Filter and aggregate data to provinces or districts without code or mapping software
Find and integrate subnational data — satellite, conflict, aid, economic, health and more — from anywhere in the world into a single simple-to-use spreadsheet. For free.
GeoQuery enables individuals and organizations of all skill levels to freely find and aggregate satellite, economic, health, conflict, and other spatial data into a single, simple-to-use file compatible with Microsoft Excel and other common software. Without writing custom scripts, GeoQuery users can quickly get massive amounts of measurement data (from surveys, satellites, etc.) at fully customizable geographic boundaries (administrative zones, environmentally protected areas, etc.) and timeframes. AidData is able to provide open access to geospatial data and tools like GeoQuery through generous support from the McGovern Foundation, the Hewlett Foundation, and William & Mary.
Watch a short demonstration or go right to GeoQuery.
How GeoQuery Works
GeoQuery performs advanced spatial statistics to extract data from open-source datasets.
Every data request you make returns an email with a single spreadsheet file (CSV) where each row is a geographic boundary and each column is a variable from a requested dataset. This file can be read by nearly all software packages, and we also include a full PDF of metadata. All requests are made accessible at a unique, permanent URL to promote data sharing.
See our Quick Start Guide.
How to Get Started
Want to use spatial data, but don't have experience using ArcGIS, QGIS, or other programs for satellite imagery or spatial data analysis? Our Quick Start Guide walks you through a simple, spreadsheet-based analysis using data downloaded from GeoQuery, designed to be completed in under 10 minutes.
Find quality assured datasets curated by experts
Filter and join datasets without using code
Data is exported to a clean CSV with predictable naming conventions
Supporting documentation includes metadata
Access a permanent link of data extraction requests
Data & Documentation
Every data request from GeoQuery comes with dynamically generated documentation, and is stored at a unique, permanent URL to promote data sharing and research replication. Here is an example data request.
Documentation & Use Cases
We provide human readable documentation on every procedure and step GeoQuery uses to process data. Get documentation on GeoQuery and use cases from around the world.
Custom Data Requests
Want to request data aggregated to your own custom boundaries? Send us your GeoJSON or zipped shape file and we'll get it done.
What Data is Available Through GeoQuery?
Below is an overview of available data. For more information, visit AidData's complete catalogue of data available through GeoQuery.
GeoBoundaries (William and Mary), GADM, Global Grid 0.5 decimal degrees
Multiple data sources from the AidData research lab, including World Bank and Chinese development projects, country-specific (e.g. Afghanistan, Nepal) datasets.
Population and the Environment
Population Density and Counts (CIESIN), Slope and Elevation (NASA), Protected Areas (IUCN), NDVI (UMD GLCF), Land Cover (European Space Agency, NASA), Precipitation and Temperature (UDEL)
Conflict and Health
Conflict deaths (UCDP), Conflict Events (ACLED), Lootable Gold Deposits (GOLDATA), Child Mortality (Stanford), Ozone Concentration and Particulate Matter (TM5-FASST).
Nighttime Lights (DMSP; VIIRS), On-shore petroleum (PRIO), Gemstone Deposits (GEMDATA), Gross Domestic Product (CIRES), Drug Cultivation Sites (DRUGDATA)
Access to Infrastructure
Distance to Coastal features and Water (GSHHG), Distances to Roads (gRoads, CIESIN), Distance to country borders (GADM), Travel Time to Major Cities (JRC)
Citations & Licenses
Open Source Code
We are committed to transparency: every line of our code is open source. Get the raw Github code powering GeoQuery and a suite of R-based examples and packages that assist in the use of data from GeoQuery.
Please cite the following in any and all applications of the extracted datasets:
Goodman, S., BenYishay, A., Lv, Z., & Runfola, D. (2019). GeoQuery: Integrating HPC systems and public web-based geospatial data tools. Computers & Geosciences, 122, 103-112.
Why do I need to cite GeoQuery?
GeoQuery executes advanced zonal statistics calculations in order to compute the number in the spreadsheets that you download from the "raw" data behind the numbers from the datasets that you selected from GeoQuery. You can read more about that here: GeoQuery: Integrating HPC systems and public web-based geospatial data tools
Get information about the sources of data we integrate into GeoQuery, our data federation model, and licenses for our software and content.