Geospatial Data Pack for Visualization 🗺️

Learn Geographic Mapping with Altair, Vega-Lite and Vega using Curated Datasets

Complete geographic and geophysical data collection for mapping and visualization. This consolidation includes 18 complementary datasets used by 31+ Vega, Vega-Lite, and Altair examples 📊. Perfect for learning geographic visualization techniques including projections, choropleths, point maps, vector fields, and interactive displays.

Source data lives on GitHub and can also be accessed via CDN. The vega-datasets project serves as a common repository for example datasets used across these visualization libraries and related projects.

Why Use This Dataset? 🤔

• Comprehensive Geospatial Types: Explore a variety of core geospatial data models:
  • Vector Data: Includes points (like airports.csv), lines (like londonTubeLines.json), and polygons (like us-10m.json).
  • Raster-like Data: Work with gridded datasets (like windvectors.csv, annual-precip.json).
• Diverse Formats: Gain experience with standard and efficient geospatial formats like GeoJSON (see Table 1, 2, 4), compressed TopoJSON (see Table 1), and plain CSV/TSV (see Table 2, 3, 4) for point data and attribute tables ready for joining.
• Multi-Scale Coverage: Practice visualization across different geographic scales, from global and national (Table 1, 4) down to the city level (Table 1).
• Rich Thematic Mapping: Includes multiple datasets (Table 3) specifically designed for joining attributes to geographic boundaries (like states or counties from Table 1) to create insightful choropleth maps.
• Ready-to-Use & Example-Driven: Cleaned datasets tightly integrated with 31+ official examples (see Appendix) from Altair, Vega-Lite, and Vega, allowing you to immediately practice techniques like projections, point maps, network maps, and interactive displays.
• Python Friendly: Works seamlessly with essential Python libraries like Altair (which can directly read TopoJSON/GeoJSON), Pandas, and GeoPandas, fitting perfectly into the Kaggle notebook environment.

Table of Contents

• Why Use This Dataset?
• Dataset Inventory
• Usage Guide
• Appendix: Geospatial Examples by Technique
• Licenses
• Sources
• Learning Resources

Dataset Inventory 🗂️

This pack includes 18 datasets covering base maps, reference points, statistical data for choropleths, and geophysical data.

1. BASE MAP BOUNDARIES (Topological Data)

2. GEOGRAPHIC REFERENCE POINTS (Point Data) 📍

The dataset contains example gwfvisdb files required to run the examples displayed on the GWF-VIS visualization gallery (https://gwf-vis.usask.ca/#gallery). The code associated with each visualization example contains a 'data_source' variable. This variable can be examined to see where the data is currently hosted. Users may also upload the data file on other static file servers and update the 'data_source' to replicate the visualizations.

The geospatial analytics market size is predicted to rise from $93.49 billion in 2024 to $362.45 billion by 2035, growing at a CAGR of 13.1% from 2024 to 2035

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Geospatial Analytics Market Size 2025-2029

The geospatial analytics market size is forecast to increase by USD 178.6 billion, at a CAGR of 21.4% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing adoption of geospatial analytics in sectors such as healthcare and insurance. This trend is fueled by the ability of geospatial analytics to provide valuable insights from location-based data, leading to improved operational efficiency and decision-making. Additionally, emerging methods in data collection and generation, including the use of drones and satellite imagery, are expanding the scope and potential of geospatial analytics. However, the market faces challenges, including data privacy and security concerns. With the vast amounts of sensitive location data being collected and analyzed, ensuring its protection is crucial for companies to maintain trust with their customers and avoid regulatory penalties. Navigating these challenges and capitalizing on the opportunities presented by the growing adoption of geospatial analytics requires a strategic approach from industry players. Companies must prioritize data security, invest in advanced analytics technologies, and collaborate with stakeholders to build trust and transparency. By addressing these challenges and leveraging the power of geospatial analytics, businesses can gain a competitive edge and unlock new opportunities in various industries.

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

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, driven by the increasing demand for location-specific insights across various sectors. Urban planning relies on geospatial optimization and data enrichment to enhance city designs and improve infrastructure. Cloud-based geospatial solutions facilitate real-time data access, enabling location intelligence for public safety and resource management. Spatial data standards ensure interoperability among different systems, while geospatial software and data visualization tools provide valuable insights from satellite imagery and aerial photography. Geospatial services offer data integration, spatial data accuracy, and advanced analytics capabilities, including 3D visualization, route optimization, and data cleansing. Precision agriculture and environmental monitoring leverage geospatial data to optimize resource usage and monitor ecosystem health. Infrastructure management and real estate industries rely on geospatial data for asset tracking and market analysis. Spatial statistics and disaster management applications help mitigate risks and respond effectively to crises. Geospatial data management and quality remain critical as the volume and complexity of data grow. Geospatial modeling and interoperability enable seamless data sharing and collaboration. Sensor networks and geospatial data acquisition technologies expand the reach of geospatial analytics, while AI-powered geospatial analytics offer new opportunities for predictive analysis and automation. The ongoing development of geospatial technologies and applications underscores the market's continuous dynamism, providing valuable insights and solutions for businesses and organizations worldwide.

How is this Geospatial Analytics Industry segmented?

The geospatial analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. TechnologyGPSGISRemote sensingOthersEnd-userDefence and securityGovernmentEnvironmental monitoringMining and manufacturingOthersApplicationSurveyingMedicine and public safetyMilitary intelligenceDisaster risk reduction and managementOthersTypeSurface and field analyticsGeovisualizationNetwork and location analyticsOthersGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth AmericaBrazilRest of World (ROW)

By Technology Insights

The gps segment is estimated to witness significant growth during the forecast period.The market encompasses various applications and technologies, including geospatial optimization, data enrichment, location-based services (LBS), spatial data standards, public safety, geospatial software, resource management, location intelligence, geospatial data visualization, geospatial services, data integration, 3D visualization, satellite imagery, remote sensing, GIS platforms, spatial data infrastructure, aerial photography, route optimization, data cleansing, precision agriculture, spatial interpolation, geospatial databases, transportation planning, spatial data accuracy, spatial analysis, map projections, interactive maps, marketing analytics, data storytelling, geospati

Refined DataCo Smart Supply Chain Geospatial Dataset

Optimized for Geospatial and Big Data Analysis

This dataset is a refined and enhanced version of the original DataCo SMART SUPPLY CHAIN FOR BIG DATA ANALYSIS dataset, specifically designed for advanced geospatial and big data analysis. It incorporates geocoded information, language translations, and cleaned data to enable applications in logistics optimization, supply chain visualization, and performance analytics.

Key Features

1. Geocoded Source and Destination Data

• Accurate latitude and longitude coordinates for both source and destination locations.
• Facilitates geospatial mapping, route analysis, and distance calculations.

2. Supplementary GeoJSON Files

• src_points.geojson: Source point geometries.
• dest_points.geojson: Destination point geometries.
• routes.geojson: Line geometries representing source-destination routes.
• These files are compatible with GIS software and geospatial libraries such as GeoPandas, Folium, and QGIS.

3. Language Translation

• Key location fields (countries, states, and cities) are translated into English for consistency and global accessibility.

4. Cleaned and Consolidated Data

• Addressed missing values, removed duplicates, and corrected erroneous entries.
• Ready-to-use dataset for analysis without additional preprocessing.

5. Routes and Points Geometry

• Enables the creation of spatial visualizations, hotspot identification, and route efficiency analyses.

Applications

1. Logistics Optimization

• Analyze transportation routes and delivery performance to improve efficiency and reduce costs.

2. Supply Chain Visualization

• Create detailed maps to visualize the global flow of goods.

3. Geospatial Modeling

• Perform proximity analysis, clustering, and geospatial regression to uncover patterns in supply chain operations.

4. Business Intelligence

• Use the dataset for KPI tracking, decision-making, and operational insights.

Dataset Content

Files Included

1. DataCoSupplyChainDatasetRefined.csv

   • The main dataset containing cleaned fields, geospatial coordinates, and English translations.

2. src_points.geojson

   • GeoJSON file containing the source points for easy visualization and analysis.

3. dest_points.geojson

   • GeoJSON file containing the destination points.

4. routes.geojson

   • GeoJSON file with LineStrings representing routes between source and destination points.

Attribution

This dataset is based on the original dataset published by Fabian Constante, Fernando Silva, and António Pereira:
Constante, Fabian; Silva, Fernando; Pereira, António (2019), “DataCo SMART SUPPLY CHAIN FOR BIG DATA ANALYSIS”, Mendeley Data, V5, doi: 10.17632/8gx2fvg2k6.5.

Refinements include geospatial processing, translation, and additional cleaning by the uploader to enhance usability and analytical potential.

Tips for Using the Dataset

• For geospatial analysis, leverage tools like GeoPandas, QGIS, or Folium to visualize routes and points.
• Use the GeoJSON files for interactive mapping and spatial queries.
• Combine this dataset with external datasets (e.g., road networks) for enriched analytics.

This dataset is designed to empower data scientists, researchers, and business professionals to explore the intersection of geospatial intelligence and supply chain optimization.

This web app launches the MultiSpec Online tool on MyGeoHub (https://mygeohub.org) for geospatial data exploration, analysis and visualization.

The Goddard Earth Sciences Data and Information Services Center (GES-DISC) at NASA is responsible for safeguarding and distributing invaluable Earth science data. Recognizing the critical role of satellite data visualization in immersive environments, we have embarked on a venture that explores the utilization of existing tools and technologies such as virtual reality (VR), augmented reality (AR), and extended reality (XR).

The intention of this project is not merely to experiment, but to potentially redefine how we interact with our large data inventory. Our objective is to deepen our comprehension of data and create engaging, interactive experiences.

Geospatial Solutions Market size was valued at USD 282.75 Billion in 2024 and is projected to reach USD 650.14 Billion by 2032, growing at a CAGR of 12.10% during the forecast period 2026-2032.Geospatial Solutions Market: Definition/ OverviewGeospatial solutions are applications and technologies that use spatial data to address geography, location, and Earth's surface problems. They use tools like GIS, remote sensing, GPS, satellite imagery analysis, and spatial modelling. These solutions enable informed decision-making, resource allocation optimization, asset management, environmental monitoring, infrastructure planning, and addressing challenges in sectors like urban planning, agriculture, transportation, disaster management, and natural resource management. They empower users to harness spatial information for better understanding and decision-making in various contexts.Geospatial solutions are technologies and methodologies used to analyze and visualize spatial data, ranging from urban planning to agriculture. They use GIS, remote sensing, and GNSS to gather, process, and interpret data. These solutions help users make informed decisions, solve complex problems, optimize resource allocation, and enhance situational awareness. They are crucial in addressing challenges and unlocking opportunities in today's interconnected world, such as mapping land use patterns, monitoring ecosystem changes, and real-time asset tracking.

Overview

Empower your location data visualizations with our edge-matched polygons, even in difficult geographies.

Our self-hosted geospatial data cover administrative and postal divisions with up to 5 precision levels. All levels follow a seamless hierarchical structure with no gaps or overlaps.

The geospatial data shapes are offered in high-precision and visualization resolution and are easily customized on-premise.

Use cases for the Global Administrative Boundaries Database (Geospatial data, Map data)

• In-depth spatial analysis

• Clustering

• Geofencing

• Reverse Geocoding

• Reporting and Business Intelligence (BI)

Product Features

• Coherence and precision at every level

• Edge-matched polygons

• High-precision shapes for spatial analysis

• Fast-loading polygons for reporting and BI

• Multi-language support

For additional insights, you can combine the map data with:

• Population data: Historical and future trends

• UNLOCODE and IATA codes

• Time zones and Daylight Saving Time (DST)

Data export methodology

Our location data packages are offered in variable formats, including - .shp - .gpkg - .kml - .shp - .gpkg - .kml - .geojson

All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why companies choose our map data

• Precision at every level

• Coverage of difficult geographies

• No gaps, nor overlaps

Note: Custom geospatial data packages are available. Please submit a request via the above contact button for more details.

Geospatial Analytics Market Outlook

In 2023, the global geospatial analytics market size was valued at approximately USD 55 billion and is projected to reach around USD 165 billion by 2032, growing at a CAGR of 12.5% during the forecast period. The market is driven by technological advancements and the increasing need for geospatial data across various industries.

One of the key growth factors of the geospatial analytics market is the rapid advancement in geospatial technologies such as Geographic Information Systems (GIS), remote sensing, and global positioning systems (GPS). These technologies have significantly enhanced the accuracy and efficiency of data collection, analysis, and interpretation. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) algorithms with geospatial analytics has further augmented its capabilities, making it an indispensable tool for decision-making across diverse sectors.

Another significant driver of the geospatial analytics market is the growing adoption of location-based services and real-time data analysis. With the proliferation of smartphones and IoT devices, there is an increasing demand for applications that provide real-time location data. This has led to a surge in the use of geospatial analytics in urban planning, transportation and logistics, and disaster management. Companies and governments are leveraging geospatial data to optimize routes, manage resources efficiently, and respond swiftly to emergencies.

Furthermore, the rising awareness about climate change and environmental sustainability has propelled the use of geospatial analytics in climate change adaptation and environmental monitoring. Governments and organizations are increasingly relying on geospatial data to understand environmental changes, assess risks, and devise strategies for climate resilience. This trend is particularly significant in regions prone to natural disasters, where timely and accurate geospatial data can save lives and minimize damages.

From a regional perspective, North America holds a significant share of the geospatial analytics market, driven by the presence of major technology companies and extensive government initiatives focused on smart city development and environmental conservation. Europe follows closely, with substantial investments in geospatial technologies for urban planning and infrastructure development. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by rapid urbanization, industrialization, and government initiatives to enhance geospatial infrastructure.

Component Analysis

The geospatial analytics market is segmented into three main components: software, hardware, and services. Each of these components plays a pivotal role in the functioning and advancement of geospatial analytics. Starting with software, which encompasses a wide array of applications such as Geographic Information Systems (GIS), remote sensing software, and enterprise geospatial solutions. GIS software, in particular, is integral to the collection, storage, analysis, and visualization of geospatial data, enabling organizations to make informed decisions based on spatial patterns and relationships.

Hardware components in the geospatial analytics market include devices and equipment used for data collection and processing, such as GPS devices, drones, LiDAR sensors, and remote sensing satellites. These hardware components are essential for acquiring high-resolution geospatial data from various sources, providing a comprehensive view of geographical areas. The evolution of drone technology and advancements in satellite imaging have significantly enhanced the capability to capture accurate and detailed geospatial information, driving the demand for advanced hardware solutions.

Services in the geospatial analytics market encompass a range of offerings, including consulting, integration, maintenance, and support services. These services are crucial for the successful implementation and operation of geospatial analytics solutions. Consulting services help organizations identify the most suitable geospatial technologies and strategies to meet their specific needs. Integration services ensure seamless deployment of geospatial solutions within existing IT infrastructures, while maintenance and support services provide ongoing technical assistance and updates to keep the systems running smoothly.

The interplay between software, hardware, and services is critical for the effective utilization

The NSF-funded DIBBS project, Geospatial Data Analysis Building Blocks, focuses on geospatial data management, analysis, modeling and visualization. This flyer describes the highlights of the project as of December 2015, and provides the project URL and other relevant information.

According to Cognitive Market Research, the global Geospatial Solutions market size is USD 508421.2million in 2024 and will expand at a compound annual growth rate (CAGR) of 16.50% from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD 203368.48 million in 2024 and will grow at a compound annual growth rate (CAGR) of 14.7% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 152526.36 million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD 116936.88 million in 2024 and will grow at a compound annual growth rate (CAGR) of 18.5% from 2024 to 2031.
Latin America market of more than 5% of the global revenue with a market size of USD 25421.06 million in 2024 and will grow at a compound annual growth rate (CAGR) of 15.9% from 2024 to 2031.
Middle East and Africa held the major market of around 2% of the global revenue with a market size of USD 10168.42 million in 2024 and will grow at a compound annual growth rate (CAGR) of 16.2% from 2024 to 2031.
The hospitals held the highest Geospatial Solutions market revenue share in 2024.

Key Drivers for Geospatial Solutions Market

Growing Demand for Location-based Data and Insights to Increase the Demand Globally: Businesses and organizations prioritize making well-informed decisions, driving demand for location-based data and insights. Having accurate and comprehensive information about people, places, and things is becoming increasingly important. Geospatial solutions play a crucial role in gathering, evaluating, and presenting this data, which drives market growth. These technologies help with resource allocation, market targeting, and strategy planning by providing advanced tools for interpreting spatial data. Businesses use geospatial data to improve customer experiences, optimize operations, and gain competitive advantages due to the development of GPS, remote sensing, and GIS. Because of this, the geospatial industry is expanding rapidly and satisfying the changing demands of various industries looking for useful location-based insights.

Advancements in Technology to Propel Market Growth: The geospatial industry is expanding significantly due to technological advancements, including aerial images, remote sensing, GNSS (Global Navigation Satellite Systems), and LiDAR (Light Detection and Ranging). These developments provide ever-more accurate, affordable, and easily accessible ways to collect geospatial data. While GNSS offers precise global location data, remote sensing technologies allow data collection from inaccessible or remote areas. LiDAR and aerial images improve data resolution and detail, allowing for more complex analysis and visualization. The geospatial market is growing due to the ongoing development of these technologies, which enables businesses and organizations in various industries to make wise decisions, maximize operations, and seize new possibilities.

Key Restraints for Geospatial Solutions Market

Data Privacy and Security Concerns to Limit the Sales: The widespread use of geographical data gives rise to serious privacy and security problems. The increasing accessibility and utilization of location-based data across many businesses underscores the need for strong data governance frameworks to preserve individuals' privacy and prevent potential compromises of sensitive data. Furthermore, upholding moral principles and legal compliance depends on gaining users' trust via open data policies and permission procedures. Companies may promote the responsible and ethical use of location-based information by addressing these concerns and fostering better stakeholder confidence. Additionally, companies should limit risks connected with gathering, sharing, and utilizing geospatial data.

Key Trends for Geospatial Solutions Market

The Emergence of Real-Time Geospatial Analytics and Digital Twins: The capacity to analyze streaming geospatial data instantaneously is revolutionizing logistics, emergency response, and utility management. This development is complemented by the establishment of digital twins—virtual representations of physical assets or urban areas that utilize real-time geospatial data for simulation, monitoring, and optimization.

Democratization through SaaS and Platform-Based Models: Geospatial functionalities are progressively being made av...

The United States geospatial analytics market is experiencing robust growth, projected to reach a significant size within the forecast period (2025-2033). The market's Compound Annual Growth Rate (CAGR) of 10.04% from 2019-2033 indicates a consistently expanding demand for geospatial data analysis across diverse sectors. Key drivers include the increasing availability of high-resolution satellite imagery, advancements in data processing capabilities (cloud computing, AI), and the growing need for data-driven decision-making in various industries. Specific sectors like agriculture, utilizing geospatial analytics for precision farming, and the defense and intelligence sectors, leveraging it for surveillance and strategic planning, are major contributors to market growth. Further fueling expansion are trends like the rising adoption of Internet of Things (IoT) devices generating location-based data, and the increasing sophistication of geospatial analytics software, incorporating advanced visualization and predictive modeling techniques. While data security concerns and the high cost of implementation pose some restraints, the overall market outlook remains positive, driven by the substantial benefits offered by geospatial analytics in improving efficiency, optimizing resource allocation, and enhancing situational awareness across a wide spectrum of applications. The market segmentation reveals significant opportunities across different types of geospatial analytics (surface analysis, network analysis, and geovisualization) and end-user verticals. While the provided data indicates a significant presence of companies like Harris Corporation, Bentley Systems Inc., and ESRI Inc., the market's competitive landscape is dynamic, with both established players and emerging technology companies vying for market share. The United States' dominance in geospatial technology and data infrastructure further supports the market's projected growth trajectory. The substantial investments in R&D and the prevalence of skilled professionals in the country further contribute to the market's expansion. Looking ahead, the integration of geospatial analytics with other technologies like blockchain and big data is expected to unlock new possibilities, further driving market growth and innovation in the coming years. Recent developments include: May 2023 : CAPE Analytics, a player in AI-powered geospatial property intelligence, has extended its partnership with The Hanover Insurance Group, which provides independent agents with the best insurance coverage and prices. Integrating geospatial analytics and inspection and rating models into Hanover's underwriting procedure is the central component of the partnership expansion. The company's rating plans will benefit from this strategic move, which will improve workflows, new and renewal underwriting outcomes, and pricing segmentation., March 2023 : Carahsoft Technology Corp., The Trusted Government IT Solutions Provider, and Orbital Insight, a player in geospatial intelligence, announced a partnership. By the terms of the agreement, Carahsoft will act as Orbital Insight's Master Government Aggregator, making the leading AI-powered geospatial data analytics available to the public sector through Carahsoft's reseller partners and contracts for Information Technology Enterprise Solutions - Software 2 (ITES-SW2), NASA Solutions for Enterprise-Wide Procurement (SEWP) V, National Association of State Procurement Officials (NASPO) ValuePoint, National Cooperative Purchasing.. Key drivers for this market are: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Potential restraints include: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Notable trends are: Network Analysis is Expected to Hold Significant Share of the Market.

County Buddy is a dataset detailing the presence, count, and institutions of special populations (incarcerated individuals, college students, military personnel, and Native Americans) at the U.S. county and census tract levels. It offers geographic and demographic context to help explain variation in socio-economic indicators like life expectancy, income, and education.

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 GeoFileReader is a component designed to facilitate the reading and processing of geospatial data files. It supports various formats commonly used in Geographic Information Systems (GIS), such as Shapefiles, GeoJSON, and others, enabling users to easily access and manipulate geospatial data for analysis and visualization. The component can be integrated into workflows to streamline data preparation tasks, including loading, filtering, and transforming geospatial data, which is essential for spatial analysis and mapping projects.

The Geospatial Data Act of 2018 (GDA) serves as the Federal foundation for geospatial data management and sharing with the public. The GDA defines geospatial data as information tied to a location on Earth, including geographic location identifiers and characteristics of natural or constructed features and boundaries. This is important for HHS work with disasters, emergencies, preparedness, and responses that necessitate quality data like remote sensing, land surveying, or mapping. Here, you can explore data maps, vector datasets (points, lines, polygons), raster datasets (images, aerial photographs), and other HHS geospatial data. Explore HHS geospatial data assets below. To develop your own maps and geospatial visualizations, create a free account (sign in required) on HealthData.gov.

The interactive map creation tools market is experiencing robust growth, driven by increasing demand for visually engaging data representation across diverse sectors. The market, estimated at $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $7.8 billion by 2033. This expansion is fueled by several key factors. The rising adoption of location-based services (LBS) and geographic information systems (GIS) across industries like real estate, tourism, logistics, and urban planning is a major catalyst. Businesses are increasingly leveraging interactive maps to enhance customer engagement, improve operational efficiency, and gain valuable insights from geospatial data. Furthermore, advancements in mapping technologies, including the integration of AI and machine learning for improved data analysis and visualization, are contributing to market growth. The accessibility of user-friendly tools, coupled with the decreasing cost of cloud-based solutions, is also making interactive map creation more accessible to a wider range of users, from individuals to large corporations. However, the market also faces certain challenges. Data security and privacy concerns surrounding the use of location data are paramount. The need for specialized skills and expertise to effectively utilize advanced mapping technologies may also hinder broader adoption, particularly among smaller businesses. Competition among established players like Mapbox, ArcGIS StoryMaps, and Google, alongside emerging innovative solutions, necessitates constant innovation and differentiation. Nevertheless, the overall market outlook remains positive, with continued technological advancements and rising demand for data visualization expected to propel growth in the coming years. Specific market segmentation data, while unavailable, can be reasonably inferred from existing market trends, suggesting a strong dominance of enterprise-grade solutions, but with substantial growth expected from simpler, more user-friendly tools designed for individuals and small businesses.