Geospatial data refers to data that represents events, objects, or features on the Earth’s surface. With geospatial data, it is easy to get a representation of the natural world frequently and in real-time.
Scientists use geospatial analytics to build visualizations such as maps, graphs and cartograms, to show current shifts or historical changes on the Earth’s surface.
This article looks at the Best Public Datasets for Geospatial Analytics currently available today.
Geospatial Datasets
Natural Earth
The Natural Earth dataset is a free and open-source dataset of physical and cultural geospatial data, available in vector and raster maps at 1:10m, 1:50m and 1:110 million scales, including rivers, lakes, borders, coastlines and populated places. It is designed to be simple, making it useful for an extensive range of applications, including cartography, education, GIS and research. The dataset is constantly maintained and updated by a community of volunteers, ensuring the data's reliability.
You can download the
Global Land Cover Facility (GLCF)
The Global Land Cover Facility (GLCF) dataset is a part of NASA’s Earth Observing System Data and Information System (EOSDIS), hosted by the University of Maryland. It is a repository of satellite imagery and geospatial data products related to land cover and land use analysis. This dataset provides data on vegetation, water bodies, urban areas, etc., at both global and regional scales. The dataset is derived from satellite sensors and processed with advanced algorithms to offer information for scientific research in climate change, biodiversity and land use planning.
You can download the
OpenStreetMap (OSM)
This geospatial dataset was launched in 2004 and is maintained by a community of organizations and volunteers, with the aid of GPS devices, aerial imagery and other sources. It is a collaborative project to create a free and open-source world map. It comprises information on roads, buildings, natural and other geospatial elements. This data is then edited and refined by the community to deliver a comprehensive map of the world. The OSM dataset is a popular alternative to proprietary maps as it is freely available in vector format and can be easily customized to meet specific needs.
You can download the
LandScan Global Population Database
The LandScan Global Population Database is a dataset that provides information on global population density and distribution on various scales. It uses
You can sign up and download the
United States Geological Survey (USGS)
This geospatial dataset is a comprehensive collection of geospatial data on the physical and cultural features of the United States. It comprises data on hydrology, geology, topography, land use/cover, mineral and energy resources. Various portals and tools, including maps, satellite images and data download services are provided by USGS for research, resource management, planning/policy making and education.
You can download the
NASA Earth Observations (NEO)
The NASA Earth Observations dataset is a collection of satellite imagery and derived geospatial products on various environmental factors such as precipitation, temperature, vegetation and land cover. This dataset is primarily collected, maintained and regularly updated by NASA’s multiple satellites and is available for scientific research, education etc. To monitor natural resources, track environmental changes, and support scientific research and decision-making, NEO provides a detailed and globally consistent image of the Earth's environment and changes across time.
You can download the
Eurostat
The Eurostat database comprises geospatial data on the European Union, maintained by the European Commission. It offers a wide range of data on the EU’s member states, including economy, population and environment, updated regularly in tabular and spatial data. This Eurostat database covers topics such as demographics, education, labour market, health, energy etc., to support the policymaking of the European Union and its member states.
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DigitalGlobe Open Data Program
This geospatial dataset is a collection of high-resolution satellite imagery for various geospatial applications such as urban planning, natural resource management and disaster response. It covers various regions of the world and is sourced from DigitalGlobe’s constellation of earth observation satellites. The program is aimed at supporting the humanitarian, scientific and public benefit communities by providing access to high-quality, geospatial data.
You will need to create a free account to access and download the
Global Biodiversity Information Facility (GBIF)
The GBIF is a repository of biodiversity data from around the world, including occurrence records, species distribution and taxonomic information. It is collected from a variety of sources, including museums, herbaria, field surveys, and remote sensing, and is made available to researchers, policymakers etc., through an accessible online website. This repository is used to support research on conservation, biodiversity and sustainable development.
You can sign up and download the dataset from the
Global Administrative Areas (GADM)
The Global Administrative Areas (GADM) database is a database of the world’s administrative boundaries, including provinces, states and territories. It offers a hierarchical dataset of the world’s political divisions, from first-level administrative divisions like a country or state to lower-level divisions like counties or districts. The data is regularly updated and available in vector format for mapping, spatial analysis and location-based applications.
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Common Use Cases for Geospatial Datasets
Physical and Cultural Geospatial Data
Population and Demographic Data
Administrative and Political Boundaries
Economic and Social Data
Satellite Imagery and Remote Sensing Data
Biodiversity and Environmental Data
Final Thoughts
Geospatial data helps us to uncover hidden spaces and have a better understanding of the earth.
Some of these datasets can be used across multiple categories and are available for anyone to download and use freely.
The lead image of this article was generated via HackerNoon's AI Stable Diffusion model using the prompt 'geospatial analytics'.