Welcome to Apiscrapy, your ultimate destination for comprehensive location-based intelligence. As an AI-driven web scraping and automation platform, Apiscrapy excels in converting raw web data into polished, ready-to-use data APIs. With a unique capability to collect Google Address Data, Google Address API, Google Location API, Google Map, and Google Location Data with 100% accuracy, we redefine possibilities in location intelligence.

Key Features:

Unparalleled Data Variety: Apiscrapy offers a diverse range of address-related datasets, including Google Address Data and Google Location Data. Whether you seek B2B address data or detailed insights for various industries, we cover it all.

Integration with Google Address API: Seamlessly integrate our datasets with the powerful Google Address API. This collaboration ensures not just accessibility but a robust combination that amplifies the precision of your location-based insights.

Business Location Precision: Experience a new level of precision in business decision-making with our address data. Apiscrapy delivers accurate and up-to-date business locations, enhancing your strategic planning and expansion efforts.

Tailored B2B Marketing: Customize your B2B marketing strategies with precision using our detailed B2B address data. Target specific geographic areas, refine your approach, and maximize the impact of your marketing efforts.

Use Cases:

Location-Based Services: Companies use Google Address Data to provide location-based services such as navigation, local search, and location-aware advertisements.

Logistics and Transportation: Logistics companies utilize Google Address Data for route optimization, fleet management, and delivery tracking.

E-commerce: Online retailers integrate address autocomplete features powered by Google Address Data to simplify the checkout process and ensure accurate delivery addresses.

Real Estate: Real estate agents and property websites leverage Google Address Data to provide accurate property listings, neighborhood information, and proximity to amenities.

Urban Planning and Development: City planners and developers utilize Google Address Data to analyze population density, traffic patterns, and infrastructure needs for urban planning and development projects.

Market Analysis: Businesses use Google Address Data for market analysis, including identifying target demographics, analyzing competitor locations, and selecting optimal locations for new stores or offices.

Geographic Information Systems (GIS): GIS professionals use Google Address Data as a foundational layer for mapping and spatial analysis in fields such as environmental science, public health, and natural resource management.

Government Services: Government agencies utilize Google Address Data for census enumeration, voter registration, tax assessment, and planning public infrastructure projects.

Tourism and Hospitality: Travel agencies, hotels, and tourism websites incorporate Google Address Data to provide location-based recommendations, itinerary planning, and booking services for travelers.

Discover the difference with Apiscrapy – where accuracy meets diversity in address-related datasets, including Google Address Data, Google Address API, Google Location API, and more. Redefine your approach to location intelligence and make data-driven decisions with confidence. Revolutionize your business strategies today!

NZ Parcel Boundaries Wireframe provides a map of land, road and other parcel boundaries, and is especially useful for displaying property boundaries.
This map service is for visualisation purposes only and is not intended for download. You can download the full parcels data from the NZ Parcels dataset.
This map service provides a dark outline and transparent fill, making it perfect for overlaying on our basemaps or any map service you choose.
Data for this map service is sourced from the NZ Parcels dataset which is updated weekly with authoritative data direct from LINZ’s Survey and Title system. Refer to the NZ Parcel layer for detailed metadata.
To simplify the visualisation of this data, the map service filters the data from the NZ Parcels layer to display parcels with a status of 'current' only.
This map service has been designed to be integrated into GIS, web and mobile applications via LINZ’s WMTS and XYZ tile services. View the Services tab to access these services.
See the LINZ website for service specifications and help using WMTS and XYZ tile services and more information about this service.

In 2016 NYC Parks contracted with the UVM Spatial Analysis Lab to use modern remote sensing and object-based image analysis to create a new wetlands map for New York City. Data inputs include Light Detection and Ranging Data, State and Federal Wetland Inventories, soils, and field data. Because the map was conservative in its wetlands predictions, NYC Parks staff improved the map through a series of desktop and field verification efforts. From June to November 2020, NYC Parks staff field verified the majority of wetlands on NYC Parks' property. The map will be opportunistically updated depending on available field information and delineations. Another dedicated field verification effort has not been planned. As of June 2021, no subsequent updates to the data are scheduled. Original field names were updated to field names that are easier to understand. This dataset was developed to increase awareness regarding the location and extent of wetlands to promote restoration and conservation in New York City. This map does not supersede U.S. Fish and Wildlife Service National Wetlands Inventory (NWI) and New York State Department of Environmental Conservation (NYSDEC) wetlands maps and has no jurisdictional authority. It should be used alongside NWI and NYSDEC datasets as a resource for identifying likely locations of wetlands in New York City. Mapped features vary in the confidence of their verification status, ranging from "Unverified" (meaning the feature exists in its original remotely mapped form and has not been ground truthed) to "Verified - Wetland Delineation" (meaning the boundaries and type of wetland have been verified during an official wetland delineation). Because of the rapid nature of the protocol and the scale of data collection, this product is not a subsitute for on-site investigations and field delineations. The dataset also includes broad classifications for each wetland type, e.g. estuarine, emergent wetland, forested wetland, shrub/scrub wetland, or water. Cowardin classifcations were not used given rapid verfication methods. The accuracy of the wetlands map has improved over time as a result of the verification process. Fields were added over time as necessitated by the workflow and values were updated with information, either from the field verifications, delineation reports, or desktop analysis. OBJECTID, Shape, Class_Name_Final, Verification_Status, Create_Date, Last_Edited_Date, Verification_Status_Year, SHAPE_Length, SHAPE_Area https://www.nycgovparks.org/greening/natural-resources-group Data Dictionary: https://docs.google.com/spreadsheets/d/1a45qCho45MV-AuOlGxyaRp0cg3cRFKw4lAYBIaU3zi4/edit#gid=260500519 Map: https://data.cityofnewyork.us/dataset/NYC-Wetlands/7piy-bhr9

🇺🇸 미국 English In 2016 NYC Parks contracted with the UVM Spatial Analysis Lab to use modern remote sensing and object-based image analysis to create a new wetlands map for New York City. Data inputs include Light Detection and Ranging Data, State and Federal Wetland Inventories, soils, and field data. Because the map was conservative in its wetlands predictions, NYC Parks staff improved the map through a series of desktop and field verification efforts. From June to November 2020, NYC Parks staff field verified the majority of wetlands on NYC Parks' property. The map will be opportunistically updated depending on available field information and delineations. Another dedicated field verification effort has not been planned. As of June 2021, no subsequent updates to the data are scheduled. Original field names were updated to field names that are easier to understand. This dataset was developed to increase awareness regarding the location and extent of wetlands to promote restoration and conservation in New York City. This map does not supersede U.S. Fish and Wildlife Service National Wetlands Inventory (NWI) and New York State Department of Environmental Conservation (NYSDEC) wetlands maps and has no jurisdictional authority. It should be used alongside NWI and NYSDEC datasets as a resource for identifying likely locations of wetlands in New York City. Mapped features vary in the confidence of their verification status, ranging from "Unverified" (meaning the feature exists in its original remotely mapped form and has not been ground truthed) to "Verified - Wetland Delineation" (meaning the boundaries and type of wetland have been verified during an official wetland delineation). Because of the rapid nature of the protocol and the scale of data collection, this product is not a subsitute for on-site investigations and field delineations. The dataset also includes broad classifications for each wetland type, e.g. estuarine, emergent wetland, forested wetland, shrub/scrub wetland, or water. Cowardin classifcations were not used given rapid verfication methods. The accuracy of the wetlands map has improved over time as a result of the verification process. Fields were added over time as necessitated by the workflow and values were updated with information, either from the field verifications, delineation reports, or desktop analysis. OBJECTID, Shape, Class_Name_Final, Verification_Status, Create_Date, Last_Edited_Date, Verification_Status_Year, SHAPE_Length, SHAPE_Area https://www.nycgovparks.org/greening/natural-resources-group Data Dictionary: https://docs.google.com/spreadsheets/d/1a45qCho45MV-AuOlGxyaRp0cg3cRFKw4lAYBIaU3zi4/edit#gid=260500519 Map: https://data.cityofnewyork.us/dataset/NYC-Wetlands/7piy-bhr9

ParcelMap BC is the current, complete and trusted mapped representation of titled and Crown land parcels across British Columbia, considered to be the point of truth for the graphical representation of property boundaries. It is not the authoritative source for the legal property boundary or related records attributes; this will always be the plan of survey or the related registry information. This particular dataset is a subset of the complete ParcelMap BC data and is comprised of the parcel fabric and attributes for over two million parcels published under the Open Government Licence - British Columbia. Notes: 1. Parcel title information is sourced from the BC Land Title Register. Title questions should be directed to a local Land Title Office. 2. This dataset replaces the Integrated Cadastral Fabric.

This dataset identifies property managed partially or solely by NYC Parks. This data has been produced in whole or part using secondary data. Data accuracy is limited by the scale and accuracy of the original sources. Site-specific conditions should be field-verified.

Records are added as more land is designated under NYC Parks’ jurisdiction. Each record represents an acquisition.

User Guide: https://docs.google.com/document/d/1NExNJF5YKID04oOopi0fHainRuGG3Pz_jKSrMujPsPk/edit?usp=sharing

Data Dictionary: https://docs.google.com/spreadsheets/d/1Q4DBWu7riNFxWvy1vnTJHoOI3r2L9oW6eCN56jCNyCw/edit?usp=sharing

This map displays franchise areas for the telephone companies that provider service in Vermont.The layers displayed include:- VT Data - E911 address points- VT Data - Town Boundaries- Telephone Company Central Offices - Telephone Wirecenter BoundariesTelephone Company Central OfficesThis dataset depicts the E-911 locations of the incumbent local exchange carrier (ILEC) central offices in Vermont. This information was collected from public property tax parcel information. Each site was then viewed on Google Earth Street View for confirmation.Telephone Wirecenter BoundariesBoundaries of the wirecenter serving areas for incumbent local exchange carriers (ILECs) in Vermont. The boundaries were developed from the paper maps by the Vermont Public Service Department (PSD) in the 1990s. This dataset was reviewed by the ILECs for an FCC process in 2013. The feature names were reviewed and updated then. The actual boundary polygons are of unknown precision and are therefore useful only for general analysis.DISCLAIMER: VCGI and the State of Vermont make no representations of any kind, including but not limited to the warranties of merchantability or fitness for a particular use, nor are any such warranties to be implied with respect to the data.

Summary: A comprehensive NSW Land Tenure layer has been developed, integrating the latest and most reliable datasets sourced from various governmental authorities and departments. To the best of our knowledge, this layer offers detailed mapping of recent updates and changes in land tenure across the state. It includes information on land allocations, ownership transformations, and management updates, providing an up-to-date and accurate representation of land tenure in New South Wales.

Description: The statewide Land Tenure layer is a comprehensive dataset created by incorporating spatial and aspatial data from various state and commonwealth government departments, organisations and authorities, including the Forestry Corporation of NSW; NSW Department of Primary Industries and Regional Development; NSW Spatial Services; Department of Climate Change, Energy, the Environment and Water (Environment and Heritage); The Australian Department of Agriculture, Fisheries and Forestry (ABARES: SOFR23 & SOFR18); the NSW SEED data portal; and National Park. The wall-to-wall spatial feature class demonstrates how land in NSW is being managed or owned. It can also be employed to monitor changes in land management or ownership transfer over time. The process of acquiring datasets for updating the tenure layer and creating the statewide layer began in January 2024 and continued until August 2024. The collected datasets were amalgamated, and gaps were filled. This combined layer has then been manually assessed and visually compared against various datasets to ensure its completeness and accuracy. Esri basemaps such as Imagery, Imagery Hybrid, OpenStreetMap, and Google Earth maps were also used for visual assessment. Furtheremore, expert knowledge from government professionals, and land history web search were considered to address potential inaccuracies and unreliability in datasets from various sources. The land tenure data consists of seven Tenure classes each class covering various tenure types as below: - Tenure Class: presents tenure classification of the dataset as Crownland-Leasehold; Crownland-Other; Indigenous Owned; National Park; Private; State Forest; Unresolved Tenure. Tenure Type of each tenure class are as follow: Crownland-Leasehold: Crown Timberland Lease; LEASE (SOFR2023); Leasehold Crown Land; Western Lands Lease; Crownland-Other: Crown Road; Crown Waterway; Either Crown Waterway, Road or other; OCL (SOFR2023); Other crownland; Public Road; Reserved Crown Timber Land; Timber Reserve; Vacant And Reserved Crown Land; Vacant Crown Land; Reserve for Public Buildings (Forestry); Indigenous Owned: Aboriginal Area; National Park: Conservation Reserve; Fire trail within national parks; Historic Sites; National Park; Nature Reserve; NCR (SOFR2023); Regional Park; State Conservation Area; Private: Hardwood Joint Venture; PRIV (SOFR2023); Private; Hardwood Plantations; Private Property; Private Softwood Plantation; Profit á Prendre; Softwood Joint Venture; State Forest: FCNSW Ownership; MUF (SOFR2023); State Forest: State Forest OEH Managed Flora Reserve; Unresolved Tenure: null (-2); ND (SOFR2023). - Shape_Area: Area of each Tenure class in square meter. Caveats: - In general, data from diverse sources retains different levels of accuracy, reliability and coverage, therefore, a thorough visual assessment has been carried out to overcome the issue. Having said that, there still could be potential minor errors which could have been missed due to the large extent of the dataset. - Note that Roads, Waterways and general public areas across the Greater Sydney and Wollongong have not been properly mapped in this version. This will be updated in the next update.