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.

Download .zipThis map was derived from the Logan County Soil Survey by combining the Natural Resources Conservation Service Limitation ratings for homesites with information on bearing strength from the unified soil classification.

Soils used in this analysis were digitized from the paper original soil survey sheets. These sheets were taped together to form an area covering each of the USGS 7.5 minute quadrangle maps in the county. The areas for each quadrangle were then digitized using run-length encoding technique sampling along horizontal lines which represented the midline of cells with a height of 250 feet. The measurement increment along these lines was one decafoot (10 feet). The quadrangle files were then merged into a county file which has subsequently been converted to Arc/Info format.

The user should bear in mind that this coverage is only an approximation of the soil survey and should not be used for site specific analysis.

Additional details of the digitizing process are available upon request.

Original coverage data was converted from the .e00 file to a more standard ESRI shapefile(s) in November 2014.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesReal Estate & Land ManagementReal Estate and Lands Management2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

Discover the booming real estate surveying and mapping market! This comprehensive analysis reveals key trends, growth drivers, and regional insights for 2025-2033, featuring major players like Trimble and Fugro. Learn about market size, CAGR, and future opportunities in this dynamic sector.

Download .zipThe analysis for limitations for large scale development was completed by considering several different factors including slope, ground water, land use, soil drainage, shrink-swell potential, sewer and water service areas, and unique natural features. These factors are listed in order of increasing severity based on the degree of ease or cost in overcoming their associated limitations.

The soils used in this analysis were digitized from the paper final soil survey field sheets. These sheets were taped together to form an area covering each of the USGS 7.5 minute quadrangle maps in the county. The areas for each quadrangle were then digitized using run-length encoding technique sampling along horizontal lines which represented the midline of cells with a height of 250 feet. The measurement increment along these lines was one decafoot (10 feet). The quadrangle files were then merged into a county file which has subsequently been converted to Arc/Info format.

The user should bear in mind that this coverage is only an approximation of the soil survey and should not be used for site specific analysis.

Additional details of the digitizing process are available upon request.

Original coverage data was converted from the .e00 file to a more standard ESRI shapefile(s) in November 2014.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesReal Estate & Land ManagementReal Estate and Lands Management2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

Download .zipThe analysis was completed by considering several different factors including slope, land use, soil drainage, shrink-swell potential, unified texture classification, flooding potential, and unique natural features to determine limitations for large scale development. These factors are listed in order of increasing severity based on the degree of ease or cost in overcoming their associated limitations.

The soils used in this analysis were digitized from the paper final soil survey field sheets. These sheets were taped together to form an area covering each of the USGS 7.5 minute quadrangle maps in the county. The areas for each quadrangle were then digitized using run-length encoding technique sampling along horizontal lines which represented the midline of cells with a height of 250 feet. The measurement increment along these lines was one decafoot (10 feet). The quadrangle files were then merged into a county file which has subsequently been converted to Arc/Info format.

The user should bear in mind that this coverage is only an approximation of the soil survey and should not be used for site specific analysis.

Additional details of the digitizing process are available upon request.

Original coverage data was converted from the .e00 file to a more standard ESRI shapefile(s) in November 2014.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesReal Estate & Land ManagementReal Estate and Lands Management2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

The OGC (Open Geospatial Consortium) standard API, which is an international standard developed for the sharing and interoperability of spatial data, enables efficient provision and use of various geographic information such as maps, features, and rasters on the web. The latest OGC API adopts a RESTful structure to enhance development convenience and expandability, and inherits existing standards such as WMS and WFS in a modern way.

Explore the burgeoning Real Estate Surveying and Mapping market, driven by urban development and real estate expansion. Discover market size, growth drivers, key trends, and regional dynamics shaping this vital industry through 2033.

Air right lots are reflect a party’s right to construct an improvement above an existing area of land that is not owned by the constructor. They are a type of development right in real estate referring to the empty space about a property. These tax lot numbers start at 7000. There are approximately 704 air rights lots. Non-contiguous Air Rights Lots numbered in 8000 series can either be District owned Multifamily rental units or Existing Development Mixed (residential and commercial).Multifamily 8000 series lots can be proposed development projects that are inclusive of the Mayor’s Office Affordable/Public Housing Initiatives. Additionally, they can either be development sites that are owned by the District and the site is leased to developer. Due to financing and legal requirements, each set of government funded units are required to have separate parcel ID’s (SSL’s). All the units are rentals, none of the units will be for sale.Existing Development Mixed Use 8000 series lots are residential owner(s) that own both residential and commercial portions. The Lot split is done to ensure each party pays the appropriate real estate taxes assessed to each specific use. There is a master covenant lease outlining property access-rights-use between residential and commercial owner and lease holders. There is also a master lease related to the commercial space where the residential owner is the lease holder.

Download .zipLarge scale development refers to heavy industry, large buildings, etc. This map was produced in cooperation with City of Delaware officials. It is a combination of data on unified class (a measure of bearing strength), slope, shrink-swell potential, depth to bedrock, and type of bedrock. Consult the publication "Land Capability Analysis in Delaware County," available from the ODNR, Division of Real Estate and Land Management for specific information concerning what constitutes a slight, moderate, or severe limitation.

This map is not meant to substitute for an onsite investigation.

Explanation of abbreviations in legend: mod-moderate, sev-severe, br-depth and type of bedrock.

Soils used in this analysis were digitized from the paper original soil survey sheets. These sheets were taped together to form an area covering each of the USGS 7.5 minute quadrangle maps in the county. The areas for each quadrangle were then digitized using run-length encoding technique sampling along horizontal lines which represented the midline of cells with a height of 250 feet. The measurement increment along these lines was one decafoot (10 feet). The quadrangle files were then merged into a county file which has subsequently been converted to Arc/Info format.

The user should bear in mind that this coverage is only an approximation of the soil survey and should not be used for site specific analysis.

Additional details of the digitizing process are available upon request.

Original coverage data was converted from the .e00 file to a more standard ESRI shapefile(s) in November 2014.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesReal Estate & Land ManagementReal Estate and Lands Management2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

Dataset SummaryPlease note: this data is live (updated nightly) to reflect the latest changes in the City's systems of record.About the Data:For a data dictionary / codebook, click here.This dataset is a polygon feature layer with the boundaries of all tax parcels owned by the City of Rochester. This includes all public parks, and municipal buildings, as well as vacant land and structures currently owned by the City. The data includes fields with features about each property including property type, date of sale, whether the property is expected to be sold, land value, dimensions, and more.To view a interactive map that features this layer, please visit:https://maps.cityofrochester.gov/portal/apps/webappviewer/index.html?id=eecba714701449c69054851c9ac57198About City Owned Properties:The City's real estate inventory is managed by the Division of Real Estate in the Department of Neighborhood and Business Development. Properties like municipal buildings and parks are expected to be in long term ownership of the City. Properties such as vacant land and vacant structures are ones the City is actively seeking to reposition for redevelopment to increase the City's tax base and economic activity. The City acquires many of these properties through the tax foreclosure auction process when no private entity bids the minimum bid. Some of these properties stay in the City's ownership for years, while others are quickly sold to development partners. For more information please visit the City's webpage for the Division of Real Estate: https://www.cityofrochester.gov/realestate/

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

Discover the booming Land Planning & Development market, projected to reach $150 billion by 2025 with a 7% CAGR. This in-depth analysis explores key drivers, trends, restraints, and leading companies shaping this dynamic industry. Learn about market segmentation, regional variations, and future growth opportunities.

Like other Assessor and Recorder data sets from First American, BlackKnight, ATTOM or HouseCanary, we provide both residential real estate and commercial restate data on homes, properties and pracels nationally.

Over 250M parcels, updated daily.

Access detailed property and tax assessment records with our extensive nationwide database. This robust dataset provides comprehensive information about residential and commercial properties, including detailed ownership, valuation, and transaction history. Core Data Elements:

Complete property identification (APNs, Tax IDs) Full property addresses with geocoding Precise latitude/longitude coordinates FIPS codes and Census tract information School district assignments

Property Characteristics:

Detailed lot dimensions and size Building square footage breakdowns Living area measurements Basement and attic specifications Garage and parking information Year built and effective year Number of bedrooms and bathrooms Room counts and configurations Building class and condition codes Construction details and materials Property amenities and features

Valuation Information:

Current AVM (Automated Valuation Model) values Confidence scores and value ranges Market valuations with dates Assessed values (land and improvements) Tax amounts and years Tax rate codes and districts Various tax exemption statuses

Transaction History:

Current and previous sale details Recording dates and document numbers Sale prices and price codes Buyer and seller information Multiple mortgage records including:

Loan amounts and terms Lender information Recording dates Interest rates Due dates Loan types and positions

Ownership Details:

Current owner information Corporate ownership indicators Owner-occupied status Mailing addresses Care of names Foreign address indicators

Legal Information:

Complete legal descriptions Subdivision details Lot and block numbers Zoning information Land use codes HOA information and fees

Property Status Indicators:

Vacancy flags Pre-foreclosure status Current listing status Price ranges Market position

Perfect For:

Real Estate Professionals

Property researchers Title companies Real estate attorneys Appraisers Market analysts

Financial Services

Mortgage lenders Insurance companies Investment firms Risk assessment teams Portfolio managers

Government & Planning

Urban planners Tax assessors Economic developers Policy researchers Municipal agencies

Data Analytics

Market researchers Data scientists Economic analysts GIS specialists Demographics experts

Data Delivery Features:

Multiple format options Regular updates Bulk download capability Custom field selection Geographic filtering API access available Standardized formatting Quality assured data

Quality Assurance:

Verified against public records Regular updates Standardized formatting Address verification Geocoding validation Duplicate removal Data normalization Quality control processes

This comprehensive property database provides unprecedented access to detailed property information, perfect for industry professionals requiring in-depth property data for analysis, research, or business development. Our data undergoes rigorous quality control processes to ensure accuracy and completeness, making it an invaluable resource for real estate professionals, financial institutions, and government agencies. Updated continuously from authoritative sources, this dataset offers the most current and accurate property information available in the market. Custom data extracts and specific geographic coverage options are available to meet your exact needs.

Weekly/Quarterly/Annual and One-time options are available for sale.

See our sample

The Geographic Information Systems (GIS) platform market is poised for substantial growth, projected to reach an estimated market size of $XXX million in 2025, with a Compound Annual Growth Rate (CAGR) of XX% expected throughout the forecast period of 2025-2033. This robust expansion is primarily driven by the increasing demand for sophisticated data visualization, spatial analysis, and location-based services across a multitude of sectors. The government and utilities sector is a significant contributor, leveraging GIS for infrastructure management, urban planning, resource allocation, and emergency response. Commercial applications are also rapidly adopting GIS for customer analytics, supply chain optimization, real estate development, and targeted marketing. The proliferation of web-enabled GIS solutions, including Web Map Services, is democratizing access to geospatial data and tools, fostering innovation and wider adoption beyond traditional GIS professionals. Desktop GIS continues to hold its ground for complex analytical tasks, but the trend towards cloud-based and mobile GIS solutions is accelerating, offering greater flexibility and scalability. Key trends shaping the GIS platform market include the integration of Artificial Intelligence (AI) and Machine Learning (ML) for advanced spatial analytics and predictive modeling, the growing importance of real-time data processing and streaming, and the rise of open-source GIS solutions challenging established players. The increasing availability of high-resolution satellite imagery and IoT sensor data further fuels the need for powerful GIS platforms. However, certain restraints might temper this growth, such as the initial cost of implementation for some advanced solutions, a potential shortage of skilled GIS professionals, and data privacy concerns associated with extensive location data collection. The market is characterized by intense competition among established global players and emerging innovators, all vying to capture market share by offering comprehensive, user-friendly, and technologically advanced GIS solutions. This comprehensive report delves into the dynamic Geographic Information Systems (GIS) Platform market, providing in-depth analysis and forecasts from 2019 to 2033, with a base year of 2025. The study meticulously examines market concentration, key trends, regional dominance, product insights, and the driving forces and challenges shaping this vital industry. We project the market to reach values in the tens of millions and hundreds of millions of dollars across various segments.

The Urban Planning Software market is booming, projected to reach $8.87 billion in 2025 and grow at a CAGR of 7.81% through 2033. Discover key trends, leading companies, and regional insights in this comprehensive market analysis. Learn how AI, GIS, and cloud solutions are transforming urban development.

Explore the booming urban planning apps market, valued at $76.9M by 2025 and growing at 7.3% CAGR. Discover key drivers, emerging trends, market segmentation, and regional insights for smart city development.

The Office of the Deputy Mayor for Planning and Economic Development (DMPED) is charged with executing the Mayor's economic development strategy. DMPED manages a portfolio of real estate projects located across the District of Columbia. More information is available on the Project Pipeline Database (PPD) Public Access Dashboard.

DisclaimerBefore using this layer, please review the 2018 Rochester Citywide Housing Market Study for the full background and context that is required for interpreting and portraying this data. Please click here to access the study. Please also note that the housing market typologies were based on analysis of property data from 2008 to 2018, and is a snapshot of market conditions within that time frame. For an accurate depiction of current housing market typologies, this analysis would need to be redone with the latest available data.About the DataThis is a polygon feature layer containing the boundaries of all census blockgroups in the city of Rochester. Beyond the unique identifier fields including GEOID, the only other field is the housing market typology for that blockgroup.Information from the 2018 Housing Market Study- Housing Market TypologiesThe City of Rochester commissioned a Citywide Housing Market Study in 2018 as a technical study to inform development of the City's new Comprehensive Plan, Rochester 2034, and retained czb, LLC – a firm with national expertise based in Alexandria, VA – to perform the analysis.Any understanding of Rochester’s housing market – and any attempt to develop strategies to influence the market in ways likely to achieve community goals – must begin with recognition that market conditions in the city are highly uneven. On some blocks, competition for real estate is strong and expressed by pricing and investment levels that are above city averages. On other blocks, private demand is much lower and expressed by above average levels of disinvestment and physical distress. Still other blocks are in the middle – both in terms of condition of housing and prevailing prices. These block-by-block differences are obvious to most residents and shape their options, preferences, and actions as property owners and renters. Importantly, these differences shape the opportunities and challenges that exist in each neighborhood, the types of policy and investment tools to utilize in response to specific needs, and the level and range of available resources, both public and private, to meet those needs. The City of Rochester has long recognized that a one-size-fits-all approach to housing and neighborhood strategy is inadequate in such a diverse market environment and that is no less true today. To concisely describe distinct market conditions and trends across the city in this study, a Housing Market Typology was developed using a wide range of indicators to gauge market health and investment behaviors. This section of the Citywide Housing Market Study introduces the typology and its components. In later sections, the typology is used as a tool for describing and understanding demographic and economic patterns within the city, the implications of existing market patterns on strategy development, and how existing or potential policy and investment tools relate to market conditions.Overview of Housing Market Typology PurposeThe Housing Market Typology in this study is a tool for understanding recent market conditions and variations within Rochester and informing housing and neighborhood strategy development. As with any typology, it is meant to simplify complex information into a limited number of meaningful categories to guide action. Local context and knowledge remain critical to understanding market conditions and should always be used alongside the typology to maximize its usefulness.Geographic Unit of Analysis The Block Group – a geographic unit determined by the U.S. Census Bureau – is the unit of analysis for this typology, which utilizes parcel-level data. There are over 200 Block Groups in Rochester, most of which cover a small cluster of city blocks and are home to between 600 and 3,000 residents. For this tool, the Block Group provides geographies large enough to have sufficient data to analyze and small enough to reveal market variations within small areas.Four Components for CalculationAnalysis of multiple datasets led to the identification of four typology components that were most helpful in drawing out market variations within the city:• Terms of Sale• Market Strength• Bank Foreclosures• Property DistressThose components are described one-by-one on in the full study document (LINK), with detailed methodological descriptions provided in the Appendix.A Spectrum of Demand The four components were folded together to create the Housing Market Typology. The seven categories of the typology describe a spectrum of housing demand – with lower scores indicating higher levels of demand, and higher scores indicating weaker levels of demand. Typology 1 are areas with the highest demand and strongest market, while typology 3 are the weakest markets. For more information please visit: https://www.cityofrochester.gov/HousingMarketStudy2018/Dictionary: STATEFP10: The two-digit Federal Information Processing Standards (FIPS) code assigned to each US state in the 2010 census. New York State is 36. COUNTYFP10: The three-digit Federal Information Processing Standards (FIPS) code assigned to each US county in the 2010 census. Monroe County is 055. TRACTCE10: The six-digit number assigned to each census tract in a US county in the 2010 census. BLKGRPCE10: The single-digit number assigned to each block group within a census tract. The number does not indicate ranking or quality, simply the label used to organize the data. GEOID10: A unique geographic identifier based on 2010 Census geography, typically as a concatenation of State FIPS code, County FIPS code, Census tract code, and Block group number. NAMELSAD10: Stands for Name, Legal/Statistical Area Description 2010. A human-readable field for BLKGRPCE10 (Block Groups). MTFCC10: Stands for MAF/TIGER Feature Class Code 2010. For this dataset, G5030 represents the Census Block Group. BLKGRP: The GEOID that identifies a specific block group in each census tract. TYPOLOGYFi: The point system for Block Groups. Lower scores indicate higher levels of demand – including housing values and value appreciation that are above the Rochester average and vulnerabilities to distress that are below average. Higher scores indicate lower levels of demand – including housing values and value appreciation that are below the Rochester average and above presence of distressed or vulnerable properties. Points range from 1.0 to 3.0. For more information on how the points are calculated, view page 16 on the Rochester Citywide Housing Study 2018. Shape_Leng: The built-in geometry field that holds the length of the shape. Shape_Area: The built-in geometry field that holds the area of the shape. Shape_Length: The built-in geometry field that holds the length of the shape. Source: This data comes from the City of Rochester Department of Neighborhood and Business Development.