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) 📍

HazMatMapper is an online and interactive geographic visualization tool designed to facilitate exploration of transnational flows of hazardous waste in North America (http://geography.wisc.edu/hazardouswaste/map/). While conventional narratives suggest that wealthier countries such as Canada and the United States (US) export waste to poorer countries like Mexico, little is known about how waste trading may affect specific sites within any of the three countries. To move beyond anecdotal discussions and national aggregates, we assembled a novel geographic dataset describing transnational hazardous waste shipments from 2007 to 2012 through two Freedom of Information Act requests for documents held by the US Environmental Protection Agency. While not yet detailing all of the transnational hazardous waste trade in North America, HazMatMapper supports multiscale and site-specific visual exploration of US imports of hazardous waste from Canada and Mexico. It thus enables academic researchers, waste regulators, and the general public to generate hypotheses on regional clustering, transnational corporate structuring, and environmental justice concerns, as well as to understand the limitations of existing regulatory data collection itself. Here, we discuss the dataset and design process behind HazMatMapper and demonstrate its utility for understanding the transnational hazardous waste trade.

Data files for the examples in the book Geographic Data Science in R: Visualizing and Analyzing Environmental Change by Michael C. Wimberly.

TrashVisualization.RR code that merges and analyzes all of the data. SizesOfObjects:Table of sizes of objects we compare in the VR. WPP2017_POP_F01_1_TOT:United Nations, Department of Economic and Social Affairs, Population Division (2017). World Population Prospects: The 2017 Revision, DVD Edition.Population:Cleaned population data from UN data set above taking only 2015.1260352_SupportingFile:Jambeck JR, Geyer R, Wilcox C, Siegler TR, Perryman M, Andrady A, et al. Marine pollution. Plastic waste inputs from land into the ocean. Science. 2015 Feb 13;347(6223):768–71.DetailedSummary-Earth (+1-2):Coastal Cleanup Day Data from 2016-2018 https://www.coastalcleanupdata.org/WCD:World Cleanup Day Data for 2018https://www.letsdoitworld.org/wp-content/uploads/2019/01/WCD_2018_Waste_Report_FINAL_26.01.2019.pdfAnything with the word "Key":A key used for merging country names between data sets.

Keep up to date on data visualization technologies - Assess tools and keep a list of required functionalities - Be informed and prepared should a funding opportunity arise.

🌍 Ultimate Geographic Data Collection | Cities & Zip Codes

📌 Overview

Welcome to the Ultimate Geographic Data Collection, a comprehensive dataset providing valuable geographic insights. This dataset includes U.S. Zip Codes, U.S. Cities, and World Cities data, making it an essential resource for developers, data analysts, and researchers. Whether you're building location-based applications, conducting geographic analysis, or working on machine learning projects, this dataset offers an extensive and curated collection of location-based information.

📊 What's Inside?

• U.S. Zip Codes Database (Free Version) 🏙️

  • Includes ZIP codes, state associations, and geographic coordinates.
  • 🔗 Usage Condition: Requires a visible backlink to SimpleMaps US Zip Code Database.

• U.S. Cities Database (Free Version) 🌆

  • Includes city names, state information, latitude, longitude, and population data.
  • 🔗 Usage Condition: Requires a visible backlink to SimpleMaps US Cities Database.

• Basic World Cities Database 🗺️

  • Provides global city data licensed under Creative Commons Attribution 4.0.
  • 📜 Learn more: CC BY 4.0 License.

• Comprehensive & Pro World Cities Database (Density Data) 🌎

  • Population density estimates sourced from CIESIN - Columbia University.
  • 🔗 Licensed under Creative Commons Attribution 4.0 with no additional restrictions.

⚖️ License & Usage Terms

• ✅ You CAN:

  • Use this dataset in private and public-facing applications.
  • Create copies and backups for your projects.
  • Transfer the license (with provider approval via email).

• 🚫 You CANNOT:

  • Redistribute the dataset publicly without written permission.
  • Use it in a way that violates any laws.
  • Bypass the backlink requirement (for free U.S. Zip Code & Cities Databases).

🛠️ How to Use

1. Download the dataset 📥.
2. Ensure compliance with licensing terms.
3. Use it in your projects for analysis, visualization, or machine learning.
4. Provide attribution (if applicable) for free datasets.

⚠️ Disclaimer

• This dataset is provided "AS IS", without any warranties.
• The provider is not liable for any issues arising from usage.
• Users are responsible for ensuring legal compliance in their jurisdiction.

🔥 Get Started!

Enhance your geographic projects with this powerful dataset today! 🚀

📩 For any inquiries, licensing requests, or attribution clarifications, contact the dataset provider.

“Today, in the spirit of science, grey literature communities are called to demonstrate their know-how and merit to wider audiences” [D. Farace, 2011].This quotation stresses the important role of the several international organizations in producing and disseminating knowledge in the field of Grey Literature (GL): the paper aims to provide a first snapshot of the geographical distribution of GL organizations and their participation to the annual International Conference on Grey Literature over the time (in the period from 2003 to 2015. See List of Conferences on Table 2 ).Nowadays a visual representation of data is often associated with the traditional statistical graphs, in particular for representing complex phenomena by means of maps and diagrams, which allow a deeper and more focused analysis of the data. In our case the geographical representation of stakeholders in government, academics, business and industry aims at visualizing the GL community across the globe: it concerns 674 organizations which over the years have contributed to the development of a common vision on the most pressing issues of the field by using new paradigms such as Open Access and the social networks.Given this scenario the GL Community is visualized by name and country of the organization and by year, as documented by the GL List of Participating Organizations published in the thirteen GL Program Books which can be found on the GreyGuide site. The results are presented in the form of visual graphs, which confirm the international flavor of this field.

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.

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 air pollution problem in China continues to become more severe with dramatic economic development. The focus of this study was to create a map representing the spatial–temporal pattern of the air quality in the three major economic zones in China, including the Beijing–Tianjin–Hebei Economic Zone, the Yangtze River Delta Economic Zone, and the Pearl River Delta Economic Zone in 2014. A calendar view was used to visualize the daily condition of air quality and primary pollutant in each city in 2014, and geographic references were added to each visualization according to their spatial relationships. The map provides an efficient way to investigate and understand the current status of air quality and spatial–temporal patterns of air quality.

No Publication Abstract is Available

In response to the growing concern in geographic information science, which pertains to utilizing contemporary internet technology to communicate past information or knowledge for establishing foundations in geography. Recent studies have investigated geomatics solutions for historical city, and enhancing GIS skills through collaborative approach. In this study, we build upon prior research by exploring how the implementation of current technology can promote a cooperative learning environment, particularly within the realm of forestry education. Minetest, the 3D voxel game engine has high capability of modification, for visualizing natural environments and urban structures. The goal of this study was to investigate the potential of using the game engine for forestry education purposes. To meet this objective, we developed precise and detailed models of building structures and their surrounding environment. We also explored the visualization beyond 3D geospatial data, by generating analytical results of solar radiation on building roofs using GIS software. The visualization process was facilitated by the use of 3D light detection and ranging (LiDAR) data, provided by the UBC Campus + Community Planning department. The proposed approach proved to be effective in producing compatible geospatial data for visualization in the game engine. We also conducted exploratory statistical analysis to examine the relationship between building energy usage and solar radiation. The exploratory regression result of the solar radiation analysis has an R2adj of 0.19, which indicates its insignificant impact on building energy usage. Finally, the findings of this research provide a foundation for future studies that can continue to explore the potential of using 3D game engines. Keywords: 3D Geo-Visualization, Forestry Education, Remote Sensing, Light Detection and Ranging (LiDAR), Building Energy Usage, Solar Radiation Analysis

The Global GIS Mapping Tools Market is poised for significant expansion, projected to reach a substantial market size of $10 billion by 2025, with an anticipated Compound Annual Growth Rate (CAGR) of 12.5% through 2033. This robust growth trajectory is fueled by the increasing demand for advanced spatial analysis and visualization capabilities across a multitude of sectors. Key drivers include the escalating need for accurate geological exploration to identify and manage natural resources, the critical role of GIS in planning and executing complex water conservancy projects for sustainable water management, and the indispensable application of GIS in urban planning for efficient city development and infrastructure management. Furthermore, the burgeoning adoption of cloud-based and web-based GIS solutions is democratizing access to powerful mapping tools, enabling broader use by organizations of all sizes. The market is also benefiting from advancements in data processing, artificial intelligence integration, and the growing availability of open-source GIS platforms. Despite the optimistic outlook, certain restraints could temper the market's full potential. High initial investment costs for sophisticated GIS software and hardware, coupled with a shortage of skilled GIS professionals in certain regions, may pose challenges. However, the overwhelming benefits of enhanced decision-making, improved operational efficiency, and the ability to gain deep insights from spatial data are compelling organizations to overcome these hurdles. The competitive landscape is dynamic, featuring established players like Esri and Autodesk alongside innovative providers such as Mapbox and CARTO, all vying for market share by offering specialized features, user-friendly interfaces, and integrated solutions. The continuous evolution of GIS technology, driven by the integration of remote sensing data, big data analytics, and real-time information, will continue to shape the market's future. Here's a comprehensive report description on GIS Mapping Tools, incorporating your specified requirements:

This in-depth report provides a panoramic view of the global GIS Mapping Tools market, meticulously analyzing its landscape from the Historical Period (2019-2024) through to the Forecast Period (2025-2033), with 2025 serving as both the Base Year and the Estimated Year. The study period encompasses 2019-2033, offering a robust historical context and forward-looking projections. The market is valued in the millions of US dollars, with detailed segment-specific valuations and growth trajectories. The report is structured to deliver actionable intelligence to stakeholders, covering market concentration, key trends, regional dominance, product insights, and critical industry dynamics. It delves into the intricate interplay of companies such as Esri, Hexagon, Autodesk, CARTO, and Mapbox, alongside emerging players like Geoway and Shenzhen Edraw Software, across diverse applications including Geological Exploration, Water Conservancy Projects, and Urban Planning. The analysis also differentiates between Cloud Based and Web Based GIS solutions, providing a granular understanding of market segmentation.

This 90 minute session will cover data discovery and extraction via the CHASS Census Analyzer and basic GIS visualization. We will highlight the added value features of using CHASS compared to Statistics Canada Census Profiles. We will provide an overview of the steps involved in visualizing Census data in ArcGIS, including data elements and major processes. This session will also feature a critical discussion on visualizing Census data in GIS software, focusing on the technical expertise required to produce usable visualizations as well as the responsibility (and credit) for producing visualizations.

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.

Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.

This is not big dataset it have only 195 rows and 35 columns. Dataset is given geographic and other information of different country in the world. Like Unemployment rate, Fertility rate and Tax etc. By analysis this find some comparisons between countries.

Columns: Density, Agricultural Land, Land area, Population, Birth rate, unemployment rate, Co2-emission, etc.

Global Geographic Information Systems Market is segmented by Application (Urban planning_ Environmental management_ Transportation), Type (Mapping software_ Spatial data analytics_ Geospatial visualization), and Geography (North America_ LATAM_ West Europe_Central & Eastern Europe_ Northern Europe_ Southern Europe_ East Asia_ Southeast Asia_ South Asia_ Central Asia_ Oceania_ MEA)

This research explores the innovative use of a 3D gaming engine, Minetest, for visualizing changes in canopy cover change at the University of British Columbia (UBC) campus, addressing the pressing challenge of urban expansion on green spaces. We compared and visualized canopy height change for UBC campus in both 2D traditional environment and 3D gaming engine environment and we revealed a consistency between the spatial patterns of canopy cover change observed in both environments. Our findings indicate 3D environment provided multi-dimensional insights into canopy cover changes, offering decision-makers more straightforward and transparent insight than traditional maps can achieve in an immersive and interactive environment. We observed there is a significant change in canopy cover with 25 percent loss in total where Wesbrook community area experienced the most significant canopy cover loss in past 5 years due to rapid urban development. Our findings goes beyond merely presenting geographic maps and attributes from a 3D voxel game perspective. Instead, it will serve as a useful tool and references for UBC decision makers and planners to inform management plan on the pathway of building a green, well-planned community.