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Patrick J. McGovern Foundation
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show submenu for “About”
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Patrick J. McGovern
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Ideas + Action
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Our Grants
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Digital Dirt: Using Data to Advance Soil Carbon Sequestration
Digital Dirt: Using Data to Advance Soil Carbon Sequestration
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Ideas + Action
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Our Grants
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towards the development of data-driven approaches to guiding optimized placement of off-shore wind farms to maximize energy production while minimizing biological impact.
towards the development of data-driven approaches to guiding optimized placement of off-shore wind farms to maximize energy production while minimizing biological impact.
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Our Grants
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In support of developing spatial explicit models that will serve as critical inputs to an open source platform designed to monitor extreme environmental events and advise the fishing sector on appropriate adaptive management strategies.
In support of developing spatial explicit models that will serve as critical inputs to an open source platform designed to monitor extreme environmental events and advise the fishing sector on appropriate adaptive management strategies.
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to inform the global conversation around climate change through the production of foundational climate data products and scientific analysis for key decision-makers and stakeholders at every level.
to inform the global conversation around climate change through the production of foundational climate data products and scientific analysis for key decision-makers and stakeholders at every level.
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towards the development of a functionality to index earth observations for monitoring, characterizing, and search – identifying plastic waste sites through satellite imagery to enable broader environmental detection and monitoring efforts.
towards the development of a functionality to index earth observations for monitoring, characterizing, and search - identifying plastic waste sites through satellite imagery to enable broader environmental detection and monitoring efforts.
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in support of automated, accurate, and accessible species detection in West Africa through use of machine learning (ML) on camera trap video assets, to provide insights of climate change on wildlife to enable conservation efforts on species abundance.
in support of automated, accurate, and accessible species detection in West Africa through use of machine learning (ML) on camera trap video assets, to provide insights of climate change on wildlife to enable conservation efforts on species abundance.
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in support of advancing a climate hazard data visualization and mapping tool that draws on spatial modeling to more accurately determine the location and needs of populations most vulnerable to climate change-driven health inequities.
in support of advancing a climate hazard data visualization and mapping tool that draws on spatial modeling to more accurately determine the location and needs of populations most vulnerable to climate change-driven health inequities.
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to support expanding emissionality globally with public partners
to support expanding emissionality globally with public partners
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Our Grants
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to support data-driven approaches to accelerate and empower adoption of natural climate solutions.
to support data-driven approaches to accelerate and empower adoption of natural climate solutions.
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to build and sustain the democratization of data.
to build and sustain the democratization of data.
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