National Geographic

Apply By:  08 Oct . 2018

Our planet is at a crossroads—there is both an opportunity and a critical need to act. We must increase the global understanding of our planet and create a community of change, driven by data and cutting-edge technology, to adequately address the many pressing scientific questions and environmental challenges we face. Artificial intelligence (AI) and machine learning can help transform conservation work by collecting and analyzing more precise data, producing faster and more meaningful insights, and accelerating promising solutions.

The National Geographic Society (NGS) and Microsoft’s AI for Earth program are partnering to support the exploration of how AI can help us understand, engage, and protect the planet. The $1 million AI for Earth Innovation Grant will provide grants to 5-15 novel projects that improve the way we monitor, model, and ultimately manage Earth’s natural systems for a more sustainable future. 

The grants will support the creation and deployment of open source trained models and algorithms that are available to other environmental researchers and innovators and thereby have the potential to provide exponential impact.

To qualify, applications should outline a proposal to use AI for conservation in at least one of the following core areas: 

Biodiversity conservation: Species are going extinct at alarming rates, and our planet’s last wild places need protection. AI can help in areas like:

  • Protected area management and restoration
  • Sustainable trade
  • Invasive species and disease control
  • Pollution control
  • Realizing natural capital (including valuing natural capital, species identification)

Climate change: Extreme weather events, rising sea levels, higher global temperatures, and increased ocean acidity threaten human health, infrastructure, and the natural systems we rely on for life itself. AI can help in areas like:

  • Climate resilience
  • Extreme weather and climate modeling
  • Sustainable land-use change
  • Ecosystem services (including carbon sequestration and afforestation/reforestation)

Agriculture: To feed the world’s rapidly growing population, farmers must produce more food on less arable land, and with lower environmental impact. AI can help in areas like:

  • Land-use planning and management
  • Natural resource conservation
  • Sustainable supply chains
  • Climate-resilient agriculture

Water: In the next two decades, demand for fresh water—for human consumption, agriculture, and hygiene—is predicted to dramatically outpace supply. AI can help in areas like:

  • Water supply (including catchment control)
  • Water quality and sanitation
  • Water efficiency
  • Extreme-event (droughts, floods, disasters, etc.) management
  • Healthy oceans


Grant Resources: Typical proposal requests should be less than $100,000; however, applicants may request up to $200,000. Successful applicants may use awarded funds over one year. (Please see the Preparing Your Proposal page regarding stipend eligibility and other budgetary guidance.)

In addition to financial support, successful proposals will receive free access to AI for Earth API’s, applications, tools, and tutorials, and support for their computational work on Microsoft Azure.

Project Requirements: All models supported through this grant must be open source, and grant recipients must be willing to share their models for use by other environmental researchers and innovators.

Applicant Qualifications: We recommend that the main applicant has a demonstrated background in environmental science and/or technology, and we require that at least one member of the team has strong enough technical skills (such as AI, machine learning, statistical data analysis, scientific modeling, software development, and/or remote sensing) to complete the proposed project successfully.

We believe great ideas spring from a diversity of experiences, and thus encourage applications from all over the world.

Application Categories: When applying for this RFP, please select “Changing Planet” in the Lens dropdown menu on the Project Description tab of the application.


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