The average price of detached and duplex houses in the biggest cities in Germany varied between approximately ***** euros and 10,000 euros per square meter in 2024. Housing was most expensive in Munich, where the square meter price of houses amounted to ***** euros. Conversely, Berlin was most affordable, with the square meter price at ***** euros. How have German house prices evolved? House prices maintained an upward trend for more than a decade, with 2020 and 2021 experiencing exceptionally high growth rates. In 2021, the nominal year-on-year change exceeded 10 percent. Nevertheless, the second half of 2022 saw the market slowing, with the annual percentage change turning negative for the first time in 12 years. Another way to examine the price growth is through the house price index, which uses 2015 as a base. At its peak in 2022, the German house price index measured about *** percent, which means that a house bought in 2015 would have appreciated by ** percent. Is housing affordable in Germany? Housing affordability depends greatly on income: High-income areas often tend to have more expensive housing, which does not necessarily make them unaffordable. The house price to income index measures the development of the cost of housing relative to income. In the first quarter of 2024, the index value stood at ***, meaning that since 2015, house price growth has outpaced income growth by about ** percent. Compared with the average for the euro area, this value was lower.

Extract detailed property data points — address, URL, prices, floor space, overview, parking, agents, and more — from any real estate listings. The Rankings data contains the ranking of properties as they come in the SERPs of different property listing sites. Furthermore, with our real estate agents' data, you can directly get in touch with the real estate agents/brokers via email or phone numbers.

A. Usecase/Applications possible with the data:

1. Property pricing - accurate property data for real estate valuation. Gather information about properties and their valuations from Federal, State, or County level websites. Monitor the real estate market across the country and decide the best time to buy or sell based on data

2. Secure your real estate investment - Monitor foreclosures and auctions to identify investment opportunities. Identify areas within special economic and opportunity zones such as QOZs - cross-map that with commercial or residential listings to identify leads. Ensure the safety of your investments, property, and personnel by analyzing crime data prior to investing.

3. Identify hot, emerging markets - Gather data about rent, demographic, and population data to expand retail and e-commerce businesses. Helps you drive better investment decisions.

4. Profile a building’s retrofit history - a building permit is required before the start of any construction activity of a building, such as changing the building structure, remodeling, or installing new equipment. Moreover, many large cities provide public datasets of building permits in history. Use building permits to profile a city’s building retrofit history.

5. Study market changes - New construction data helps measure and evaluate the size, composition, and changes occurring within the housing and construction sectors.

6. Finding leads - Property records can reveal a wealth of information, such as how long an owner has currently lived in a home. US Census Bureau data and City-Data.com provide profiles of towns and city neighborhoods as well as demographic statistics. This data is available for free and can help agents increase their expertise in their communities and get a feel for the local market.

7. Searching for Targeted Leads - Focusing on small, niche areas of the real estate market can sometimes be the most efficient method of finding leads. For example, targeting high-end home sellers may take longer to develop a lead, but the payoff could be greater. Or, you may have a special interest or background in a certain type of home that would improve your chances of connecting with potential sellers. In these cases, focused data searches may help you find the best leads and develop relationships with future sellers.

How does it work?

• Analyze sample data
• Customize parameters to suit your needs
• Add to your projects
• Contact support for further customization

In the Official Property Register Information System (ALKIS®), all data of the property register is merged and maintained integrated. This includes data from the former property map and the former real estate book in ALKIS. The basis for ALKIS® is a technical concept developed by the Association of Surveying Administrations of the Länder of the Federal Republic of Germany (AdV) for the management of all basic data of the official surveying system. All federal states are committed to maintaining an ALKIS basic data base according to this concept. In addition, according to the data model, additional country-specific data are available.

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

Description of INSPIRE Download Service (predefined Atom): In the Official Property Register Information System (ALKIS®), all data of the real estate cadastre are merged and maintained integratedly. This includes data from the former property map and the former property book in ALKIS. The basis for ALKIS® is a technical concept developed by the Association of Surveying Administrations of the Länder of the Federal Republic of Germany (AdV) for the management of all basic data of the official surveying system. All federal states are committed to maintaining an ALKIS baseline database according to this concept. In addition, there are country-specific additional data according to the data model. Color – The link(s) for downloading the records is/are generated dynamically from GetFeature requests to a WFS 1.1.0 Description of INSPIRE Download Service (predefined Atom): In the Official Property Register Information System (ALKIS®), all data of the real estate cadastre are merged and maintained integratedly. This includes data from the former property map and the former property book in ALKIS. The basis for ALKIS® is a technical concept developed by the Association of Surveying Administrations of the Länder of the Federal Republic of Germany (AdV) for the management of all basic data of the official surveying system. All federal states are committed to maintaining an ALKIS baseline database according to this concept. In addition, there are country-specific additional data according to the data model.

Color – The link(s) for downloading the records is/are generated dynamically from GetFeature requests to a WFS 1.1.0

The official real estate cadastre information system (ALKIS) is a product of the working group of the surveying authorities of the federal states of the Federal Republic of Germany (AdV). In ALKIS, the previously separately managed data from the automated real estate book (ALB) and the automated real estate map (ALK point file, ALK floor plan file) were migrated to one information system. ALKIS is now the official real estate cadastre information system. The main building blocks of the program system for ALKIS are the acquisition and qualification component (EQK), the data management component (DHK) and the output and presentation component (APK).

Globally available, ON-DEMAND noise pollution maps generated from real-world measurements (our sample dataset) and AI interpolation. Unlike any other available noise-level data sets! GIS-ready, high-resolution visuals for real estate platforms, government dashboards, and smart city applications.

The Official Property Register Information System (ALKIS) is a product of the Association of Surveying Administrations of the Länder of the Federal Republic of Germany (AdV). In ALKIS, the previously separately managed data of the Automated Property Book (ALB) and the Automated Property Map (ALK point file, ALK floor plan file) were migrated into an information system. ALKIS is now the official real estate register information system. The main building blocks of the ALKIS program system are the acquisition and qualification component (EQK), the data storage component (DHK) and the output and presentation component (APK).

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.

Amazon Customer FAQs Amazon Customer FAQs Get FAQs for any product on Amazon and get details like the question, answer, answered user name, and more.

Yellow Pages Scraper Yellow Pages Scraper Get details like business name, phone number, address, website, ratings, and more from Yellow Pages search results.

GPKG database of Polygons describing the coverage area of every individual cell tower on an operator's network (covering 2G, 3G and 4G. 5G will be available later). Every cell is identified by its GCI and for every GCI we supply a polygon describing the coverage area of that cell tower. The data can be used for network planning, real estate and connected and autonomous vehicles. Note that the data does not describe the locations of the actual towers or enode-B's themselves. This can be provided separately.

The spatial data of the properties of the Official Property Register Information System (ALKIS) can be updated with the user-related inventory data update (NBA procedure). The NBA procedure in ALKIS replaces the BZSN or LBESAS procedures of the previous differential data methods for ALK or ALB data. For this type of ALKIS data provision, the user can determine, among other things, the updating rhythm, the spatial and content scope of the data delivery for his/her requirements. Alkis combines the previously separated and multi-stored data of the Automated Property Book (ALB) and the Automated Property Map (ALK) in one data model. The modelling of ALKIS data is carried out in accordance with the provisions of the GeoInfoDok in version 6.0.1 of the Association of Surveying Administrations of the Länder of the Federal Republic of Germany (AdV). The data is generally provided in NAS format and in the case of recurring updates as difference data in the NBA procedure. The data is provided free of charge via automated procedures. A legitimate interest must be demonstrated for owner data. A fee shall be charged for the examination of these interests. When using the owner data, the AGNB of the LGB must be observed.

Snapshot img

Geographic Information System Analytics Market Size 2024-2028

The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.

What will be the Size of the GIS Analytics Market during the forecast period?

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The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.

How is this Geographic Information System Analytics Industry segmented?

The geographic information system analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  Retail and Real Estate
  Government
  Utilities
  Telecom
  Manufacturing and Automotive
  Agriculture
  Construction
  Mining
  Transportation
  Healthcare
  Defense and Intelligence
  Energy
  Education and Research
  BFSI


Components

  Software
  Services


Deployment Modes

  On-Premises
  Cloud-Based


Applications

  Urban and Regional Planning
  Disaster Management
  Environmental Monitoring Asset Management
  Surveying and Mapping
  Location-Based Services
  Geospatial Business Intelligence
  Natural Resource Management


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    South Korea


  Middle East and Africa

    UAE


  South America

    Brazil


  Rest of World

By End-user Insights

The retail and real estate segment is estimated to witness significant growth during the forecast period.

The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector, gover

Xverum’s Location Data is a highly structured dataset of 230M+ verified locations, covering businesses, landmarks, and points of interest (POI) across 5000 industry categories. With accurate geographic coordinates, business metadata, and mapping attributes, our dataset is optimized for GIS applications, real estate analysis, market research, and urban planning.

With continuous discovery of new locations and regular updates, Xverum ensures that your location intelligence solutions have the most current data on business openings, closures, and POI movements. Delivered in bulk via S3 Bucket or cloud storage, our dataset integrates seamlessly into mapping, navigation, and geographic analysis platforms.

🔥 Key Features:

Comprehensive Location Coverage: ✅ 230M+ locations worldwide, spanning 5000 business categories. ✅ Includes retail stores, corporate offices, landmarks, service providers & more.

Geographic & Mapping Data: ✅ Latitude & longitude coordinates for precise location tracking. ✅ Country, state, city, and postal code classifications. ✅ Business status tracking – Open, temporarily closed, permanently closed.

Continuous Discovery & Regular Updates: ✅ New locations added frequently to ensure fresh data. ✅ Updated business metadata, reflecting new openings, closures & status changes.

Detailed Business & Address Metadata: ✅ Company name, category, & subcategories for industry segmentation. ✅ Business contact details, including phone number & website (if available). ✅ Operating hours for businesses with scheduling data.

Optimized for Mapping & Location Intelligence: ✅ Supports GIS, real estate analysis & smart city planning. ✅ Enhances navigation & mapping solutions with structured geographic data. ✅ Helps businesses optimize site selection & expansion strategies.

Bulk Data Delivery (NO API): ✅ Delivered via S3 Bucket or cloud storage for full dataset access. ✅ Available in a structured format (.json) for easy integration.

🏆 Primary Use Cases:

Location Intelligence & Mapping: 🔹 Power GIS platforms & digital maps with structured geographic data. 🔹 Integrate accurate location insights into real estate, logistics & market analysis.

Retail Expansion & Business Planning: 🔹 Identify high-traffic locations & competitors for strategic site selection. 🔹 Analyze brand distribution & presence across different industries & regions.

Market Research & Competitive Analysis: 🔹 Track openings, closures & business density to assess industry trends. 🔹 Benchmark competitors based on location data & geographic presence.

Smart City & Infrastructure Planning: 🔹 Optimize city development projects with accurate POI & business location data. 🔹 Support public & commercial zoning strategies with real-world business insights.

💡 Why Choose Xverum’s Location Data? - 230M+ Verified Locations – One of the largest & most structured location datasets available. - Global Coverage – Spanning 249+ countries, with diverse business & industry data. - Regular Updates – Continuous discovery & refresh cycles ensure data accuracy. - Comprehensive Geographic & Business Metadata – Coordinates, addresses, industry categories & more. - Bulk Dataset Delivery (NO API) – Seamless access via S3 Bucket or cloud storage. - 100% Compliant – Ethically sourced & legally compliant.

Access Xverum’s 230M+ Location Data for mapping, geographic analysis & business intelligence. Request a free sample or contact us to customize your dataset today!

The data set of the georeferenced inventory addresses Wuppertal contains the official address components (road keys, street name, house number, address addition, ETRS89-UTM32 kilometre square, city district) and the location coordinates of all house number-bearing buildings in Wuppertal. For data sets of this kind, the state of North Rhine-Westphalia has introduced the term "building references". The data set does not include postal codes, so it is not suitable for the production of anonymous mass mailings. It is created by the weekly automated merging of the building references from the official real estate cadastre information system ALKIS for the measured buildings and the building references of existing but not yet measured buildings from the municipal information system WuNDa/adressen, a subsystem within the Wuppertal navigation and data management system WuNDa. However, the existing buildings, which have not yet been measured, are determined only once a month by comparing them with the ProBAUG building permit procedure. The coordinates of the ALKIS building references correspond to the insertion position of the house number in the property map. The coordinates of the building references to the existing but not yet measured buildings deviate in the order of a few meters from the later available ALKIS coordinates. The data is provided in the formats ESRI-Shapefile, KML, GeoJSON and CSV. The city of Wuppertal regards the combined dataset as a municipal product. It is therefore under the city's preferred open data license CC BY 4.0 and not under the "Data License Germany - Zero - Version 2.0 (dl-zero-en/2.0)" prescribed by the state of North Rhine-Westphalia for the ALKIS building references.

Street noise-level data from any city. Analyze noise exposure across 180+ countries for risk modeling, real estate, AI-training and health studies. Real measurements + AI interpolation. CSV, S3, and high-res maps available.

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!

APISCRAPY, your premier provider of Map Data solutions. Map Data encompasses various information related to geographic locations, including Google Map Data, Location Data, Address Data, and Business Location Data. Our advanced Google Map Data Scraper sets us apart by extracting comprehensive and accurate data from Google Maps and other platforms.

What sets APISCRAPY's Map Data apart are its key benefits:

1. Accuracy: Our scraping technology ensures the highest level of accuracy, providing reliable data for informed decision-making. We employ advanced algorithms to filter out irrelevant or outdated information, ensuring that you receive only the most relevant and up-to-date data.

2. Accessibility: With our data readily available through APIs, integration into existing systems is seamless, saving time and resources. Our APIs are easy to use and well-documented, allowing for quick implementation into your workflows. Whether you're a developer building a custom application or a business analyst conducting market research, our APIs provide the flexibility and accessibility you need.

3. Customization: We understand that every business has unique needs and requirements. That's why we offer tailored solutions to meet specific business needs. Whether you need data for a one-time project or ongoing monitoring, we can customize our services to suit your needs. Our team of experts is always available to provide support and guidance, ensuring that you get the most out of our Map Data solutions.

Our Map Data solutions cater to various use cases:

1. B2B Marketing: Gain insights into customer demographics and behavior for targeted advertising and personalized messaging. Identify potential customers based on their geographic location, interests, and purchasing behavior.

2. Logistics Optimization: Utilize Location Data to optimize delivery routes and improve operational efficiency. Identify the most efficient routes based on factors such as traffic patterns, weather conditions, and delivery deadlines.

3. Real Estate Development: Identify prime locations for new ventures using Business Location Data for market analysis. Analyze factors such as population density, income levels, and competition to identify opportunities for growth and expansion.

4. Geospatial Analysis: Leverage Map Data for spatial analysis, urban planning, and environmental monitoring. Identify trends and patterns in geographic data to inform decision-making in areas such as land use planning, resource management, and disaster response.

5. Retail Expansion: Determine optimal locations for new stores or franchises using Location Data and Address Data. Analyze factors such as foot traffic, proximity to competitors, and demographic characteristics to identify locations with the highest potential for success.

6. Competitive Analysis: Analyze competitors' business locations and market presence for strategic planning. Identify areas of opportunity and potential threats to your business by analyzing competitors' geographic footprint, market share, and customer demographics.

Experience the power of APISCRAPY's Map Data solutions today and unlock new opportunities for your business. With our accurate and accessible data, you can make informed decisions, drive growth, and stay ahead of the competition.

[ Related tags: Map Data, Google Map Data, Google Map Data Scraper, B2B Marketing, Location Data, Map Data, Google Data, Location Data, Address Data, Business location data, map scraping data, Google map data extraction, Transport and Logistic Data, Mobile Location Data, Mobility Data, and IP Address Data, business listings APIs, map data, map datasets, map APIs, poi dataset, GPS, Location Intelligence, Retail Site Selection, Sentiment Analysis, Marketing Data Enrichment, Point of Interest (POI) Mapping]

The Official Property Register Information System (ALKIS®) is a product of the Association of Surveying Administrations of the Länder of the Federal Republic of Germany (AdV). In ALKIS, the previously separately kept data of the Automated Property Book (ALB) and the Automated Property Map (ALK point file, ALK floor plan file) were migrated into an information system. Alkis is now the official real estate registry information system. The main components of the program system for ALKIS® are the acquisition and qualification component (EQk), the data holding component (DHK) and the output and presentation component (APK). This is a simplified presentation of parcels, parcel numbers, selected buildings and buildings.

The data set of the georeferenced inventory addresses Wuppertal contains the official address components (street key, street name, house number, additional address, ETRS89-UTM32 square, city district) and the location coordinates of all buildings bearing house numbers in Wuppertal. For such data sets, the State of NRW has introduced the term “Building References”. The data record does not include postcodes, so is not suitable for the production of anonymous mass mail items. It is created by the weekly automated merging of the building references from the Official Property Register Information System ALKIS for the measured buildings and the building references of existing but not yet measured buildings from the municipal information system Wunda/Addresses, a subsystem within the Wuppertal navigation and data management system Wunda. However, the existing buildings, which have not yet been measured, are determined only once a month by means of a comparison with the ProBAUG building permit procedure. The coordinates of the ALKIS building references correspond to the insertion position of the house number in the property map. The coordinates of the building references to the existing but not yet measured buildings differ in the order of a few meters from the later available ALKIS coordinates. The data is provided in the formats ESRI-Shapefile, KML, GeoJSON and CSV. The city of Wuppertal considers the combined data set as a municipal product. It is therefore under the city’s preferred open data license CC BY 4.0 and not under the “Data License Germany – Zero – Version 2.0 (dl-zero-de/2.0)” required by the state of NRW for the ALKIS building references.

The following basic geodata are available for the municipality of Stuhr: Automated real estate map (ALK) scale 1:1,000; German basic map scale 1:5.000 (DGK5); Digital topographic map 1:25,000 and 1:100,000 (DTK25; DTK100); Aerial photographs 2007/2008