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GeoQuery enables individuals and organizations of all skill levels to freely find and aggregate satellite, economic, health, aid, 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.


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.

Quick Start Guide (PDF)

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.

Watch a short demonstration or go right to GeoQuery.


Expert curation

Find quality assured datasets curated by experts

User Interface

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

Video Walkthroughs

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.

Boundary Data

GeoBoundaries (William and Mary), Global Grid 0.5 decimal degrees, Chinese financed development project sites, major cities, and more

Measurement Data

International Aid

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).

Economic Development

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. You can access the raw code powering GeoQuery on GitHub.

Github  →

Citing 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

License Information

Get information about the sources of data we integrate into GeoQuery, our data federation model, and licenses for our software and content.

Data Licenses & Providers