Project Grant 2322325
- The National Science Foundation (NSF) awarded a $230,552 Project Grant under the Integrative Activities program (CFDA 47.083) to the University of Maine System. The goal of this 2-year grant, with a performance period from January 1, 2025 to December 31, 2026, is to leverage artificial intelligence (AI) to extract information on beetles from imagery generated by the NSF-funded National Ecological Observatory Network (NEON). This effort aims to fuel scientific discovery related to biodiversity...
- The National Science Foundation (NSF) awarded a $320,000 Project Grant under the Geosciences Program (CFDA 47.050) to the University of Delaware. The funding will support collaborative research to empower artificial intelligence (AI) to reveal phytoplankton community dynamics in coastal oceans. The project aims to address the scarcity of in-situ data for estuarine-coastal phytoplankton by constructing a large-scale database of phytoplankton observations, enabling global data sharing. It will...
- The National Science Foundation awarded a $275,000 Project Grant under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084) to Gaia AI, Inc. for a one-year project ending April 2024. The grant funds the development of techniques to combine disparate data sources including LiDAR, satellite imagery, and drone data to construct high-fidelity digital twins of forests. By expressing LiDAR metrics in a way that associates them with top-down imagery, the awardee aims to build...
- This $126,270 federal Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) aims to develop new capabilities to monitor and understand forest carbon dynamics in the Earth system. The key products and services to be delivered include: Cross-platform and cross-region learning frameworks to enable fine-scale carbon dynamics monitoring at large geographic scales. High-fidelity fast approximations of theory-based carbon forecasting models using new meta-learning...
- This Project Grant award for $600,000 from the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074) will fund the development of an interactive web-based platform called OpenForest4D. This platform will enable the generation of high-quality, research-grade estimates of forest structure and above-ground biomass across large spatial and temporal scales by applying novel statistical and AI models to a fusion of multi-source remote sensing data. The University of Florida...
- This National Science Foundation (NSF) Project Grant award under the Geosciences Program (CFDA 47.050) provides $300,000 in funding to the Massachusetts Institute of Technology (MIT) from November 15, 2024 to October 31, 2027. The award supports the development of machine learning-powered "surrogate models" to increase the computational speed and efficiency of geophysical models used for air pollution and climate research. Key project objectives include: Creating simplified,...
- This National Science Foundation (NSF) Polar Programs grant awarded to Colgate University, with a funding amount of $116,134, will support a project to map fine-scale changes in Arctic vegetation using a combination of drone imagery and deep learning techniques. The goal is to better understand how changes in Arctic plant communities, such as the expansion of shrubs and grasses, are influencing global climate patterns. The project will involve analyzing an archive of high-resolution drone...
- This $398,374 Project Grant awarded by the National Science Foundation (NSF) under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports a research project examining factors that drive the regeneration of forests in developing regions that have been deforested. The research combines satellite imagery and ethnographic methods to analyze how rural-to-urban land sales and the priorities of urban landowners contribute to tree cover gain. The project will expand geographic...
- This Project Grant award, valued at $1,018,281 and provided by the National Science Foundation's Office of Advanced Cyberinfrastructure, supports the development of OpenForest4D - a web-based cyberinfrastructure platform for next-generation 4D forest mapping and monitoring. The goal is to apply novel statistical models and artificial intelligence methodologies to a fusion of multi-source remote sensing data to generate on-demand, research-grade estimates of forest structure and above-ground...
- This $399,162 Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) aims to develop interpretable, stable, and mass-conserving artificial intelligence (AI) models to improve the computational speed and efficiency of geoscientific models, such as those used for air pollution and climate research. The project will create simpler "surrogate" machine learning models for key components like atmospheric chemistry and wildfire plume rise, allowing for...
The National Science Foundation Office of Integrative Activities awarded a $129,759 Project Grant to Colby College to leverage artificial intelligence (AI) and machine learning techniques to advance sampling strategies and prediction methods for mapping biogenic volatile organic compound (BVOC) emissions in heterogeneous forest landscapes. The project, funded through the NSF Geosciences program (CFDA 47.050), will apply AI methods to forest imaging data to plan BVOC field sampling locations in disparate forest ecosystems in Central Maine and near Manaus, Brazil. The research aims to address key questions about optimizing BVOC sampling, understanding BVOC concentration variations across forest features, and assessing the impact of spatial BVOC emission variations on regional and global estimates. The project includes support for a summer undergraduate student and plans for a summer institute on AI-driven environmental sensing and modeling to provide new STEM research opportunities.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $129.8k | 8/4/23 |