


 GARBHEADER
 String
 1
 Garbage Header Code


 GARBUNITS
 Double
 8
 Number of Garbage Units


 CREATEYEAR

Publication Date: April 2025. Updated annually, or as needed. The data can be downloaded here: https://gis.ny.gov/parcels#data-download. This feature service only contains parcel data for NYS State-owned tax parcels. 2024 Parcel geometry was incorporated as received from County Real Property Departments. No attempt was made to edge-match parcels along adjacent counties. County attribute values were populated using 2024 Assessment Roll tabular data NYS ITS Geospatial Services obtained from the NYS Department of Tax and Finance’s Office of Real Property Tax Services (ORPTS).Tabular assessment data was joined to the county provided parcel geometry using the SWIS & SBL or SWIS & PRINT KEY unique identifier for each parcel. Detailed information about assessment attributes can be found in the ORPTS Assessor’s Manuals available here: https://www.tax.ny.gov/research/property/assess/manuals/assersmanual.htm. New York City data comes from NYC MapPluto which can be found here: https://www1.nyc.gov/site/planning/data-maps/open-data/dwn-pluto-mappluto.page. The State-owned tax parcel polygons in this file are the result of a best effort selection based on the Primary Owner and Additional Owner fields in the NYS Statewide Tax Parcels file, Geospatial Services data, State agency data, and online research. These same data and information are also the basis for a best effort assignment of a NYS agency name (listed in the NYS Name field) to most tax parcel polygons where the Owner Type field value is State. The NYS Name Source field consists of a code that describes how the State-owned designation and agency name were determined, if this was verified, and the means of verification, if applicable.This map service is available to the public.The State of New York, acting through the New York State Office of Information Technology Services, makes no representations or warranties, express or implied, with respect to the use of or reliance on the Data provided. The User accepts the Data provided “as is” with no guarantees that it is error free, complete, accurate, current or fit for any particular purpose and assumes all risks associated with its use. The State disclaims any responsibility or legal liability to Users for damages of any kind, relating to the providing of the Data or the use of it. Users should be aware that temporal changes may have occurred since this Data was created.

August 2025

The Virginia Geographic Information Network (VGIN) has coordinated the development and maintenance of a statewide Parcels data layer in conjunction with local governments across the Commonwealth. The Virginia Parcel dataset is aggregated as part of the VGIN Local Government Data Call update cycle. Localities are encouraged to submit data bi-annually and are included into the parcel dataset with their most recent geography.Attributes for these Virginia parcels are limited to locality identification and parcel id. Tax parcel boundaries have not been edge-matched across municipal boundaries but they are associated by local government FIPS and locality name.The boundaries are intended for cartographic use and spatial analysis only, and not for use as legal descriptions or property surveys. Not all localities within the Commonwealth of Virginia have confirmed a digital record for parcel geography or submit data with a bi-annual frequency.GDB Version: ArcGIS Pro 3.3Additional Resources:Shapefile DownloadREST EndpointVirginia Parcels: Local Schema Tables

The Cumberland County GIS Data Viewer provides the general public with parcel, zoning, hydrology, soils, utilities and topographic data. You can search for a specific address, street name, parcel number (PIN), or by the owner's name.

Update information can be found within the layer’s attributes and in a table on the Utah Parcel Data webpage under Basic Parcels."Database containing parcel boundary, parcel identifier, parcel address, owner type, and county recorder contact information" - HB113. The intent of the bill was to not include any attributes that the counties rely on for data sales. If you want other attributes associated with the parcels you need to contact the county recorder.Users should be aware the owner type field 'OWN_TYPE' in the parcel polygons is a very generalized ownership type (Federal, Private, State, Tribal). It is populated with the value of the 'OWNER' field where the parcel's centroid intersects the CADASTRE.LandOwnership polygon layer.This dataset is a snapshot in time and may not be the most current. For the most current data contact the county recorder.

ALK — Automated Property Map in Saarland The ALK is the digitally-run property map, also known as the hallway or cadastral map, as a representing part of the real estate register. This is a nationwide and leaf-free representation of the geometry, location and shape of the parcels/lots and buildings with uniform spatial reference: Other objects include land use, trade names, street names, house numbers, classification of road and water bodies, public regulations such as water, nature and monument conservation areas, surveying and border points. Coordinate dimension: 2D (no heights) Coordinate unit: Meters, even-cartographic.

County assessor's online applications for searching and rviewing data about parcels and proprties.

A list of central and local government land in England, which may not be registered with HM Land Registry (HMLR).

HMLR has created this dataset for the Ministry for Housing, Communities and Local Government (MHCLG) by combining HMLR freehold polygon data with the public sector ownership data currently openly available from the Office of Government Property.

The dataset is not definitive or complete as not all central and local government data is captured, and/or available, and the two datasets are not held in the same format. The list is therefore indicative rather than definitive.

Intellectual Property Rights

The dataset includes address data processed against Ordnance Survey’s AddressBase Premium product and incorporates Royal Mail’s PAF® database (Address Data). Royal Mail and Ordnance Survey permit your use of Address Data:

• for personal and/or non-commercial use
• in relation to the analysis of public sector land and property.

If you want to use the Address Data in any other way, you must contact Royal Mail. Email

Address data

The following fields comprise the address data included in the dataset

• Property Name
• Street No
• Road
• Town
• Postcode

The Easiest Way to Collect Data from the Internet Download anything you see on the internet into spreadsheets within a few clicks using our ready-made web crawlers or a few lines of code using our APIs

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Easy to Use Crawlers Amazon Product Details and Pricing Scraper Amazon Product Details and Pricing Scraper Get product information, pricing, FBA, best seller rank, and much more from Amazon.

Google Maps Search Results Google Maps Search Results Get details like place name, phone number, address, website, ratings, and open hours from Google Maps or Google Places search results.

Twitter Scraper Twitter Scraper Get tweets, Twitter handle, content, number of replies, number of retweets, and more. All you need to provide is a URL to a profile, hashtag, or an advance search URL from Twitter.

Amazon Product Reviews and Ratings Amazon Product Reviews and Ratings Get customer reviews for any product on Amazon and get details like product name, brand, reviews and ratings, and more from Amazon.

Google Reviews Scraper Google Reviews Scraper Scrape Google reviews and get details like business or location name, address, review, ratings, and more for business and places.

Walmart Product Details & Pricing Walmart Product Details & Pricing Get the product name, pricing, number of ratings, reviews, product images, URL other product-related data from Walmart.

Amazon Search Results Scraper Amazon Search Results Scraper Get product search rank, pricing, availability, best seller rank, and much more from Amazon.

Amazon Best Sellers Amazon Best Sellers Get the bestseller rank, product name, pricing, number of ratings, rating, product images, and more from any Amazon Bestseller List.

Google Search Scraper Google Search Scraper Scrape Google search results and get details like search rank, paid and organic results, knowledge graph, related search results, and more.

Walmart Product Reviews & Ratings Walmart Product Reviews & Ratings Get customer reviews for any product on Walmart.com and get details like product name, brand, reviews, and ratings.

Scrape Emails and Contact Details Scrape Emails and Contact Details Get emails, addresses, contact numbers, social media links from any website.

Walmart Search Results Scraper Walmart Search Results Scraper Get Product details such as pricing, availability, reviews, ratings, and more from Walmart search results and categories.

Glassdoor Job Listings Glassdoor Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Glassdoor.

Indeed Job Listings Indeed Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Indeed.

LinkedIn Jobs Scraper Premium LinkedIn Jobs Scraper Scrape job listings on LinkedIn and extract job details such as job title, job description, location, company name, number of reviews, and more.

Redfin Scraper Premium Redfin Scraper Scrape real estate listings from Redfin. Extract property details such as address, price, mortgage, redfin estimate, broker name and more.

Yelp Business Details Scraper Yelp Business Details Scraper Scrape business details from Yelp such as phone number, address, website, and more from Yelp search and business details page.

Zillow Scraper Premium Zillow Scraper Scrape real estate listings from Zillow. Extract property details such as address, price, Broker, broker name and more.

Amazon product offers and third party sellers Amazon product offers and third party sellers Get product pricing, delivery details, FBA, seller details, and much more from the Amazon offer listing page.

Realtor Scraper Premium Realtor Scraper Scrape real estate listings from Realtor.com. Extract property details such as Address, Price, Area, Broker and more.

Target Product Details & Pricing Target Product Details & Pricing Get product details from search results and category pages such as pricing, availability, rating, reviews, and 20+ data points from Target.

Trulia Scraper Premium Trulia Scraper Scrape real estate listings from Trulia. Extract property details such as Address, Price, Area, Mortgage and more.

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This dataset is refreshed on a weekly basis from the datasets the team works on daily.Last update date: 29 August 2025.National Highways Operational Highway Boundary (RedLine) maps out the land belonging to the highway for the whole Strategic Road Network (SRN). It comprises two layers; one being the an outline and another showing the registration status / category of land of land that makes up the boundary. Due to the process involved in creating junctions with local highway authority (LHA) roads, land in this dataset may represent LHA highway (owned by National Highways but the responsibility of the LHA to maintain). Surplus land or land held for future projects does not form part of this dataset.The highway boundary is derived from:Ordnance Survey Mastermap Topography,HM Land Registry National Polygon Service (National Highway titles only), andplots researched and digitised during the course of the RedLine Boundary Project.The boundary is split into categories describing the decisions made for particular plots of land. These categories are as follows:Auto-RedLine category is for plots created from an automated process using Ordnance Survey MasterMap Topography as a base. Land is not registered under National Highways' name. For example, but not limited to, unregistered ‘ancient’ highway vested in Highways England, or bridge carrying highways over a rail line.NH Title within RedLine category is for plots created from Land Registry Cadastral parcels whose proprietor is National Highways or a predecessor. Land in this category is within the highway boundary (audited) or meets a certain threshold by the algorithm.NH Title outside RedLine category is for plots created in the same way as above but these areas are thought to be outside the highway boundary. Where the Confidence is Low, land in this category is yet to be audited. Where the Confidence is High, land in this category has been reviewed and audited as outside our operational boundary.National Highways (Technician) Data category is for plots created by National Highways, digitised land parcels relating to highway land that is not registered, not yet registered or un-registerable.Road in Tunnel category, created using tunnel outlines from Ordnance Survey MasterMap Topography data. These represent tunnels on Highways England’s network. Land is not registered under National Highways' name, but land above the tunnel may be in National Highways’ title. Please refer to the definitive land ownership records held at HM Land Registry.The process attribute details how the decision was made for the particular plot of land. These are as follows:Automated category denotes data produced by an automated process. These areas are yet to be audited by the company.Audited category denotes data that has been audited by the company.Technician Data (Awaiting Audit) category denotes data that was created by National Highways but is yet to be audited and confirmed as final.The confidence attribute details how confident you can be in the decision. This attribute is derived from both the decisions made during the building of the underlying automated dataset as well as whether the section has been researched and/or audited by National Highways staff. These are as follows:High category denotes land that has a high probability of being within the RedLine boundary. These areas typically are audited or are features that are close to or on the highway.Moderate category denotes land that is likely to be within the highway boundary but is subject to change once the area has been audited.Low category denotes land that is less likely to be within the highway boundary. These plots typically represent Highways England registered land that the automated process has marked as outside the highway boundary.Please note that this dataset is indicative only. For queries about this dataset please contact the GIS and Research Team.

The ALKIS® planning map contains boundaries and numbers of parcels, buildings, waters, administrative borders and road names. With its scale, it forms the link between the corridor map and the topographic map. For reasons of legibility, the ALKIS® planning map is generalised, i.e. it is dispensed with border and fixed point signatures, house numbers and no longer displayable parcel numbers, street names. The ALKIS® scheduling card is delivered as a grid file or as an analog output in whole map sheets, square tiles or as sheet-cut-free raster data sections in grayscales. It can also be delivered with height lines (DHK) and/or digital orthophotos (DOP). In combination with DOP, the lines are displayed in yellow overlapping. The raster file is offered with a duck resolution of 600 dpi.

A map and list of addresses in Greater Sudbury. The address point file is a point representation of over 60,000 primary and secondary addresses within the City of Greater Sudbury. Data includes addresses on primary structures (e.g. houses and businesses) and secondary address points which represent buildings that are more than 250 ft. from a primary structure. Updated daily as changes are made to our source data.OBJECTID/ADDRESSID - Simply Unique IdentifiersSTYPE - Primary or Secondary. Primary identify a place or residence. which represent buildings that are more than 250 ft. from a primary structure. ADDRESSLIFECYCLESTATUS - Typically Active or Retired. Retired Addresses may occur on lot splits or during address validation exercisesADDRESSALIAS - Where the full text address may have another 'known' name (ex: 3720 Municipal Road 80, 3720 Highway 69 North)ADDRESSNUMBERPREFIX - Prefix to a full text address. ( AddressNumber AddressNumberPrefix Streetname Addressnumbersuffix)ADDRESSNUMBER- The address number,ADDRESSNUMBERSUFFIX - Suffix to the full text address ( AddressNumber AddressNumberPrefix Streetname Addressnumbersuffix)COMMUNITY - Community that the point belongs too.LASTUPDATE - Any time the data point is moved or attribute information is updated this field gets timestamped.CREATEDATE - When the data point gets created this field gets timestamped.ASSIGNEDADDRESSID - The “AssignedAddressID” represents a relationship between addresses and commercial or residential units that fall within. The “AssignedAddressID”, where relevant, will equal the “AddressID” of the appropriate address. UNIT_OR_AMENITY - Field to aid in filtering data based on the point.UNIT_AMENITY_TYPE - Field to aid in filtering data based on the point.NAME - IF an amenity was collected will contain the name of this amenity (Ex. Schoolnames, restuarant names)VERIFIED_DATE - Simply a timestamp identifying if the City has been requested to verify an existing address.

LINZ maintains a point layer of primary address points allocated by local councils for rateable properties. The principle purpose of this dataset is to allocate voters to the correct electorate. The set is actively maintained, but is still incomplete and some locations are incorrect. Nevertheless it is by far the most comprehensive address database available.

It includes all (allocated) rural address points (RAPID numbers), commercial addresses and many flat numbers. So numbers are not numeric, there are all sorts of formats included here, sorry. Addresses are not unique. The points are "location addresses", not "postal addresses". For residential town addresses this is normally the same, but for commercial and rural locations they are not the same.

Primary addresses are only the number and alpha parts. Not included is a flat, unit, apartment, floor or other subdivision of the main property address. They should also not be a range, simply the entrance to the property.

Address points only have a number and a key to a road centreline segment. They did not contain a full address or postcode as you see here.

Road names in the address are joined from the road centreline segments All road names in this database are official, with a locality (suburb or town) allocated to make the complete address unique within a local council district. Road names are unique if you include the location and local authority name as part of the name. The postcode alone does not make an address unique because they cover too large an area and NZPost use a different surburb/mailtown/postcode composite key.

The locality is not derived from the road centrelines. These are not useful because the do not have a left and right and do not reflect common usage. Instead the Fire Service locality polygons have been used to tag the addresses with the preferred name. I know it may not be the name used elsewhere, so a geocoder allows for alternatives.

These addresses are a "situation" or "location" address, not a "delivery address" or "property identifier". It does not have complete flat or unit numbers, although there are some due to confusion in the purpose of the database, so you will see some.

NZ Post uses this dataset to maintain their GeoPAF file which is a subset of this data because they only supply 'deliverable' addresses where they deliver mail. Therefore no commercial or rural addresses are included in the PAF (PO Boxes are the postal address for these properties). The postcode has been added from an authoritative postcode map. Postcodes are for bulk mail sorting, not for defining a unique location address. (NZPost will supplement the PAF with all address points for a significant fee.)

Note that an address number is related to the road centreline. No road - no address. It is a linear referencing system, starting at one end, continuing in sequence to the end of the road with odd numbers on one side and even numbers on the other. In towns the spacing is approximately 20 metres, and in the country it is 200 metres.

Addresses are NOT related to parcels and should not be a property key because they are not unique, consider a corner section. They do not define property boundaries. Think of addresses as the location of the letterbox marking the entrance to the property, not the building. The mapped point is generally located 15 metres from the centreline at the entrance or at the neck of a rear section. Address ranges on a point are deprecated in the NZ address standard, a single number should be allocated to the principle entrance so the fire service can find it quickly and unambiguously.

This is different from base address ranges with parity and direction on a road centreline which would be really useful and are common overseas but do not exist for NZ. Even private sets are not done properly. A base address is a simple integer with a range of 1 - 99999.

See Where The Hell Are You? for more explanation on the confusion between an address and a property and the NZ Address Standard AS/NZS 4819:2003.

Meshblock codes for the 2013 census have been added.

Source LINZ Bulk Data Extract August 2014, Postcodes Feb 2014

UPS Facilities Locations Dataset

Locations and Details of UPS Facilities across the United States

By Homeland Infrastructure Foundation [source]

About this dataset

The UPS Facilities dataset is a comprehensive collection of information about UPS (United Parcel Service) facilities located across the United States. This dataset provides details on the location, placement, and contact information of each facility.

The dataset includes various columns such as X and Y coordinates, which indicate the longitude and latitude coordinates respectively. These coordinates pinpoint the exact geographic location of each UPS facility. Additionally, there are columns for the name of each facility, address including street address and additional information (ADDRESS2 and ADDRESS3), city, state, ZIP code, phone number for contact purposes.

Furthermore, this dataset provides insightful information about each facility's match status in terms of its address accuracy or completeness. It also includes details about the specific business associated with each UPS facility.

In addition to these data points, there are columns that provide census codes for each facility location. These codes offer additional contextual information related to demographic and socio-economic characteristics associated with each area where a UPS facility is situated.

Overall, this extensive dataset serves as a comprehensive resource for researchers or businesses looking to analyze or utilize information regarding UPS facilities across different states in the United States

How to use the dataset

Introduction:

• Understanding the Dataset Structure: The dataset consists of several columns that provide relevant information about each UPS facility location. Here is a brief overview of the key columns:

• NAME: The name of the UPS facility.

• ADDRESS: The street address of the UPS facility.

• ADDRESS2/ADDRESS3: Additional address information for the facility.

• CITY/STATE/ZIP: The city, state, and ZIP code where the facility is located.

• PHONE: The contact phone number for the facility.

Additionally, there are geographic coordinates (LATITUDE and LONGITUDE) representing each facility's precise location on a map. Other columns such as PLACEMENT, MATCHSTATU, CENSUSCODE, and BUSINESSNA provide further context regarding placement status, address matching status, census codes for locations, and associated business names.

• Potential Use Cases:

a) Visualizing Facility Distribution: Using latitude and longitude coordinates from this dataset with mapping tools like Python's Folium or Tableau can help create interactive maps that showcase spatial distributions across different regions.

b) Analyzing Facility Density: By aggregating data at regional levels (e.g., state-wise), you can analyze which areas have higher concentrations of UPS facilities compared to others. This analysis may offer insights into patterns related to population density or commercial activity.

c) Optimizing Transportation Routes: Understanding where these facilities are located can be beneficial for route optimization. By analyzing facility placements and their proximity to transportation networks, you can identify potential areas for streamlining logistics operations.

d) Market Research: The dataset's additional columns (such as BUSINESSNA) allow researchers to analyze UPS facilities within the context of associated businesses. This information can be useful for market research, identifying industry clusters, or studying supply chain dynamics.

• Data Cleaning and Preprocessing: Before utilizing this dataset, it is recommended to perform standard data cleaning procedures, such as handling missing or incorrect values. Pay attention to any inconsistencies in column names or encoding formats that may require normalization.

• Combining with Other Datasets: To

Research Ideas

• Geospatial analysis: This dataset can be used for geospatial analysis to analyze the distribution and concentration of UPS facilities across different states or cities. It can help identify areas with high or low availability of UPS services and assist logistics planning and decision making.
• Customer segmentation: By combining this dataset with customer data, businesses can segment their customers based on proximity to UPS facilities. This can help companies optimize their delivery routes, improve customer service, and target marketing efforts more effectively.
• Benchmarking and competition analysis: The dataset can also be used for benchmarking purposes by comparing the number of UPS facilities in different regions or against competito...

The Canada Basemap – Transportation (CBMT) is a vector tile service that provides spatial reference context with an emphasis on transportation networks across Canada. It is designed especially for use as a background layer in a web mapping application or geographic information system (GIS). Access: Access is free of charge under the terms of the Open Government Licence - Canada. Data Sources: Data for the CBMT is sourced from multiple datasets. - Topographic data of Canada - CanVec Series. - “Automatically Extracted Buildings” GeoBase (a raw digital product in vector format automatically extracted from airborne Lidar data, high-resolution optical imagery or other sources). - Open Street Map (OSM) data available under the Open Database License (https://www.openstreetmap.org/copyright). - Official names from the Canadian Geographical Names Database (CGNDB). Geographic Coverage: CBMT has complete coverage of the world, with full datasets in Canada and only partial data in other parts of the world including boundaries, Country Names, and major cities. Data Update Frequency: Updates are applied monthly to reflect the latest updates in the source datasets. Projection: Data is provided in the EPSG:3857 (WGS84 Pseudo-Mercator) projected coordinate system. Layer Access: - CBMT is accessible via the ArcGIS Online item link with the applied style or it can also be accessed directly with the default style using the following Vector Tile Server: https://tiles.arcgis.com/tiles/HsjBaDykC1mjhXz9/arcgis/rest/services/CBMT_CBCT_3857_V_OSM/VectorTileServer - In QGIS or other applications that require the style JSON, the following link can be used: https://arcgis.com/sharing/rest/content/items/800d755712e8415aab301b9d55bc2800/resources/styles/root.json Use Cases: This layer is suitable for use in any map as a basemap layer and can be modified to meet the needs of the project by editing the JSON style in the Vector Tile Style editor. Additional Versions: - A geometry-only version (CBMT3857GEOM) and a text-only version (CBMT3857TXT) are available. - French versions of the basemap are accessible via the Carte de base du Canada - Transport 3857 V (CBCT3857).

The Canada Basemap – Transportation (CBMT) is a vector tile service that provides spatial reference context with an emphasis on transportation networks across Canada. It is designed especially for use as a background layer in a web mapping application or geographic information system (GIS). Access: Access is free of charge under the terms of the Open Government Licence - Canada. Data Sources: Data for the CBMT is sourced from multiple datasets. - Topographic data of Canada - CanVec Series - “Automatically Extracted Buildings” GeoBase (a raw digital product in vector format automatically extracted from airborne Lidar data, high-resolution optical imagery or other sources.) - Open Street Map (OSM) data available under the Open Database License (https://www.openstreetmap.org/copyright). - Official names from the Canadian Geographical Names Database (CGNDB). Geographic Coverage: CBMT covers the entire geographic area of Canada and some major transportation routes and cities in the northern States of the USA. Data Update Frequency: Updates are applied monthly to reflect the latest updates in the source datasets. Projection: Data is provided in the EPSG:3978 (NAD83 Canada Atlas Lambert) projected coordinate system. Layer Access: - CBMT is accessible via the ArcGIS Online item link with the applied style or it can also be accessed directly with the default style using the following Vector Tile Server: https://tiles.arcgis.com/tiles/HsjBaDykC1mjhXz9/arcgis/rest/services/CBMT_CBCT_3978_V_OSM/VectorTileServer - In QGIS or other applications that require the style JSON, the following link can be used: https://arcgis.com/sharing/rest/content/items/708e92c1f00941e3af3dd3c092ae4a0a/resources/styles/root.json Use Cases: This layer is suitable for use in any map as a basemap layer and can be modified to meet the needs of the project by editing the JSON style in the Vector Tile Style editor. Additional Versions: - A geometry-only version (CBMT3978GEOM) and a text-only version (CBMT3978TXT) are available. - French versions of the basemap are accessible via the Carte de base du Canada - Transport 3978 V (CBCT3978).

HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) provides hydrographic information in a consistent and comprehensive format for regional and global-scale applications. HydroSHEDS offers a suite of geo-referenced data sets in raster and vector format, including stream networks, watershed boundaries, drainage directions, and ancillary data layers such as flow accumulations, distances, and river topology information. The goal of developing HydroSHEDS was to generate key data layers to support regional and global watershed analyses, hydrological modeling, and freshwater conservation planning at a quality, resolution and extent that has previously been unachievable. Available resolutions range from 3 arc-second (approx. 90 meters at the equator) to 5 minute (approx. 10 km at the equator) with seamless near-global extent. HydroSHEDS has been developed by the Conservation Science Program of World Wildlife Fund (WWF), in partnership or collaboration with the U.S. Geological Survey (USGS); the International Centre for Tropical Agriculture (CIAT); The Nature Conservancy (TNC); McGill University, Montreal, Canada; the Australian National University, Canberra, Australia; and the Center for Environmental Systems Research (CESR), University of Kassel, Germany. Major funding for this project was provided to WWF by JohnsonDiversey, Inc. and Sealed Air Corporation. HydroSHEDS data are free for non-commercial and commercial use. See License Agreement for specific restrictions and use requirements. This product [insert Licensee Derivative Product name] incorporates data from the HydroSHEDS database which is © World Wildlife Fund, Inc. (2006-2013) and has been used herein under license. WWF has not evaluated the data as altered and incorporated within [insert Licensee Derivative Product name], and therefore gives no warranty regarding its accuracy, completeness, currency or suitability for any particular purpose. Portions of the HydroSHEDS database incorporate data which are the intellectual property rights of © USGS (2006-2008), NASA (2000-2005), ESRI (1992-1998), CIAT (2004-2006), UNEP-WCMC (1993), WWF (2004), Commonwealth of Australia (2007), and Her Royal Majesty and the British Crown and are used under license. The HydroSHEDS database and more information are available at http://www.hydrosheds.org.