Project Grant 2531450
- This $285,000 Project Grant awarded by the Division of Computer and Network Systems at the National Science Foundation (CFDA 47.070 Computer and Information Science and Engineering) supports research to advance urban tree resilience and preparedness for ice storms in Oklahoma City. The project integrates meteorological, remote sensing, and community-based data to develop a damage prediction framework that can identify high-risk areas and inform emergency response planning. Key objectives include...
- 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...
- The National Science Foundation (NSF) awarded a $169,618 Computer and Information Science and Engineering (CFDA 47.070) Project Grant to Oklahoma State University (OSU) to develop artificial intelligence (AI) and machine learning (ML) techniques that provide novel insights into the extinction risk of biological species. The project aims to leverage natural language processing and automated reasoning to address challenges in biodiversity data and species taxonomy classification, ultimately...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award of $413,467 to Arizona State University (ASU) will develop the "OpenForest4D" web-based cyberinfrastructure platform for next-generation 4D forest mapping and monitoring. The award aims to enable a wide range of users to generate on-demand, research-grade estimates of forest structure and above-ground biomass across multiple timescales by applying...
- This Project Grant award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) provides $274,990 to Trees ROI LLC to develop a 3-dimensional, non-destructive ground penetrating radar (GPR) computed tomography (CT) system with software analytics to assess the quality of container-grown root systems in nursery stock trees. The goal is to modernize industry inspection methods to improve the quality, value, and lifespan of nursery trees, promoting...
- The National Science Foundation awarded a $188,280 Project Grant under its Geosciences program (CFDA 47.050) to the Regents of the University of Minnesota. The grant supports a two-year planning effort to assess the synergies and trade-offs between the benefits and burdens of urban trees and forests. Key objectives include: (i) analyzing the convergent conditions of tree-related ecosystem services and disservices in metropolitan regions, (ii) evaluating tree species-level vulnerability to...
- This Project Grant award of $250,000 from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports the development of advanced AI-driven tools to help communities across the U.S. better understand and mitigate environmental risks from extreme weather events. The project aims to build an AI model that integrates diverse datasets, including spatial, hazard, and socioeconomic data, to analyze regional environmental risks and community...
- 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...
- The National Science Foundation's Geosciences Program (CFDA 47.050) awarded a $672,505 project grant to Cleveland State University to investigate how urban tree canopies impact stormwater runoff and water quality. The 3-year project will use advanced methods from hydrology, ecology, and remote sensing to quantify how rainfall interception, stemflow, and throughfall vary across common urban tree species like oak and maple. The research aims to determine which canopy traits are most effective...
- The University of Oklahoma (OU) was awarded a $2,246,892 Project Grant from the National Science Foundation's Geosciences Program (CFDA 47.050) to advance the science and decision-making needed to support a national wildfire warning system. The 3-year project, running from September 2025 to August 2028, aims to improve fire prediction, risk communication, and coordination among emergency agencies to help communities respond quickly to wildfires. The research is organized into three integrated...
The National Science Foundation (NSF) awarded a $1,199,990 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Oklahoma (OU) for the "TREE-CARE: TREEFALL RISK EVALUATION AND EMPOWERMENT FOR COMMUNITY ASSESSMENT AND RESILIENCE ENHANCEMENT" project. This project aims to develop a science-based, data-driven, and community-centered framework for assessing and managing tree-related hazards in urban areas. It will integrate AI-powered image recognition, numerical fragility modeling, and historical hazard data to identify individual trees at risk of failure during high-wind or ice events. The project will also create models that link tree structure to damage potential and leverage machine learning tools to automate the detection of hazardous tree features. This initiative will empower communities to reduce risk, enhance infrastructure resilience, and adapt to increasingly severe weather conditions through collaboration with municipal partners, utility companies, and residents in Oklahoma. The award period runs from September 1, 2025, to August 31, 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $1.2m | 8/14/25 |