This dataset has been published by the Office of the Real Estate Assessor of the City of Virginia Beach and data.virginiabeach.gov. The mission of data.virginiabeach.gov is to provide timely and accurate City information to increase government transparency and access to useful and well organized data by the general public, non-governmental organizations, and City of Virginia Beach employees.
Field descriptions for the James City County Parcel layer and the Data table.
Explore Doorda's UK Geospatial Real Estate Data, offering insights into 34M+ Addresses aggregated from 10 data sources. Unlock Customer Insights and Enhanced Location Planning Capabilities.
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Geospatial data on real estate prices and housing in the USA is a strategic asset for informed decision-making in the property market. This data - at census block level - reveals regional price and construction trends, allowing real estate professionals and investors to optimize their strategies.
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This repository contains data and codes that support the findings of the study.- PPD-EPC open dataset with the enriched spatial analyses scores and UPRN.- Batch Geocoding Notebook of PPD-EPC dataset with GeoPy - Here API- PyQGIS codes for proximity, terrain, and visibility spatial analyses.- Jupyter Notebook of Machine Learning algorithms for mass property valuation.
Xverum’s Urban Planning Data is a comprehensive dataset of 230M+ verified locations, offering insights into commercial real estate, property trends, and urban development. Covering 5000 categories, our dataset supports real estate investors, urban planners, and policymakers in making data-driven decisions for infrastructure development, property market analysis, and zoning regulations.
With regular updates and continuous POI discovery, Xverum ensures your real estate and urban planning models have the latest property and commercial development data. Delivered in bulk via S3 Bucket or cloud storage, our dataset is ideal for GIS applications, market research, and smart city development.
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James City County Data - Updated nightly IGNORE dates on this site.Combination of parcel information from the GIS/Mapping and the Real Estate departments.This table includes multiple improvements per parcel.Also download the GIS and Real Estate Data Field Descriptions.pdf file for a list of field descriptions.This data is updated every night
James City County Data - Updated nightly IGNORE dates on this site.Combination of parcel information from the GIS/Mapping and the Real Estate departments.This table includes multiple improvements per parcel.Also download the GIS and Real Estate Data Field Descriptions.pdf file for a list of field descriptions.This data is updated every night
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The geospatial market is estimated to reach a value of USD 105.06 billion by 2033, growing at a CAGR of 9.1% during the forecast period of 2025-2033. This growth is attributed to the rising demand for geospatial data and services across various end-user industries, such as real estate and construction, automotive, utility and communication, government, defense and intelligence, and natural resources. Key drivers of the market include the increasing adoption of location-based services, the growing use of geospatial data for decision-making, and the rapid advancements in geospatial technologies. The market is segmented by type (surface analytics, network analytics, geovisualization, and others), technology (remote sensing, GPS, GIS, and others), and end-user (real estate and construction, automotive, utility and communication, government, defense and intelligence, natural resources, and others). North America is the largest regional market, followed by Europe, Asia Pacific, and the Middle East and Africa. Key companies in the geospatial market include Hexagon AB, Trimble Inc., Maxar Technologies, MDA Corporation, Fugro, Cyient, Esri, Bentley Systems, Incorporated, NV5 Global Inc., General Electric Company, Accenture, and RMSI. Recent developments include: In February 2023, U.S. Army has extended its contract with Maxar Technologies to provide 3D geospatial data used to create immersive digital environments. Maxar was awarded Phase 3b of the U.S. Army’s One World Terrain (OWT) contract originally awarded in 2019 to Vricon, a company Maxar acquired in 2020. Vricon uses data from Maxar’s imaging satellites to make 3D mapping products. In September 2023, Trimble and Kyivstar Partner to Provide GNSS Correction Services for Agriculture, Construction and Geospatial Applications in Ukraine. It will install a new Continuously Operating Reference Station (CORS) network to provide Global Navigation Satellite System (GNSS) correction services across the country. Available to users as an annual subscription service, the new network will be built using Trimble's hardware and software positioning technology, which provides customers with easy and reliable high-accuracy real time or post-processed GNSS corrections data for agriculture, construction, geospatial, Internet of Things (IoT) and other commercial operations. . Key drivers for this market are: Growing demand for accurate and actionable geospatial data
Advancements in cloud computing and AI technologies
Increasing adoption of location-based services and IoT devices
Need for sustainable resource management and environmental monitoring
Government initiatives and investments in geospatial infrastructure. Potential restraints include: Data privacy and security concerns
Lack of skilled workforce and technical expertise
High cost of implementing and maintaining geospatial solutions
Interoperability issues between different geospatial platforms
Limited awareness of the benefits of geospatial technologies. Notable trends are: The integration of AI and IOT fuels Integration of blockchain technology for data security and transparency
Development of open-source geospatial platforms and applications
Use of AI and machine learning for predictive analytics and automation
Focus on interconnected and interoperable geospatial ecosystems
Growing adoption of geospatial solutions in emerging marketsmarket expansion is expected to drive market growth..
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General Services Administration Owned PropertiesThis National Geospatial Data Asset (NGDA) dataset, shared as a General Services Administration (GSA) feature layer, displays federal government owned properties in the United States, Puerto Rico, Northern Mariana Islands, U.S. Virgin Islands, Guam and American Samoa. Per GSA, it is "the nation’s largest public real estate organization, provides workspace for over one million federal workers. These employees, along with government property, are housed in space owned by the federal government and in leased properties including buildings, land, antenna sites, etc. across the country."Federally owned buildings in downtown DCData currency: Current federal service (FC_IOLP_BLDG))NGDAID: 133 (Inventory of Owned and Leased Properties (IOLP))OGC API Features Link: Not AvailableFor more information: Real EstateFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets
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,
The U.S. Department of Housing and Urban Development's Real Estate Owned (REO) properties are a result of the Federal Housing Administration (FHA) paying a claim to a lending institution on a foreclosed property which was financed with an FHA Insured Mortgage and the lender transferring ownership of the property to HUD. Typically, title to the property is not transferred (or the claim paid) until the previous owner is evicted from the property. Normally, after the home is transferred to HUD, the property will go up for auction on the HUD Home store website. This layer contains single-family residential properties that are up for sale.
Federal Housing Administration Single-Family – Properties for SaleThis National Geospatial Data Asset (NGDA) dataset, shared as a Federal Housing Administration feature layer, displays single-family real estate owned (REO) properties that are up for sale in the United States. Per Housing and Urban Development (HUD), "The U.S. Department of Housing and Urban Development's Real Estate Owned (REO) properties are a result of the Federal Housing Administration (FHA) paying a claim to a lending institution on a foreclosed property which was financed with an FHA Insured Mortgage and the lender transferring ownership of the property to HUD. Typically, title to the property is not transferred (or the claim paid) until the previous owner is evicted from the property. Normally, after the home is transferred to HUD, the property will go up for auction on the HUD Home store website."FHA Single Family Property, Case Number:137-427167Data currency: current federal service (FHA Single Family REO Properties For Sale)NGDAID: 128 (FHA Single Family REO Properties for Sale - National Geospatial Data Asset (NGDA))For more information: The Federal Housing Administration (FHA); FHA Single Family HousingFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets
This is a comprehensive collection of tax and assessment data extracted at a specific time. The data is in CSV format. A data dictionary (pdf) and the current tax rate book (pdf) are also included.
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Geospatial data on real estate price development in the Netherlands is a strategic asset for informed decision-making in the property market. This data, at 6-digit postal code level, reveals regional price trends, market dynamics, and development opportunities, allowing real estate professionals and investors to optimize their strategies. Whether assessing risk, valuing properties, or identifying growth areas, geospatial insights play a crucial role.
Access Arkansas's 61 data folders with 315 services and 1,625 layers of parcel boundaries, property tax records, and GIS mapping data.
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This dataset was generated for analyzing the economic impacts of subway networks on housing prices in metropolitan areas. The provision of transit networks and accompanying improvement in accessibility induce various impacts and we focused on the economic impacts realized through housing prices. As a proxy of housing price, we consider the price of condominiums, the dominant housing type in South Korea. Although our focus is transit accessibility and housing prices, the presented dataset is applicable to other studies. In particular, it provides a wide range of variables closely related to housing price, including housing properties, local amenities, local demographic characteristics, and control variables for the seasonality. Many of these variables were scientifically generated by our research team. Various distance variables were constructed in a geographic information system environment based on public data and they are useful not only for exploring environmental impacts on housing prices, but also for other statistical analyses in regard to real estate and social science research. The four metropolitan areas covered by the data—Busan, Daegu, Daejeon, and Gwangju—are independent of the transit systems of Greater Seoul, providing accurate information on the metropolitan structure separate from the capital city.
Access Georgia's 129 data folders with 1,733 services and 3,993 layers of parcel boundaries, property tax records, and GIS mapping data.
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The Geographic Information System (GIS) Analytics market is experiencing robust growth, projected to reach $15.10 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 12.41% from 2025 to 2033. This expansion is fueled by several key drivers. Increasing adoption of cloud-based GIS solutions enhances accessibility and scalability for diverse industries. The growing need for data-driven decision-making across sectors like retail, real estate, government, and telecommunications is a significant catalyst. Furthermore, advancements in artificial intelligence (AI) and machine learning (ML) integrated with GIS analytics are revolutionizing spatial data analysis, enabling more sophisticated predictive modeling and insightful interpretations. The market's segmentation reflects this broad adoption, with retail and real estate, government and utilities, and telecommunications representing key end-user segments, each leveraging GIS analytics for distinct applications such as location optimization, infrastructure management, and network planning. Competitive pressures are shaping the market landscape, with established players like Esri, Trimble, and Autodesk innovating alongside emerging tech companies focusing on AI and specialized solutions. The North American market currently holds a significant share, driven by early adoption and technological advancements. However, Asia-Pacific is expected to witness substantial growth due to rapid urbanization and increasing investment in infrastructure projects. Market restraints primarily involve the high cost of implementation and maintenance of advanced GIS analytics solutions and the need for skilled professionals to effectively utilize these technologies. However, the overall outlook remains extremely positive, driven by continuous technological innovation and escalating demand across multiple sectors. The future trajectory of the GIS analytics market hinges on several factors. Continued investment in research and development, especially in AI and ML integration, will be crucial for unlocking new possibilities. Furthermore, the simplification of GIS analytics software and the development of user-friendly interfaces will broaden accessibility beyond specialized technical experts. Growing data volumes from various sources (IoT, remote sensing) present both opportunities and challenges; efficient data management and analytics techniques will be paramount. The market's success also depends on addressing cybersecurity concerns related to sensitive geospatial data. Strong partnerships between technology providers and end-users will be vital in optimizing solution implementation and maximizing return on investment. Government initiatives promoting the use of GIS technology for smart city development and infrastructure planning will also play a significant role in market expansion. Overall, the GIS analytics market is poised for sustained growth, driven by technological advancements, increasing data availability, and heightened demand for location-based intelligence across a wide range of industries.
The FHA insured Multifamily Housing portfolio consist primarily of rental housing properties with five or more dwelling units such as apartments or town houses, but can also be nursing homes, hospitals, elderly housing, mobile home parks, retirement service centers, and occasionally vacant land. Note that this layer does not include insured hospitals. Also, note that there is overlap between this layer and the Multifamily Properties ? Assisted layer in the Assisted Housing file geodatabase. Roughly 2/3 of the FHA insured Multifamily portfolio also participate in a rental subsidy program. To learn more about the Multifamily housing programs, please visit the following website: https://www.hud.gov/program_offices/housing/mfh/progdesc Generally speaking, the location of the property is derived from the primary address on file. Data included are for projects placed in service through December 2012 and include all attributes from the Active Property table in Real Estate Management System (REMS).
This dataset has been published by the Office of the Real Estate Assessor of the City of Virginia Beach and data.virginiabeach.gov. The mission of data.virginiabeach.gov is to provide timely and accurate City information to increase government transparency and access to useful and well organized data by the general public, non-governmental organizations, and City of Virginia Beach employees.